Inventory and Assessment of Natural Resources

Defra Project Code: NR0101

D Osborn, GJL Leeks, N Thompson, LA Ball

With special inputs from

L. Rickards, I Bradley, J Vickery

With contributions from those shown on the following page.

Contributions on specialist topics from:

INDIVIDUALS ORGANISATION TOPIC

Andrew Baker Countryside Agency Access and landscapeHeiko Balzter CEH Soil and Vegetation CarbonMary Barkham ERFF ERFF DatabasesHelaina Black CEH SoilsIan Bradley National Soil Resources

Institute, Cranfield University

Soils

Neil Cape CEH Air qualityPeter Carey CEH Countryside Survey Ray Haines-Young Nottingham UniversityJane Hall CEH Critical LoadsMark Hill CEH/BRC Biodiversity Val Kirby Countryside Agency Access and landscape issuesJohn Kupiec Environment Agency ERFF Report and earlier

AssessmentsBrian Marker ODPM ODPM dataholdingsTerry Marsh CEH Floods and NRFAAndrew McKenzie BGS GroundwaterJohn Murphy CEH RIVPACSColin Neal CEH Water QualityCaroline O'Sullivan CEH Water Poverty IndexJohn Packman CEH Hydrological modellingTerry Parr CEH ECNMark Parry Defra SPIRE InitiativeKeith Porter English Nature BiodiversityJohn Rae Defra Air QualityBrian Reynolds CEH Data for WalesLesley Rickards BODC Marine ResourcesGeoff Smith CEH Land CoverIsabella Tindall CEH LOCAR and LOISJuliet Vickery British Trust for

OrnithologyBirds (Various data sets)

Philip White ODPM ODPM dataholdings

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Contents

EXECUTIVE SUMMARY 4

1. INTRODUCTION 7

2. APPROACHES 8

3. DEVELOPMENT OF AN INVENTORY AND ASSESSMENT OF DATA FOR PROTECTING NATURAL RESOURCES 11

4. FINDINGS 12

5. MENU FOR THE FUTURE 40

Appendices and Annexes

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Executive Summary

The databases held by the National Environment Research Council and a number of other bodies – principally the National Soil Resources Institute and the British Trust for Ornithology and English Nature – have been examined to determine the degree to which they could be used to compile an inventory of UK natural resources and to determine the extent to which this knowledge could be, or is being, used to assess both the state of these resources, and also trends in them and threats to them. The work is an initial contribution to the new Defra initiative on Natural Resource Protection. This is one of a number of Defra initiatives designed to help deliver the UK Government strategy on Sustainable Development. This is set out in the recently published Securing the Future, see website: http://www.sustainable-development.gov.uk/publications/uk-strategy/uk-strategy-2005.htm .

We asked data holders and managers to complete a simple form (agreed with Defra), telling us the basic facts about their data, and how it was used, or might be used, to strengthen the evidence base on the following sets of natural resources: Biodiversity (including habitats and ecosystems), Soils, Air Quality, Water, Marine Resources, and Access to the Countryside. Issues linked to landscapes were likely to be covered more completely in a related project, but we considered landscape elements of datasets we had responses for. Our study has not been comprehensive and we have not provided a list of all the existing data sets relevant to Defra’s Natural Resource Protection agenda. This is because many organisations now make this information available on publicly accessible web-sites. In this study we sought examples of a range of reasonably well developed data sources that would illustrate what is being and could be done to meet the needs of evidence-based policy in Natural Resource Protection.

Efforts were made to identify exemplar datasets at both UK and international levels, and to gain a wide perspective on the use, integration and perceived value of data in each of the set of natural resources identified. There are few suitable international comparators.Respondents varied substantially in the way that they dealt with our enquiries. In many cases respondents referred our enquiries to central or higher parts of their organisation. We believe this indicates the seriousness with which respondents viewed the projects aims and objectives and the significance of the underlying policy needs that our questions addressed. This made synthesis of responses slightly more difficult than anticipated.

Main FindingsFrom a study of all the datasets and databases examined in this short study the main contractors for it found the following: There are few high quality data sets that can be regarded as fully functional with respect to the needs of Natural Resource Protection, but a high number that are partially functional. There is considerable potential. An inventory could be constructed. There is substantial variation in the time and spatial scales over which data is collected and the spatial coverage which is available. Some data of high value to the scientific community, or various parts of the user community, has not yet been used to address some Natural Resource Protection issues (eg the amount of data relevant to countryside access is considerable but no overall measures of access exist). Certain data sets have only been collected for short periods of time, but amongst these are examples where the research community and users have linked scientific and user aims to address issues relevant to Natural Resource Protection policy needs, (e.g. NERC Thematic Programmes).

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Research datasets appear to be underused in assisting the development and strategies of larger scale data collection by regulatory bodies. This may be due to insufficient or inappropriate mechanisms for communication between research and user communities. In certain cases, dynamic databases exist, where information is gathered for the specific purpose of meeting on government policy or delivery target, (e.g. EN PSA targets). In these excellent examples, the only issue for the scientific community is the degree to which the data reflects ecosystem or other ecological processes. The very best system would of course do this; protecting. function by measurement of an ecological process. In international arenas we were made aware that some broad approaches to environmental protection (e.g., UNECE approaches to critical loads and OSPARCOM considerations) allow obligations to treaties and conventions to be met differently by member states and signatories. We conclude therefore that there cannot be many good international examples of datasets being acquired or used for National Resource Protection. In federal countries some states may have more advanced positions on Natural Resource Protection issues than the federal authorities across the nation at a national level (e.g. USA, Germany). In some instances, we find that the data originators may not be fully aware of the uses to which data is being put by the user community (e.g. CEH Flood Data, LCM). A number of data sets show considerable potential for development as part of the NRP evidence base. These include datasets and databases of the Centre for Ecology and Hydrology, the British Ocenaographic Data Centre (and other marine groups such as the Center for Environmental, Fisheries and Aquaculture Science), the British Geological Survey, the National Soil Resources Institute, the British Trust for Ornithology, English Nature. Some of these organistaions databases have European parallels, e.g. RIVPACS, and even County Councils’ footpath information. A number of other initiatives are underway asking questions close to Natural Resource Protection interests (i.e. a Cambridge Conservation Forum / MacArthur Foundation work on environment protection criteria and environmental limits) In general there was little link between plot-scale data sets that examined processes and large scale surveys focused on major environmental factors or impacts. There is a need to integrate both data and mind-sets here. There was increasing evidence that interest groups of various kinds are prepared to get together to obtain their own information and distribute it back to interested parties in value added forms (initialising data integration) (e.g. the National Biodiversity Network). There is a role for several different types of information in an Inventory, eg Atlases, Monitoring Schemes, Surveys and plot or reach-based studies (catchments would be needed at landscape scales). Projects such as Countryside Quality Counts also have a place. Not all data holders have commented about existing or potential data integration or the lack of it. A number of good examples of integration exist. There is a reluctance to identify problems in a public document. There are also clear gaps in integration (e.g. in linkage or compatability of data collected in adjacent sub-environments (eg. air and land, river and estuary). Because, as mentioned above, some data originators do not know how their data is being used, this raises the possibility of inadvertent data mis-use. Lack of communication between different dataholders and between data collectors/holders/users may indicate that opportunities regarding synergistic development and optimised collection/use of data relevant to NRP may not be fully realised. Respondents had widely divergent issues on whether data was used or generated with respect to ecosystem services or functions. These concepts are not well embedded in all parts of the science community.

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1. INTRODUCTION

This overview aims to convey the main messages learnt from this rapid study of the information available on natural resources that could (a) contribute to making an inventory of natural resources for the UK and (b) be used to assess these resources in ways relevant to policy needs arising from the UK Government’s sustainable development strategy, Securing the Future, published earlier in 2005.

In doing this work we first established Defra’s main requirements, developed project objectives and a series of questions to ask data holders and, from the responses to these questions and discussions with data holders and selected government departments and agencies, derived the main findings

There are a large number of different types of information that could be, or are being, used to help protect the environment’s natural resources. These include:

(a) indicators of environmental state or health, such as those showing trends over time for farmland birds;

(b) modelled or measured estimates of resources of direct economic relevance, such as fish stocks;

(c) spatial information on the nature of the resource, as is the case for soils and biodiversity;

(d) information on the stock and state of natural resources over spatial and temporal scales of the kind provided by the Countryside Survey;

(e) information on the condition of specific resources delivering a particular ecosystem service, such as the nature conservation material delivering PSA targets or information on water supply;

In some cases there are considerable amounts of relevant data but no generally agreed way of providing a measure of that resource or of the way an ecosystem service is delivered from that resource. An example of this type of situation is probably illustrated by the “access to the countryside” aspect of natural resource protection.

The range of available information is very considerable and there are many different ways in which the information is used to assess the resource. Some of the material is easy to understand and interpret. In other cases skilled interpretation is needed. In addition to the “base” sets of information mentioned above there is work in hand on derived datasets that may provide further opportunities for measuring delivery of ecosystem services.

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2. APPROACH

2.1 Aim

At a high level, to review and assess the means by which the quantity and quality of natural resources in the UK are identified, monitored and assessed, with particular reference to the delivery of economic functions or ecosystem services. Commentary will be included on:

(a) the uniqueness and on environmental or ecological significance of the different resources;

(b) gaps in reporting; and,(c) opportunities for new approaches and integration – especially those that might

lead to enhancement of natural resources in future or more effective delivery of ecosystem services and functions.

2.2 Specific objectives

1. (a) Collate a list of quantity and quality of available data on natural resources in the UK indicating how this information is used to measure the stock of natural resources, assess change over time and variation in space of a range of parameters that might be linked to the delivery of ecosystems services and/or economic functions

Note: the phrase “natural resources” covers: biodiversity (including its habitats and ecosystems); water quality and supply; the soil; air quality; the marine environment; landscape; recreation and access to the natural environment; ecosystem services.

(b) Indicate how the causes of changes can be attributed and predictions made as to likely future trends in natural resources and provide examples of how this has been done.

2. Compare this list with the data available in other countries, indicate the methods used to gather this information and how such methods are developing (e.g. with respect to attributing change, predicting trends over time under different climate or land use scenarios).

3. Identify gaps in the coverage of the data sets and data bases identified in Objective 1 with respect to the ecosystem services and functions that are relevant to policy, regulation or market instruments.

4. Identify the emerging technologies and approaches for measuring the quantity and quality of natural resources and how these might be utilised to reflect the status of ecosystem and human health as well as ecosystem service sand functions and indicate, if possible in the time available, how they might help enhance natural resources in future.

5. To compile a menu of “indicative” opportunities including:

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(a) New ways to monitor the quantity and quality of the stock of natural resources.(b) New ways of developing natural resource assessment techniques with reference to the economic functions, ecosystem services delivered and upcoming integrated monitoring techniques; if possible, assess these new methods from a risk management perspective.(c) Potential mechanisms for communicating natural resources information and key issues to stakeholders, in ways that may constructively change behaviour of individuals or groups.

2.3 The needs of human beings and their interactions with natural resources: broad resource groupings

The nature of the basic requirements of human beings (or for that matter many other living organisms) have not changed over many thousands of years. At the minimum these are: air, food, water, shelter and sources of energy to use to escape the limitations that would otherwise be placed on human development by environmental constraints. Next come sources of minerals, fibres and other chemicals with which to produce a range of goods and services and improve living standards, fight disease and, it is hoped, protect and improve the quality of life. Finally, perhaps, comes the need for additional resources (or supplies of derived goods and services) with which to buffer against hard times. Beyond that point there develops a need to understand and manage risks and, if resource use threatens to outstrip supply, the wherewithal to protect these resources for future generations under the terms of some system of sustainable development. For the foreseeable future, human well-being depends on the existence of a functional ecosystem where supplies of water and nutrients are replenished on a predictable annual cycle that permits food crops to grow in a stable soil. For this to happen the chemical composition and physical structure of the environment must interact with elements of biodiversity. From the above, the key natural resources on which people depend are (those in italic bold type are already on the Defra list, see Objective 1 above):

AirWater (including the Seas)SoilMineralsBiodiversity

From which are derived:

Habitats and EcosystemsCatchmentsLandscapesEnergy sources

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There must then, of course, be access to the use of these resources and the means to manage any risks associated with their use.

2.4 Protection and enhancement: working at the limits

For several decades environment protection has rested on the idea of preventing or avoiding harm or damage. Uncertainty, of various kinds, has been handled by use of the precautionary principle. In some cases, the idea of protecting resources from harm or damage has been supplemented by the idea that resources need to be enhanced or restored (often such ideas have been introduced after evidence of harm or damage has emerged). To ensure sustainable development some degree of reserve resources may needed to be needed to ensure stocks do not become depleted. This suggests working resources up to their limits is unwise. Environmental limits are not considered further in this report as they are the subject of another current study (led by Nottingham University).

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3. DEVELOPMENT OF AN INVENTORY AND ASSESSMENT OF DATA FOR PROTECTING NATURAL RESOURCES

3.1 Inventories and assessments: functional definitions

The terms “inventory” and “assessment” both have long usages and are understood in very general terms to mean:

Inventory: A detailed list of articles, such as goods and chattels, or parcels of land, ……………sometimes with a statement of the nature and value of each; hence, any such detailed statement of property, goods or furniture, or the like.

Assessment: A means of reasoning about and estimating the value or condition of a thing, sometimes at a particular instant and sometimes used repeatedly (for example, as when used with respect to taxation).

A modern inventory, as used in commerce and industry, also contains information on the rate at which stocks are being used and can be replenished; it reflects the dynamic of the resources it lists as well as containing information on the stocks and values of the items in the inventory and information on their nature. For an environmental inventory “nature” would include factors such as resource quality and distribution now and, probably, predictions for the future based on known use and replenishment patterns and rates.

Modern assessments, as used for environment protection purposes, take account of many interacting factors (as in the case of Environmental Impact Assessment). A major consideration in using such approaches to make decisions about environmental management must be the services to be delivered by the resource. Some resources, of course, deliver different kinds of services. This is obvious in the case of water and soil. Thus different kinds of assessments will be needed depending on the ecosystem service being delivered.

An overall inventory and assessment system is probably needed where an inventory of natural resources feeds into assessments and where information from assessments feeds back to the inventory to facilitate tests of whether the resource dynamic is sustainable.

3.2 Questions in the tables: Relevance and purpose

A standardized table was distributed to targeted experts across the full range of natural resources as defined in the project specification. An example was given of a particular category and the broad area for which information was required was indicated. The precise sub-division of each category was not prescribed, ie the numbers of rows for each resource category were at the discretion of the expert opinion. It was indicated to each expert, that the purpose was not to duplicate detailed listings for all UK environmental data. The intention was to fully represent the data or databases that can

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contribute at a high level to provision of an overall inventory or assessment of UK natural resources. Therefore, there is an emphasis upon longer term and large scale.

The Table was designed to be largely self explanatory, with all fields visible, and to maximize response rates, by ensuring it could be easily and quickly filled in. Most cells in the Data type rows can be completed by ticking or inserting a score. In some cases a single word or short comment was needed. Support notes were provided. At an early stage, the table and notes were tested, with Defra officers and major data providers.

Below is a listing of the main column fields which require further explanation regarding their relevance and purpose:

Length of time series – There are examples of important high quality information that has only been collected once. Such data were entered here in a Less than 5 years column,, with an accompanying note of qualification. The less than 5 years category was expected to capture one-off surveys and those associated with the 3-5years cycle of research projects. Longer time series are often intended to provide indications of trends, whilst those of 20 years or more often provide key baseline measurements, providing important data to detect and predict major changes in natural resources.

Major data managers, holders or generators – This provided a useful way of indicating the sources of more detailed information and the organizations with current responsibility for stewardship. “Orphaned” data is a reference to data that is no longer being actually collected and is no longer under the active care of any organisation.

Spatial Coverage – There are some datasets, which despite collection at local or regional levels, may yield valuable data which is of value, in setting monitoring standards and strategy in addition to providing inputs to policy at the national and UK levels. Data of particular relevance in England Scotland or Wales was also specifically identified. Sets that dealt with “ecosystems” or “ecosystems” relevant to natural resource protection were also sought.

Stocks and Assessments – A key underlying element of interest is whether data on natural resources can be used to make statements about the stock or resource, its condition, threats to it or the sustainability of its current and future use. Information on these issues is important. For several columns we have used the word “could” as we need to capture the full extent of what you think is possible.

Integration – Some data remains and is useful in freestanding forms. However, there are opportunities to integrate data at the monitoring, archiving and processing stages. This is made possible by technological changes and is increasingly required to meet the operational needs of natural resource managers and stakeholders. Respondents were asked to give examples of the extent to which data on natural resources is “joined-up” and to indicate any institutional impediments to data integration.

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Gaps – An important aspect of this work is to identify gaps. Therefore, the flagging of gaps in knowledge was requested, including deficiencies in integration or perceived new opportunities of any kind were encouraged.

International exemplars – Datasets identified from non-UK parts of the world provide useful examples and in some cases benchmarks to demonstrate how data may be used to protect natural resources, through compilation of inventories or by making assessments.

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4. FINDINGS

This section of the report deals with the findings derived from our consultations with a wide range of organizations and from the responses received on the proformas sent to key dataholders and managers. The proformas provided a wealth of information, and we have had to summarise this using a “traffic light” technique. The summary table is at Annex 1 and indicates considerable differences between the different types of data. Interpretaative remarks for the summary table are to be found at the end of Section 4.1 which provides a commentary on the proformas and on a number of other sources of information we considered in the course of this study. The situation at present is quite complex, with much scientific work in hand and many national and international drivers in play that tend towards requiring States to construct inventories of their natural resources, assess the sustainable use of these, the security of supply and threats to (a) the resources themselves and (b) patterns of production and consumption of goods and services derived from the resources. In this section, specific points from individual table returns will be highlighted (Subsection 4.1). Sections 4.2 and 4.3 cover general points regarding the identification of trends, gaps and data priorities in Natural Resource Protection.

4.1 Commentary on individual Natural Resource Protection (NRP) “subject categories” based on returns from respondents

There are vast numbers of datasets available on natural resources and other aspects of the environment. The numbers are far too great to examine each one in this study, so we have selected datasets and sources that it was hoped would reveal general principles of inventory and assessment work for NRP purposes.

Overall, both nationally and internationally, data on natural resource issues is available from a very wide range of sources in a very wide range of different formats. By way of example: for information accessible through the internet information on some resources is readily available as data tables whilst other material is available mostly in the form of graphs and charts. Some material is available that has been derived from single datasets whilst other material has been generated as a result of integration of several – or even many – datasets. Sometimes data has been used as inputs to models to make predictions about the environment, and on other occasions datasets have been combined to derive indexes of environmental performance.

To keep this study manageable, it was centred on those datasets and databases that seemed representative of the broad range relevant to NRP issues and those that seemed most likely to be most relevant to the aims of the study – which were to test the potential of their use in an inventory of natural resources and for assessing the resources in a variety of ways.

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The variety of datasets available and the diversity of their sources was such that a high degree of selection has been required. Selection of datasets was based on a number of considerations that emerged during the preliminary stages of the work where we recognised that:

(a) the historical origins of datasets differed markedly; (b) that it would be necessary to interact with data originators and managers on

questions about both the suitability of data for use in an inventory and its use for assessment purposes; and,

(c) some datasets were used extensively for policy or regulatory purposes whilst other were generated purely for scientific ones.

The characteristics of a range of different types of information on natural resources were examined. These ranged from databases assembled form wide ranging survey work in the UK that has few if any international equivalents (e.g Countrside Survey), to consideration of material about single aspects of NRP (such as data on chemicals affecting air quality).

Comparing all the material received has been done by taking the qualitative scores contributors were asked to return on the characteristics and uses of their datasets and, following the example set by the recent Defra report on marine resources (Charting Progress), reducing these to a traffic light type analysis (Annex 1). Although the results of this form of analysis cannot be pushed too far – especially as respondents took very different approaches to the returns they made – it seems to be the case that there are considerable differences in the suitability of various broad types of information. For example, whilst some datasets on soil seem to be very suitable for both inventory and assessment purposes, for the most part a good deal more work will be required before datasets in this area can make a major contribution to NRP initiatives. In contrast, many of the biodiversity data streams are already suitable.

In certain cases, respondents indicated that their material was developed for particular purposes (e.g determination of critical loads of sulphur and nitrogen) and that these databases, although designed to assess a threat to a resource (e.g. soil) were probably not suitable for NRP purposes. This is at least partly because such datasets and databases are actually derived from a wide range of separate data sources. There was no doubt that some groups we approached had more difficulty responding. In general, more responses were obtained from the scientific community than from regulatory bodies or providers of ecosystem services. This may be because our study has focused on data about natural resources and not on ecosystem services per se. The following sub-sections provide a commentary on the major responses received from consultees on the proformas.

4.1.1 DATASETS AND DATABASES DEALING WITH ENVIRONMENTAL SYSTEMS

Countryside Survey (CS)

The CEH CS Coordinator has provided a comprehensive set of tabular information. Overall the data is of a high quality, and of a large quantity arranged in time series

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although collection is 1-2 per decade. Information can be used to make inventory of the stock of resources, or can be used to assess condition, sustainability and threats. Generally most of the data gathered in CS is being used to measure ecosystem service delivery in the form of indicators of sustainability.

During the scoping studies for CS2007, it has also become apparent that CS resources are also used by specialist staff in Departments and Agencies to provide policy groups with broader information on countryside matters. This illustrates the increasing utility of CS

CS approach is now attracting the attention of the EU, where the CS approach is likely to be adopted as the way of tracking land use change by field survey, and the environmental research community who are planning to take advantage of the next CS to learn more about the distribution of biodiversity in the UK. Further integration between the CS, Land Cover Map and other initiatives (such as the Defra-funded Countryside Quality Counts project) will provide a set of linked databases that will be able to inform both NRP issues and countryside policy more generally. Such developments are timely with respect to the formation of Natural England.

CS is used as source material for many purposes so there is a high degree of integration with other datasets. Integration with social and economic datasets is poor at present. Data on soils cannot be used as a measure of stock.

CS can provide information on compoenets of the landscape but does not provide any overall measure of landscape.

Some further data on CS is provided at Appendix 1.1

Land Cover Map (LCM)

There are many rapidly developing Earth Observation techniques able to contribute to a census of land cover for the UK. The last LCM provided data on broad habitats. Future work could include aircraft as well as satellite based sensors now that computing power has increased sufficiently. This work is increasingly used to support government indicators of sustainability and deliver a range of ecosystem services. Because of the way LCM data is distributed to the user community little feedback is received from users on the way the LCM is being utilized. This makes it difficult to properly gauge the level and type of use made of this comprehensive database of UK land cover.

Of the information on land cover (some of which is very old), the LCM is probably the most suitable for making NRP assessments. Early attempts at mapping land cover suffer from methodological inconsistencies that make it difficult to obtain national statistics. At present trend data can only be extracted by manual efforts. Potentially, earth observation techniques can be automated, and a “change” product is being considered for the next CS in 2007. Trend information might best be extracted by asking narrow questions of the database, e.g about each cover type. The assessment of spatial pattern of land cover units within a data set could in itself help identify threats. For instance, an industrial complex

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could be seen as a threat to the surrounding landscape and the type and level of threat will depend upon the adjacent land cover type and the processes occurring at the complex. Land cover alone can identify some potential areas of threat, but additional data sets are required to fully understand and assess what is happening. An example with BGS that was considered in the past has been slope stability, where the type of land cover (e.g. agriculture or trees) will determine likelihood of slope instability.

The LCM database has been used in combination with other datasets to provide estimates of the carbon content of key environmental compartments. Until recently much relevant satellite data was discarded as there was no way of retaining it. Although problem is now rectified, this process is still not automated.

The LCM can also be integrated with digital terrain maps. In this format it might find applications for those aspects of NRP concerned with landscape.

Environmental Change Network (ECN)

This is a site based system, 50-60 sites measuring a wide range of environmental variables some of which, such as the biodiversity data, are relevant to Habitats Directive and CBD 2010 target. As the data set extends in length it becomes more widely used. There is increasing evidence of integration with other NRP areas e.g. birds and butterflies, RIVPACS and the water harmonised monitoring programmes.

Gradually, datasets are becoming more valuable for monitoring long term change. Some threats to resource can be assessed from a scenario perspective. Some of the data has unrealised potential.

Within the broad categories defined for this study (e.g. habitats, lakes, rivers, ecosystems) it is possible to find some significant trends in some (but not all) variables. However, ECN time series are relatively short and it is not yet possible, in most cases, to attribute these trends to specific causes.

Marine Resources

The British Oceanogrpahic Data Centre were consulted on this topic and have provided information on the extent and nature of data holdings on the marine environment in the UK at Appendix 1.5. The recently published Defra report Charting Progress: An Integrated Assessment of the State of UK Seas provides a comprehensive overview of material very relevant to NRP issues. The information does not need to be repeated here.

4.1.2 DATA ON WATER

Surface water

This is a classic dataset. It is comprehensive with good UK coverage and widely used nationally and internationally.

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Despite excellence of this material there are gaps at the land-water interface and in the representativeness of hydrological conditions other than at gauging stations. There is a recognized need for further integration of the information on flow with water quality databases. This would make it easier to assess sustainability issues and threats to the resource, for example, by pollution.

As with many other datasets and databases examined, there are outstanding issues with respect to detecting trends over time. This is something of a general finding, if not a surprising one, and should be regarded as an important aspect of the NRP evidence base. In the case of water resources and flood magnitude the trend issue is, of course, scientifically complex and politically sensitive. Broadly speaking, the national river flow archive and floods database show no compelling evidence of trend. Natural variability and the pervasive impact of artificial influences on many flow regimes implies the need to be cautious when interpreting any national/regional signals of change (apparent short-term trends being especially problematic). Further discussion of these issues is needed but because of the detailed nature of the scientific and practical issues involved, this is well beyond the scope of this report.

Groundwater

The quantity and quality of this information is high. Information is gathered from a number of boreholes and wells in situations where the characteristics of the aquifers are well understood. By integrating the raw data into models, it is possible to make assessments of the stock and condition of the resource. In this area, more work may be needed on spatial variability as pressures on water resources are likely to increase with time, partly as the result of changing climatic conditions and partly as a result of changing patterns of demand for water dependant ecosystem services, many of which are related to human population demography.

Trends can be detected for boreholes, wells, and aquifers, especially with respect to groundwater level and quality. Because of good links between industry and those conducting and interpreting the monitoring data, continuities between the natural resource and the ecosystem service are sufficiently clear to enable effective environmental management.

Research catchments

LOIS and LOCAR are two NERC Thematic research programmes which provide information on rivers in particular catchments. Although the quality of the data is very good the focus of these studies was on the generation of scientific understanding and methodologies rather than policy. Consequently the data cannot be used to create an inventory or assess the national resource directly. Some of the data can be used to assess threats (e.g. from chemicals). The data holders responses on the assessment issues were variable, some regarded these as “not applicable” and others thought their datasets were

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not suitable for such purposes. This illustrates the type of gap can exist between the needs of the scientific community and the needs of a policy one.

4.1.3 DATA ON AIR QUALITY

Very substantial amounts of Air Quality data exist. NETCEN manage a considerable amount of the data resource, and much of the data is available through an archive where some datasets stretch back over 50 years. The database on air quality contains some 150,000,000 records making it one of the largest encountered in this study. As well as the NETCEN contribution, organisations such as CEH and key universities support the critical loads work, centered on managing potential impacts.

The transboundary nature of air pollution has driven a number of developments in air quality work that are not so prominent in other areas. This includes use of emission inventories.

Modelling, based on a sound understanding of atmospheric chemistry processes, plays a key role in making use of the raw data. Modelling is particularly necessary in this area as the spatial and temporal scales on which atmospheric process occur differ from the scales at which data can be collected. This type of process-based approach has proved a robust one, and air quality management has a strong evidence base as a result.

A feature of air quality information is that trend data can be obtained. Thus, it can be said at present, that: sulphur dioxide levels are going down; oxides of nitrogen are fairly stable; ozone is going up slowly (although peaks are coming down due to controls on emissions); ammonia is fairly stable. Some chemical species have too short a time series for trends to be clear.

Air quality data is not just about atmospheric gases, but also takes in aerosols and particles. Some information on the dynamics of these substances is available: For example, there is a long-term downward trend in sulphate that reflects to a degree emission controls on sulphur; the nitrogen story is more complex – here there are clear non-linearities with less decline in deposition than expected. The time series for particles are generally too short for trends to be detected.

There could be more integration of information on atmospheric chemistry and physics and that on the habitats and species likely to be affected by chemicals in the atmosphere. More work may be needed here to account for the level of environmental heterogeneity exhibited in the units of the environment commonly used to manage impacts of airborne chemicals at present. Because this would involve the need to work with incomplete information and / or information with a high degree of uncertainty certain emerging knoeldege management approaches may be needed to help national and local stakeholders reach decisions on land management options that affect air quality. These approaches include Dempster-Shafer formalism.

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4.1.4 DATA ON SOILS

Soils

Information on soils came from two main sources, CEH and NSRI. The text that follows was compiled by the main authors from the tabulated returns from these two bodies. Further information on the National Soil Inventory is provided at Appendix 1.2.

Large numbers of datasets exist relating to top soil; some concern individual sites but have along time series. At these individual sites, soil processes are often studied at the plot level and it is hoped that this understanding can be fed through to national databases to provide a national view of soil processes. In the UK, the recently concluded NERC Soil Biodiversity programme has generated much information of this kind.

There is poor integration with the water environment for many soil datasets. Integration of soils information between major data generators and holders is improving and should tackle this problem in due course. At present, the returns suggest that the strongest integration is occurring between National Soils Research Institute and CEH. CEH also make good use of soils data from Scotland obtained from the Macaulay Institute.

Internationally, there are a good number of national soil observation schemes. These often include condition monitoring that does not have an equivalent in the UK at present. At present, soil information is very strong in selected areas e.g. the National Soil Inventory. In general however, the data available for soils does not appear to be suitable for use in NRP assessments. Given the importance of soils, this is a data gap that may need to be filled.

Data from the National Soils Research Institute tends to be dominated by one-off surveys, some of which are unusual in that data has been gathered over a 40 year period. There are a large number of locations from which information has been gathered. Data quantity and quality is high and can or could be used for NRP assessment purposes.

Some attempts have been made to gain an overview of global soil resources. One website dealing with this issue is at http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html

4.1.5 DATA ON BIODIVERSITY AND ITS HABITATS

Biological Records Centre (BRC)

BRC hold over 15 M records on the biodiversity of the UK. They hold information on the distribution of species and on monitoring butterflies (The Butterfly Monitoring Scheme). The data is now readily accessible through the web site of the National Biodiversity Network. There is no international equivalent as yet.

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BRC records are particularly good for vascular plants and butterflies. There are records for about 4500 other organisms. BRC data have found wide application in government policy areas (e.g. the data have been influential in biodiversity action plans) and for assessing threats to vascular plants.

Key outputs from BRC databases are the Atlases of the distribution of plants and animals. These Atlases provide a comprehensive overview of species distributions that go some way towards providing an impression of the stock of biodiversity and its pattern of distribution. By integrating this information with other material and conducting appropriate statistical analysis assessments relevant to NRP issues are possible. A good example of threat analysis from the recent Atlas on the plants of Britain and Ireland is provided in the 2002 Defra publication for The Changing Flora of the UK.

Despite the strengths of the BRC system some weaknesses remain. For example, links between BRC and local records centres could be improved.

The Butterfly Monitoring scheme focuses on sites of good conservation status but given the ecological understanding of butterfly population biology the scheme is considered an important one for indicating trends in environmental quality, particularly perhaps in respect to environmental change e.g. climate change. The data in the scheme are in the form of an index of butterfly abundance. As a result considerable work would be needed to extract information relevant to the stock of butterflies or to assessing the condition of the resource or the threats to it. Trend data can be extracted from the Monitoring Scheme and data from the scheme has been integrated with distributional information to make statements about the state of Britain’s butterflies.

During the course of this study we did not refer to the National Biodiversity Network (NBN). This organization is a grouping of many different data holders and user groups that seesk to make biodiversity information more accessible from data collectors through data managers to data users. Through their web-site (developed jointly by staff from CEH and from the Joint Nature Conservation Committee) they make information readily available to partners and members. This organization could be a model for how NRP information could be managed and made accessible. The website can be found at http://www.searchnbn.org .

Biodiversity: Habitats and Ecosystems as managed by English Nature (EN)

EN has a wide range of statutory responsibilities and not surprisingly operates extensive databases of information about the nature conservation resources they are responsible for. Although data quantity is variable, data quality is generally high. There is particular emphasis on datasets addressing Biodiversity Action Plan targets and Convention on Biodiversity indicators. For a number of the designated sites, there are Public Service Agreement (PSA) targets. A particular feature of the databases in this area of activity is their dynamic nature, and this means field officers can update the central databases remotely so that the central teams have access to the latest information on site conditions.

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This suggests there is considerable scope to use EN databases to asses the stock of nature conservation resources and make assessments relevant to NRP issues. This digital system has replaced an earlier paper based system and has taken some years to develop to its current state.

Although the data is primarily for conservation databases, some of the material e.g. on priority habitats, contributes to our understanding on landscape services.

The data provides key inputs to national activities such as Natura2000 and the work of the European Environment Agency.

Biodiversity: River macroinvertebrate communities – RIVPACS

RIVPACS is a database that provides information on river invertebrate biodiversity. Samples are collected from many sites using a standardized methodology that can be easily learnt. Taxanomic analysis of the samples is a skilled task and can be time consuming. RIVPACS provides a good measure of river quality particularly in head waters streams. Although it is mush used for policy purposes it has yet to be tested with respect to NRP. RIVPACS is difficult to extract trend data from because of the manner in which samples are obtained – in general the RIVPACS dataset does not have sufficient temporal extent to allow it to show a temporal trend in the condition of freshwater macroinvertebrate communities. This should improve as the methodology is tied into the CS procedure. Integration is good with respect to water chemistry but poor on the more physical aspects of river and catchment.

Assessments of the condition of rivers using models derived from RIVPACS provide an indirect measure of biological status. The RIVPACS predictive model is used routinely by the EA, SEPA and NIEHS to assess the condition of river macroinvertebrate communities and hence river ecological status and in this case the model could test for statistically significant changes in the condition over time.

Biodiversity – Birds

The British Trust for Ornithology (BTO) holds UK information for birds on a similar basis to the data held by BRC. The two sets of databases have many shared characteristics. For example, volunteers play a key part in providing information on the basic resource. Apart perhaps for the Netherlands, and some parts of Scandinavia, neither organisation has any international peer. However, as with the BRC, there is increasing interest in Europe in adopting similar schemes. For example, there are about 30 other schemes in the world similar to the common bird census and breeding bird survey.

A key strength of the BTO data is that some records stretch back 50 years or more, and much of the data resource is sufficiently robust and of sufficient quality to detect trends over time. Furthermore, ecological knowledge plays an increasing part in the interpretation of the raw data; this means the data can be interpreted with sufficient scientific understanding to form the basis of environmental management actions. It is no

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surprise therefore that BTO databases are major contributors to a number of key government indicators. In some of these case the approach is to use an index of actual the bird numbers.

Several of the databases can be used to make an inventory of this resource and asses condition. Sometimes threats can be assessed. The concept of assessing sustainability of the resource appears to be an alien one.

One way in which BTO data has been utilised best is by engaging in a lot of integration, particularly with CEH systems e.g. the Land Cover Map.

4.1.6 SYSTEMS AND SCHEMES PROVIDING INFORMATION ABOUT THREATS TO NATURAL RESOURCES

Critical Loads

The Critical Loads system is part of the UNECE effort to control potential damage to the environment from the deposition of sulphur and nitrogen. In effect the system consists of a linked set of datasets that provides information not only on potential impacts on soils (the original focus of the critical loads approach) but also information on potential impacts of a range of habitats. The critical loads approach is now being applied to metals. Although the model calculates data for all the 1 km sq plots over GB and predicts outcomes over time, it does measure trend data itself. Some of the contributory datasets might be analysed for trends. A feature of the system is the high degree of data integration and data coordination that the critical loads approach to controlling atmospheric deposition has engendered. The system is stimulating a number of approaches to dealing with more localized forms of atmospheric deposition – the original aim was to work at a national level. The system may be a good example of how natural resource protection could be conducted in a national context since values of, for example, “exceedance” of the critical load can be provided across the country. Although part of a UNECE scheme, the system for calculating critical loads varies between signatories to the UNECE agreements so that it is difficult to compare the approach across the UNECE area.

Predatory Bird Monitoring Scheme

We did not obtain a proforma for this scheme as we were not certain about how other data sources would produce comments on assessing threats. As this topic is not well covered, a comment on The Predatory Bird Monitoring Scheme (PBMS) is needed as it appears assessments of threats may need some special measures.

The PBMS has run since the mid-1960s, continuously evolving to meet modern needs. Like many other schemes with “comprehensive” national coverage there is a reliance on volunteers as well as professionals to send in carcasses of a range of species covering the marine, freshwater and terrestrial environments. It monitors the eggs of selected species as well as carcasses. It has been developed to assess chemical threats to biodiversity and,

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by monitoring the top of the food chain, integrates chemical inputs from many sources. It has demonstrated the effectiveness of chemical regulation (including voluntary measures by private sector groups) as populations of birds recovered after certain chemicals were withdrawn from use. Data from the scheme, usually the levels of chemicals, needs integrating with other information (e.g on toxicological studies) to determine the degree of threat. It seems to be a common feature of threat assessments that integration of more than one type of data is required. Not all such integration occurs through formal models. Often the data is used in what is really a conceptual or semi-quantitative model.

In recent years the scheme has taken into account both spatial and physiological factors when assessing threat levels and trends in threats. The physiological work has had the effect of reducing the intra-annual variation in residue levels for certain chemicals and this should reduce the length of time it takes to detect a statistically significant change in a trend line. 4.1.7 BRIEF COMMENTARY ON THE SUMMARY TABLE

The summary table has been constructed to provide an overview of the type of information that can be extracted from the proformas returned by consultees. Originally, we asked consultees to score (numerical scale: 0 – 5) the datasets they were most familiar with for (a) a number of characteristics, and (b) for the use of the datasets for a range of NRP assessment purposes.

On examining returns it was clear that using the scores might provide a false sense of the accuracy of the exercise and so it was decided to use a “traffic light” system as tool for comparing, at a high level, the type of information that seemed to be available on the different types of natural resources. Moreover, the way respondents completed the form varied greatly. Some had clearly responded in a manner that provided only the essential information whilst others provided extensive commentary on the data. Some respondents clearly spent far more time completing the form than the minimum hour respondents were originally told they needed to spend completing the form. There has not been time to analyse all the information provided by the more detailed respondents, so all the retruned proformas have been made available to Defra in case further study is needed. The use of a traffic light tool is further justified by the probability that dataholders had not previously been asked such questions of their data. It might be quite misleading to over-analyse the returns in such circumstances.

In the table (at Annex 1) a green circle indicates the data are strong with respect to the inventory or assessment feature queries whilst a red circle indicates that the data, at present at least, might be unsuitable for use in either an inventory or an assessment. Amber circles indicate a borderline case. An open circle indicates that the respondent felt the issue was “not applicable” to the dataset concerned. Scores for individual components of the resource knowledge base were averaged to provide an overall assessment – albeit a rather simple one.

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We also asked about the ability to detect trends. This happened relatively late in the study when it became clear that some good quality datasets had limited time series. Not all consultees were able to respond, but in these cases trend data is supplied on a website. This is the case for the Countryside Survey (see: www.cs2000.org.uk ).

Perhaps surprisingly, some very clear tendencies emerged from the traffic light analysis and there was some reassuring consistency in the way data providers and data users viewed the same data source (even if they described it at different levels of detail). Thus, overall and at a high level it seems:

The ability to detect trends in datasets is less certain than might have been expected (few respondents could tick the trends box, many gave a response indicating unimodal trend information was difficult to provide as sown by a question mark or horizontal arrow. This does not mean datasets were incapable of detecting change from one sampling period to another. This is, perhaps, because the questions that were asked about trend information (changes in a variable in a particular direction over time) were asked of whole databases and data systems. The ability to detect trends in parts of databases and datasystems is probably much more possible. But there are relatively few databases or data systems which have long enough time series for trend data to be reliable extracted. Rather more datasets may be able to detect differences between one sampling period and another. This topic needs more detailed study. Perhaps the term trend was too specific – the PBMS can detect trends with a good degree of certainty but even here some trends have taken over a decade to become statistically significant. Some more work on detecting trends or change in natural resource variables may be needed, especially as some environmental variables exhibit natural cycles.

The type of natural resource databases and datasets least able to satisfy the needs of the NRP initiative, at present, appear to be soil ones (large number of red traffic lights).

The type of natural resource best able to meet NRP needs, at present, are probably those concerned with biodiversity and water; but even here there were gaps in those assessment areas that require, perhaps, the strongest science – policy linkages. An example can be found by examining the traffic lights for the sustainability assessment. This suggests a gap exists in the way science relates to sustainability issues. This gap needs to be plugged if the evidence base for sustainable development policies is to be strong enough. Not all biodiversity or water resource data systems are uniformly strong. Even the strongest systems have weaknesses – often as a result of limitations on data quantity (e.g. EN dormice data). The strongest biodiversity datasets seem to be those where there are PSA or similar targets to meet, or where the data systems are used for regulatory or policy purposes. Datasets gathered purely to advance knowledge are not always of use to policy or regulation – but they have an important role with respect to environmental management decisions where they are relevant (e.g CS).

Assessing stock was thought not to be applicable to air – where air quality (strictly perhaps, an ecosystem service) is the dominant concept. Perhaps a new approach is needed here. Perhaps the NRP interest in air should focus on chemical composition. This

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would of course include carbon and ozone levels. It is interesting to consider whether having an inventory for the air with a focus on atmospheric composition and dynamics would have altered approaches to climate change or ozone depletion.

As a test for using an inventory approach that involves building information on the chemical composition of natural resources we asked those involved in carbon in the global ecosystem to provide a proformas. The response suggests that such an approach might be productive (many green traffic lights).

4.1.8 DATASETS OR SYSTEMS NOT SCORED FOR NRP PURPOSES BUT LIKELY TO BE OF RELEVANCE TO THE NRP APPROACH.

Certain sources of information were not assessed for their use in the NRP inventory and assessment area as these have been seen as potential sources of data on either natural resources or more specifically ecosystem services. It appears that regulatory bodies or accounting bodies pay more attention to the delivery of services than they do directly to the natural resources themselves. This distinction seems to be true in many countries in the EU. The separation is, perhaps, less clear in the United States.

Some of these sources of information are organizations. Information on the work of these organizations are given below:

Environmental Research Funders Forum (ERFF)

The following text is taken directly from the report by Palmer and Kupiec (2004). We have included this to illustrate the differences between the current project and the ERFF initiative on environmental data.

The Environment Research Funders' Forum is a new focus group bringing together the UK's major public sector sponsors of environmental science.

The Forum will allow funders to identify and take strategic action on any gaps in environmental research and training. It will also shape future science direction through horizon scanning and other activities and add value to UK environmental interests internationally. To do this members will share their strategies, priorities and activities.

A working group to focus on long-term environmental datasets was convened in 2004, their objective was to compile a list of NERC data-sets (see Appendix 3). ERFF is just beginning a further stage of data compilation and assessment.

SPIRE

Another initiative worthy of note is the Defra SPIRE (Spatial Information Repository). This will provide users (Defra, its Executive Agencies and Non-Departmental Public

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Bodies) with the ability to query and retrieve spatial information. This spatial information may be considered as either contextual or business. The use of geographic information as a corporate resource will be encouraged and is intended to support the Department’s strategic sustainable development objectives for land, coastal and marine environments. The current data listing is provided in Appendix 2. There are four phases to SPIRE and each one will bring in further datasets. By March 2007 around 300 datasets will be available and this will grow further.

ODPM

ODPM also holds NRP relevant data on the urban and peri-urban environment and a wide range of planning related statistics. An example is the Generalised Land Use Database (ODPM 2005) which categorises land parcels into 9 key themes, including Domestic Buildings, Gardens, Non-domestic Buildings, Road, Rail, Path, Greenspace, Water and Other (mainly hardstanding). Links to these datasets will be provided after reconstruction of the current website (which starts on 31st October 2006).

NETCEN Air Quality

Data on air quality is expressed in similar formats internationally. This may be because the recognition of the links between air quality and human health has driven the establishment of international air quality measures backed by the UN world Health Organisation. In the UK the NETCEN website provides a source of data on this topic. There are similar sources of data in other countries. For example in the USA, the EPA provides very similar material. See http://www.netcen.co.uk/ for more information.

Environment Agency (EA) Datasets

Consultations with the Environment Agency indicated that they viewed ERFF as a way to access information on data holdings falling under the NERC banner. Environment Agency data held on their website indicate the degree to which this organisation focuses on the delivery of its regulatory services. Good examples of the information available on this aspect of EA activity can be found in the The State of the Environment report at:

http://www.environment-agency.gov.uk/yourenv/1088978/?lang=_e&theme=&region=&subject=&searchfor=STATE+OF+THE+ENVIRONMENT&any_all=&choose_order=&exactphrase=&withoutwords=&exclude_itemtype=Station%2C&include_itemtype=Acrobat%20Document%2CAttached%20File_e%2CAttached%20File_w%2CHTML%20Page%2C

Not all EA information sources relate directly to regulation and service delivery. For example, they hold large spatial datasets on water quality which extend beyond water supply or sewage issues. The EA have a notable monitoring and data centre centre, which also includes application of earth observation technologies to underpin policy and environmental management activities. An example of this wider data can be found for

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carbon at: http://www.environment-agency.gov.uk/commondata/103196/259469?version=1&lang=_e

In Scotland these responsibilities fall upon the Scottish Environmental Protection Agency (SEPA) that plays a very similar role to the EA. It too holds valuable natural resource data not directly related to service delivery.

Defra Datasets – Statistics

The Defra statistics group have produced a digest of relevant statistics for many years. This is a useful source of data on environmental protection and in recent years the data types and time series material has increased, making it possible to, very broadly, link policy and environmental change. NRP data might be presented publicly building on some of these established methods.

Treasury (PSA targets)

The Treasury, as part of the PSA initiative, are a source of a number of key pieces of NRP information. Although the source is a very indirect one the following web page provides an overview of the importance of these indicators of good environmental management: http://www.hm-treasury.gov.uk/performance/DEFRA.cfm

OFWAT

It was not possible to get a proforma response from the water sector handling supply issues as they felt that reports from OFWAT contained all the necessary information. OFWAT also make data available on important aspects of water supply etc. A recent report can be found at: http://www.ofwat.gov.uk/aptrix/ofwat/publish.nsf/Content/pn2705

And a relevant data website is:

http://www.ofwat.gov.uk/aptrix/ofwat/publish.nsf/AttachmentsByTitle/leakage_04-05_tables.pdf/$FILE/leakage_04-05_tables.pdf

4.1.9 INTERNATIONAL SOURCES OF NRP EQUIVALENT INFORMATION

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Attempts to obtain information on international datasets and databases that might be useful models for the NRP programme were disappointing. We did not find any central database paralleling an NRP inventory in any way that was being used for assessment purposes.

Despite this we know that some EU initiatives are developing which could play a role in NRP developments. This is because of the general recognition that early warning systems are needed if NRP is to succeed in preventing harm or damage – the current focus of many current approaches to environment protection. One problem that was encountered was that the international initiatives although seemingly comprehensive in their aims were actually working on much more narrow questions (e.g carbon in forests).

Four main international activities are relevant to NRP – all of them are too large to even summarise in this short project:

Global Monitoring for Environment and Security, GMES (EU FP6 programme and the European Space Agency): The home page is www.gmes.info . The focus is on earth observation techniques. Many NRP issues are covered.

International Long Term Ecological Research Network, LTER (many sponsors, began in the USA): the home page for the USA grouping is www.lternet.edu ; that of the international grouping is: www.ilter.edu . The European partners include the FP6 IP led by CEH known as ALTERNET that has a biodiversity focus. ALTERNET links to another FP6 IP, ALARM, which is providing a large scale perspective on a number of risks to natural resources (especially biodiversity). LTER-Europe’s home page is at www.lter-europe.ceh.ac.uk .

Global Terrestrial Observing System, GTOS (a UN sponsored group): The home page is www.fao.org/gtos/ . It aims to make people aware of information relevant to environmental change and to help in analysis and interpretation. As might be expected for the FAO it has regional groupings. A coastal initiative has been launched recently.

Global Ocean Observing System, GOOS (a UN sponsored group): This grouping, home page http://ioc.unesco.org/goos/ aims to provide information and improve management of marine resources. It too has a coastal initiative.

The EU runs a number of other programmes relevant to NRP, including the Natura2000 system for nature conservation and CORINE for landcover/land use.

Less relevant material was discovered at the level of individual countries. In many cases, the only NRP-like material was based in individual states of the USA or similar levels or organizations in other countries. Some relevant websites include:

CANADA: http://www2.ec.gc.ca/data_e.html

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USA: http://www.epa.gov/enviro/ Provides a starting point – although the website has many branches. The chemicals data is perhaps the best organized from a data perspective. Parallels with the UK system run through NETCEN are obvious. AUSTRALIA: http://www.deh.gov.au/erin/about.html GERMANY: http://www.bmu.de/english/doc/4209.php (for an explanation) and http://www.gein.de/servlets/TextSearch?lang=en (for a data and information portal)

AUSTRIA: http://artifex.lfrz.at:8007/duz/enduser/index.jsp?outlang=1 DENMARK: http://www.dmu.dk/International/Monitoring/

GREECE: No obvious database

NETHERLANDS: No obvious database. This was a very surprising finding. It may be relevant material is located in agencies and environment protection organisations.

FRANCE: http://www.ecologie.gouv.fr/sommaire.php3#

4.1.10 ADDITIONAL TOPICS RELEVANT TO NRP

It was not possible to investigate two NRP areas in any detail. This is because both areas (discussed in outline with staff of the Countryside Agency) are still being developed in various ways and there is no real agreement on what measures might be made to quantify this resource. For both areas we provide websites where information on these topics might be found.

Access to the Countryside

There are no readily agreed ways of measuring access to the countryside, despite there being a large number of different sources on information available about access provided by a wide range of organisations (sample websites listed below).

http://www.openaccess.gov.uk/S4/html/LWWCM/Section4/GeneralContent/MappingAccessLand.html

http://www.landscapecharacter.org.uk/search/list.php?res=CCA117

http://www.hants.gov.uk/bestvalueinhampshire/bvpidetail.php?catid=5&subcatid=4&recordid=25&bvpiid=112&bvpiid=128

http://www.hants.gov.uk/countryside/row/index.html

http://www.ramblers.org.uk/footpaths/work/herefordshire.html

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http://www.staruk.org.uk/

It is possible that a measure of potential access could be obtained by examining such matters as the network of footpaths or their density in the landscape or character area. It may also be important to consider such issues as the connectivity of footpaths to various aspects of or features in the landscape. Tools might be developed to combine information on footpaths and other routes with digital terrain maps so that the amount of landscape visible to a walker might be better estimated. If such integration were possible then visualisation tools might have a role to play in engaging stakeholders in deciding between landscape management options.

Tranquility

Methods of estimating some of the “softer” aspects of NRP include measures of such characteristics of areas as tranquility. As with a number of issues touched on in this report, some might regard tranquility as an indirect measure of some other natural resource factor or as some form of ecosystem service dependent on lack of noise or absence of mechanised transport routes. One attempt at a tranquility map can be found at:

http://www.cpre.org.uk/campaigns/landscape-and-beauty/tranquil-areas/previous-tranquil-areas-maps.htm

Such measures are often created by combining a series of measures, either as GIS layers by some indexing approach. Use of indices can be very powerful as policy tools.

INTEGRATED INDICES AS POLICY TOOLS.

Indices that use a combined approach combining some “hard” and some “soft” natural resource factors may be useful. One such combined effort has been made in relation to water resources. This is the Water Poverty Index (WPI), one of a small number of “integrated indices” of natural resources. Integrating scientific data from different sources is essential if policy tools are to be robust and meaningful. The use of indices provides a means by which both quantitative and qualitative data can be incorporated into a common framework to provide a holistic assessment. The potential of such an approach is demonstrated by WPI, which is a composite index designed to capture the links between water and welfare. This index incorporates several diverse variables in a common framework, and it can be applied at a variety of scales. It can be of use for local level management, and also as a tool for Integrated Water Resources Management (IWRM), an essential component of the EU Water Framework Directive.

The WPI has been designed as a tool to monitor progress in the water sector, particularly in developing countries. It is calculated using a simple formula and the results can be displayed graphically for dissemination purposes. How the source data can be incorporated is indicated in Box 1, and an example of national level application of this tool is shown in Box 2 which indicates that for an overall look at three European

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countries capacity and access are, in this particular case, the major determinants of relative water poverty rather than patterns of use or the overall size of the resource.

Box 1. Incorporating data into a composite index framework

Box 2. A comparison of national level WPI scores

International WPI values, selected countries, 2001 (WPImax=100)

Capacity

Environment

Use

Access

Resources

0

20

40

60

80

100

Spain (63.6)United Kingdom (71.5)Hungary (61.4)

The WPI framework can be applied at a basin scale or at the level of counties or even parishes. In the UK, this could provide a useful tool to help in water resource planning and protection.

More information on the WPI is to be found at Appendix 1.4. The approach has been developed further to provide a climate vulnerability index. These indexing approaches have not been applied in detail in the UK although they have sometimes been suggested.

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Nitrogen load/Km 2

Industrial use/Km 3 /Yr

Cropland in floodplain

Multiple variables provide input into final index scores, and GIS enables meaningful representation to stakeholders

WPI values in the Mekong Basin

N

ii

N

iii

w

XwW PI

1

1

BIOMEDICAL APPROACHES: AMMENDING THESE FOR ENVIRONMENTAL HEALTH

The analysis of complex multi-variate datasets is a common problem in biomedical sciences and indeed ecology. Many modern data processing and statistical procedures, particularly perhaps those applied in metabonomics have a considerable potential to help in NRP. This is because these approaches cope with a range of different data types, could position individual locations in a relative position to others in a multi-dimensional space and track changes over time, perhaps even providing an early warning of problems ahead.

4.2 Relevance of existing databases to managing change in natural resources

Studying trends over time and space, identifying the causes of trends and managing undesirable or unwanted change in resource stock or use patterns seems close to the top of the science agenda policy makers and environmental managers currently seek from the science community. This is not surprising. There is a widespread recognition that at least some natural resources are being used at rates that may deplete them unless careful management is undertaken. There are strong policy drivers on many issues linked to natural resources, such as those provided by the Millennium Development Goals and the Plan of Implementation of the World Summit on Sustainable Development.

From a more scientific perspective, the problems, scenarios and predictions identified by the Intergovernmental Panel on Climate Change and the Millennium Ecosystem Assessment are only adding to the need for a UK inventory of natural resources and methods of assessment that go beyond what is possible within the scope of environmental impact assessment alone.

Of particular value for NRP are environmental datasets which can provide both further understanding of environmental processes and provide inputs of value to discern larger scale drivers and impacts. The purposes of environmental data collection may be classified as (a) for research to identify processes, (b) for operational use to allow interventions to meet targets, and (c) for strategic use to support overall policy decisions. However, all classes of data collection can provide valuable support to purposes for which they were not originally intended. Detailed research data on processes is usually of limited geographical extent, but provides the basic information on which understanding and generic model development is based. Models may be applied to larger and more diverse areas, representing the processes but requiring some level of overall calibration and validation to data from larger operational and strategic sites.

Some examples of data collection linked to processes and large scale modeled ouputs is in hydrological work, where process data has been used to develop flood models that have been adopted into UK practice (e.g. the two Flood Estimation Handbook (FEH) models, and the Wallingford Procedure for storm sewer analysis, InfoWorks).

Operational water resource data are collected by the EA, SEPA, and DANI and are integrated into the National Water Archive (NWA) held at CEH. They have been used to

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calibrate the first FEH model (flood peak statistics) at about 700 sites throughout the UK. The model has thereby been developed to provide GIS coverage of flood risk for every river stretch in the UK, and has been used by The EA and SEPA to develop their public web-site maps of flood zones. However, these maps only cover current conditions. To address the impacts of (a) climate and land use change, and (b) flood protection works, the second FEH model (rainfall-runoff processes) must be used. This was calibrated for just the 200 NWA sites that also had good coverage of rainfall intensity data – generally the smaller of the NWA sites. Despite this comparative lack of data to fully validate the model, by integrating its use with the previously described GIS flood risk map, it is also possible to confidently apply the process model to every river stretch in the UK. This is indeed the basis of the Catchment Flood Management Plans being developed by EA/Defra. This example clearly shows how process models developed using research data have been turned into valuable tools for operational and strategic purposes by integrating their use with available large scale data resources.

The InfoWorks model is a similar example, but in this case the hydrological component was developed by CEH using research data from very small catchments, and the model is even more reliant on validation using operational data from larger catchments (data collected by the Sewerage Undertakers). InfoWorks is the standard model on which all the Asset Management and Pollution Management works are based.

These are two examples of how models and large scale data collection have been successfully integrated. There is much scope to extend these activities, eg. with regard to use of the Harmonised Monitoring network of river water quality stations could be used to apply research models of water quality at a national scale.

Spatial and Temporal extension of data series from process understanding.

The indication of trends in some categories of Natural Resources is limited by the length of time series datasets. The length of record has often been constrained by the availability of appropriate resources and technologies for measurement. In addition to the use of process-based data to extend models to larger spatial scales and to generate future predictions, it may be possible to extend back through history (ie. “back-casting”). A promising example of this approach is described by Fowler et al (2004) in relation to UK Nitrogen Deposition. Although measurements of the concentrations of nitrogen compounds in air and precipitation in the UK have been made since the mid 19th century, no networks operating to common protocols and having traceable analytical procedures were established until the 1950s. High quality data from the last twenty years, current knowledge of atmospheric deposition processes, in addition understanding of industrial and ecosystem changes were applied to indicate the reducing dominance of coal combustion sources and increasing significance of agricultural sources from 1900 to 2000. There are substantial areas of the UK where the inventory of soil N in the top 30cm has doubled during the century, but with the largest change throughout the latter half of the century, driven by the increasing contribution of reduced N, largely from agriculture. A more detailed examination of the long-term historical nitrogen deposition in the UK is

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likely to provide a valuable guide to the areas of further study, and to the locations where effects of the accumulated soil nitrogen are most likely to be found.

4.3 Identifying data gaps and priorities for Natural Resource Protection

One clear message from this rapid study is that there is, as yet, no consistent underlying philosophy or set of principles on which to base a choice of information to include in an inventory of natural resources and no common approach to assessing those resources. The first should exist and one possible approach is set out in this report in Fig 1 and Fig 2 which outline the flow of data towards policy and regulatory applications and how natural resources and ecosystem services might be related. The second is probably unnecessary as assessment methodologies need to be fit for purpose. “Best practice” in the assessment of natural resources probably needs to be developed and some commonality of approach to this may be useful. A systematic review of existing practices and approaches may help develop this as there are some EU FP6 IPs that address various forms of environmental assessment or integrated assessment, eg ALARM and SENSOR (Sustainability Impact Assessment Tools for Environmental, Social and Economic Effects of Multifunctional Land Use in European Regions).

Many of the available environmental datasets are focused upon particular sub-environments, such as terrestrial or marine. An outstanding example of a linked data requirement across environmental boundaries is associated with OSPARCOM. By international agreement important landward determinants of marine environmental quality are compiled eg.data is required on chemical inputs to the North Sea through rivers. Even in this case there are significant inconsistencies between measurement methodologies in different member states. It is however, a good example of international co-operation, which drives measurement and databases which are of value in integrating sub-environments and in protecting supra-national and open environmental systems. It is notable that in most cases in which it is necessary to link sub-environment the measurement is often most easily or effectively achieved as an output or input from within a particular sub-environment. In some cases, this compartmentalization reflect practical requirements or traditional scientific disciplines. However, measurements focused upon actual environmental interfaces are often technically and scientifically problematic. For example, actual fluxes of water, sediments or chemical constituents measured at the interface between an estuary and shelf sea are likely to have margins of error which exceed the residual flux landward or seaward. Similarly the measures of the nutrient input or sediments moving from catchment surfaces may be approximated by physical measurements in plot studies. However, actual delivery rates to rivers might vary from 0-100%. Therefore, the spatial and temporal discontinuities in movement, e.g. from soils to rivers requires reliance to be placed upon indirect measurements of similarities between chemical, radionuclide and physical properties of materials on catchment surfaces and in-river.

Another reasonably clear message is that despite the great interest in natural resource protection by both the scientific community and government departments and agencies, there is a gap between the data being gathered by the science community (often collected

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primarily to advance knowledge) and that needed by the policy and operational environment protection groups (which is perceived to be collected for mainly legislative purposes).

Compiling a comprehensive database on all aspects of natural resources is, very probably, impossible at present. It may also be unnecessary for central government to hold such a list as many organizations already hold relevant data in accessible forms. A limited number of key measures may suffice to form the basis of a natural resource inventory for use by central UK government. Ideally, these measures should reflect the performance of the most important environmental and ecological processes and the way these respond to patterns of use and both natural and human pressures (e.g. from chemicals or the impacts of climate change).

Amongst the resource assessment methods must be monitoring techniques that provide an early warning of adverse trends or loss of system resilience (especially, perhaps, with respect to the protection of the main ecosystem services that people depend on). Significant data resources collected for research purposes are available for parts of the UK, which are more intensive in temporal and spatial cover than has been required for regulatory purposes. Examples include the databases archives which have been built up from the NERC thematic programmes and long term experimental studies, eg. The Land Ocean Interaction Study (LOIS), Lowland Catchment research (LOCAR), Environmental Diagnostics (ED) and Urban Regeneration and the Environment (URGENT) Programmes. The full value of joint use of these databases with national regulatory archives for strategic development purposes is yet to be fully realised. This points to the need for better communications between researchers and potential users.

Special inventory measures or approaches to assessment may need to be developed that provide an overall view, or integrated assessment, of ecosystem performance. Defra, with partner country environment and agriculture departments in the UK’s devolved administrations, have recently published Charting Progress: An Integrated Assessment of the State of UK Seas that goes some way towards meeting such a need – although this publication makes clear the challenges that lie ahead if an inventory of terrestrial and freshwater natural resources are to be important parts of the NRP evidence base, along with appropriate assessments.

4.4 Principles that might underpin the NRP evidence base

During the course of the study it was found that there were distinct differences in the nature of datasets and databases depending on the historical source of the data and the use to which the data was put. These fundamental differences seemed to influence a number of aspects of the datasets including the time series and the way factors such as uncertainties were handled. Fig 1 is an attempt to capture how these different data have been handled and the new demands on that might be made as a result of the need to meet the sustainable development agenda. Fig 2 is an attempt to capture another emerging theme garnered from consideration of how different types of data are being used. This is built on a view that, increasingly, if early warnings of environmental change are to be

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obtained, it will be necessary to develop a holistic approach to managing natural resources that delivers ecosystem services in a sustainable manner.

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Figure 1. Flow of data towards policy and regulation.

As respondents inputs were received it became apparent that there were three different types of data source. This is indicated on the left of the Figure 1. We have shown these as separate lines because of the historical origins of the programmes of work that provide the data appear to affect the nature of the data and its use for policy and regulatory purposes. This is not to imply that there is no scientific basis to the economic or volunteer lines. As our analysis of respondents returns illustrates, the datasets with highest utility for NRP purposes are those where there has been interactions between policy and science. The reasons for this are provided by Figure 2.

The link from environmental processes to policy and regulation could be handled through empirical approached to environmental management before the advent of sustainable development. This is because empirical approaches were able to deal with the functions and service delivery change issues identified at the bottom right of the diagram. Now that NRP issues and related aspects of sustainable development are at the heart of government policy environmental management approaches must encompass the dynamic aspects of resource management indicated top right.

The implication of the NRP approach is that we need to develop monitoring systems that provide early warnings especially when resource use approached the environmental limits of the resource. These limits need to take account of the patterns and dynamics of the resource in a heterogeneous environment.

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POLICY & REGULATION

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SCIENCE KNOWLEDGE

e.g. chemical processes, population biology,

landscape and catchment science

DATA

HUMAN INTERESTe.g. Butterflies, Birds, Wildlife

ECONOMIC/SOCIAL NEED(e.g. effect of soil type on crop yield, flooding,

public health, chemical risks)

Heterogeneity

FunctionUncertainty

Sustainability

NEW DEMANDS ON DATA RESOURCES

Measures of stockDynamics of stock

Assessment of risk, condition, threat Monitor all the above

EXISTING DEMANDS ON DATA RESOURCES

Detect ChangeAttributed Causes

Identify driversPredict Consequences

Manage Outcomes

POLICY & REGULATION

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SCIENCE KNOWLEDGE

e.g. chemical processes, population biology,

landscape and catchment science

DATA

HUMAN INTERESTe.g. Butterflies, Birds, Wildlife

ECONOMIC/SOCIAL NEED(e.g. effect of soil type on crop yield, flooding,

public health, chemical risks)

Heterogeneity

FunctionUncertainty

Sustainability

NEW DEMANDS ON DATA RESOURCES

Measures of stockDynamics of stock

Assessment of risk, condition, threat Monitor all the above

EXISTING DEMANDS ON DATA RESOURCES

Detect ChangeAttributed Causes

Identify driversPredict Consequences

Manage Outcomes

Figure 2.

Figure 2. Relationship of natural resources to ecosystem services.

The global system, including its biodiversity and the habitats and ecosystems services that support those living organisms would exist and function in the absence of human beings. People depend upon this global system’s physical, biological and chemical integrity to survive because it provides shelter, food, and energy. Figure 2 illustrates the relationship between this global system and human society. The global system is here represented as a ‘super organism’ with dynamic processes operating with physical constraints and exhibiting self regulating characteristics that are in tune with environmental cues and supplies.

For the system to operate in a healthy fashion then the key areas o=from which diagnostic and prognostic indicators will be derived will be in the operating systems area. If these sub-systems are working normally then it is quite likely that sustainable ecosystem services will be delivered. It follows that this is the areas of the global system that should be monitored most closely along with the key chemical and physical parameters.

It therefore follows that the current NRP resources list needs to be amended to include the chemical and physical parameters of air, water, and soil that are not directly relevant to Ecosystem Services.

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ECONOMIC &

SOCIAL FUNCTIONS

GOODS &SERVICES

SOCIETALSYSTEMS

HABITAT

MODIFIYING & CONTROL

POINTS

OPERATING SYSTEMS

(with limitations)

Inputs

Feedbacks

GLOBAL SYSTEMS

InternalInfluences

External Influences

Waste

EC

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TEM

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RV

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Pur

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& D

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NATURAL RESOURCESBiodiversity

Water QualityWater Supply

SoilAir Quality

Marine EnvironmentLandscape

Recreation & AccessEcosystem services

ECONOMIC &

SOCIAL FUNCTIONS

GOODS &SERVICES

SOCIETALSYSTEMS

HABITAT

MODIFIYING & CONTROL

POINTS

OPERATING SYSTEMS

(with limitations)

Inputs

FeedbacksFeedbacks

GLOBAL SYSTEMS

InternalInfluences

InternalInfluences

External InfluencesExternal

Influences

WasteWaste

EC

OS

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NATURAL RESOURCESBiodiversity

Water QualityWater Supply

SoilAir Quality

Marine EnvironmentLandscape

Recreation & AccessEcosystem services

5. MENU FOR THE FUTURE

5.1 Specific key requirements for continuity in data collection and databasing in each of the proscribed categories.

This may only be an issue for soils. There are

5.2 Major Gaps in available data

There is a great deal of data available for each aspect of NRP. Even extending NRP coverage to minerals would not lead to data shortages. The major gaps almost all relate to data integration. These are covered in various parts of the report.

5.3 Recommendations for future data assessment

The recent assessment of the state of UK seas, Charting Progress published by Defra in 2005 provides an excellent template for terrestrial natural resource inventory and assessment reporting.

There is considerable future potential value in:

Greater use of Earth Observation approaches to providing data for resource assessment; upcoming developments include an ability to measure habitat quality and improve the ways biodiversity resources can be managed by integrating information on environmental structure with population models.

Better co-ordination of environmental observation systems at global, European, national and local levels (e.g. taking forward concepts developed in the EU FP6 ALTERNET Network of Excellence). This should include consideration of the data needs arising from the Millenium Ecosystem Assessment.

Ensuring harmonization between environmental databases held by the different UK nations and regions. Currently this is not a major issue. However, with the need for data to serve different purposes and varying priorities in the different nations which form parts of the UK, there is a potential risk that changes in data specification could make cross-UK datasets more difficult to compile. This is avoidable by full consideration of any compatability requirements, and recognition of necessary variations to meet differing national or regional needs at early stages of strategic design, data collection and during review phases.

More use multi-criteria approaches (such as the WPI) at range of scales – these might include environmental limits information.

Making potential links between databases operational and/or accessible: This assessment has pointed to a serious lack of “tags” to connect data collected for

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differing purposes or to deal fully with compatability issues between different data types. Although it is tempting to believe that layering of different types of datasets within increasingly flexible and accessible GIS systems can point to functional links between drivers and impacts, similarities in spatial patterns do not necessary provide evidence of causality. Creating improved continuity in interdisciplinary interpretations for both academic and operational purposes will be important in the near future because of the long learning curves (of one or two years) required for inter-disciplinary studies involving social, economic and environmental datasets.

Important issues which need to be resolved to ensure effective use of data for Natural Resource Protection include the following:

Each of the reviews of environmental data carried out over the last ten years which are relevant to Natural Resource Protection have been carried out for very different reasons. In these reviews, the level of objective assessment of data utility has been variable and usually absent.

No broad data review has tested the reliability of statements concerning the value and use of data collected. Despite the excellent work of Defra’s own statistical groups (e.g. on environmental indicators), this problem is persisting because no single organization has taken long term ownership or responsibility for a process of continued review of environmental datasets or been fully committed to the development of enduring long term agreed standards for assessment of a broad range of resource databases.

No index is in common usage to provide an objective index of data quantity and quality in comparison to data utility. Such an index might prove useful.

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BIBILOGRAPHY

Palmer, D & Kupiec, J (2004) Long Term Datasets Working Group. Report prepared by the Environment Agency for the Environmental Researchers Funders Forum

Calder, S. (2005) Spatial Information Programme: DRAFT REPORT 18 May 2023. Geographic Information Unit, Rural Development Service. Internal Defra Report SIP-DP-024

ODPM (2005) Generalised Land Use Database Statistics for England. February 2005. Prod. Ref. No. 04 PLUS 02944

Fowler, D., O’Donoghue, M. Muller, J. B. A., Smith, R.I. Dragosits U, Skiba, U., Sutton, M. A. & Brimblecombe, P (2004) A chronology of nitrogen deposition in the UK between 1900-2000.

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Appendices

1.1 COUNTRYSIDE SURVEY

Of all the databases and datasets examined Countryside Survey (CS) - together with the Land Cover Map in a number of cases - appears to provide one of the most structured sets of information from which estimates of stock and change in stock for a large number of variables relevant to NRP can be obtained. Moreover, values obtained from the Countryside Survey databases have estimates of error about the mean as well as mean values for the whole of GB (and certain regions). It is also possible to begin detect trends in certain variables and, with careful study, extract information on land use dynamics at the landscape scale. More detail can be obtained from www.cs2000.org.uk .

These scientific aspects of Countryside Survey are also align increasingly well to the policy needs of government Departments and Agencies and both the 1998 and the upcoming 2007 CS have been amended to report more readily on major policy issues. This flexibility in the application of CS arises from the fundamental design of the survey, which takes a statistically robust sample of the countryside representative of all the major land use classes of Great Britain. A sample of over 500 1km squares forms the core of CS and many variables for landscape components, vegetation and soil are measured and geographically referenced to a shared baseline. Efforts are in hand to improve the mechanistic aspects of data integration with a view to improving accessibility of data.

It is only during preparations for the CS2007 work that the value of CS to policy groups and specialist groups in Departments and Agencies has begun to be collated. The contribution of CS work to policies on hedgerows, soil “acidity”, nitrogen impacts on vegetation and broad habitat policies is now clear and, likewise, the contribution to indicators of sustainability and quality of life is also apparent. It seems CS data is central to a number of indicators being the sole source of information for two - S3, on plant diversity and S5 on landscape features associated largely with field boundaries. CS data also is used with respect to a number of other indicators linked to river quality (e.g. impacts of nutrient pollution), agro-environment schemes and Biodiversity Action Plans. Amongst the relevant indicators are: D13; H12 and 13; Q1; R1 and R4; S4, S6, and S11; and finally T9 that relates to the actions of individuals with respect to sets of resources relevant to NRP.

During the scoping studies for CS2007, it has also become apparent that CS resources are also used by specialist staff in Departments and Agencies to provide policy groups with broader information on countryside matters.

CS approach is now attracting the attention of the EU, where the CS approach is likely to be adopted as the way of tracking land use change by field survey, and the environmental research community who are planning to take advantage of the next CS to learn more about the distribution of biodiversity in the UK. It seems further integration between the

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Land Cover Map and other initiatives (such as the Defra-funded Countryside Quality Counts) will provide a set of linked databases that will be able to inform both NRP issues and countryside policy more generally. Such developments may well be timely with respect to the formation of Natural England.

1.2 NATIONAL SOIL INVENTORY

The National Soil Inventory was made to obtain an unbiased estimate of the distribution of the soils of England and Wales and of the chemistry of the topsoil (0–15 cm depth) Samples were collected and soil profiles described at the intersections of an orthogonal 5 km grid over the whole area. This yielded about 6,000 sites, of which 5,662 could be sampled for soil.

Sufficient subsets of the sites were resampled at intervals from 12 to 25 years after the original sampling to be able to detect changes in carbon content with 95% confidence. This was done in three phases: in 1994–95 for arable and rotational grassland sites (853 of the original 2,578 sites), in 1995–96 for managed permanent grassland sites (771 of the original 1,579), and in 2003 for non-agricultural sites (bogs, scrub, rough grazing, woodland, and so on; 555 of the original 1,505). Roughly 40% of the original sites were resampled.

This is the only soil inventory on such a scale anywhere in the world to have been resampled. To allow for the varying time interval between samplings, annual rates of change in carbon were calculated for each site by assuming that the process of change was linear over the sampling interval (Bellamy et al. 2005). An analysis of known rates of change in soil carbon under different conditions showed this to be reasonable.

The strengths of the NSI are:• Well documented protocols for field and laboratory sampling. These are essential in order to maintain continuity and comparability between the sampling dates.• Baseline data from field observations on site and profile parameters, for example slope and land use and texture, horizon thickness, depth to water table and impermeable layer. • Baseline laboratory data – particle size distribution• Wide range of nutrient and heavy metal analyses.• The ability to produce robust statistics for different levels of aggregation, for example England and Wales (together and separately) and English regions.

These strengths will be enhanced by a further re-sampling of the sites within the next few years to give national and regional trends of soil health across the whole range of land use.

The data have been used in a number of Defra and Environment Agency funded projects as well as being supplied to a range of clients for use in their projects. Many of the NSRI-led projects have capitalised on the value of going back to the same point in the landscape on a regular basis and using the same protocols. These have included:

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• Derivation of headline indicators for topsoil parameters, for example organic carbon and phosphorus by Defra.• Derivation of heavy metal indicator in soils by the Environment Agency.• Monitoring of erosion in upland England and Wales.• Monitoring of changes in organic carbon and pH across England and Wales.• The NSI represents one of the key inputs into the SEISMIC (Spatial Environmental Information System for Modelling the Impact of Chemicals) database commissioned and used by Defra, UK Pesticides Safety Directorate and the Agrochemical Industry• NSI topsoil data has been used to set the standards in the DEFRA Sludge to Land report.

Bellamy, P., Loveland, PJ, Bradley, RI, Lark, RM & Kirk, GJD. (2005) Carbon losses from all soils across England and Wales. Nature 437 245-248.

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1.3 Use of Breeding Bird Survey data in policies related to the protection and enhancement of biodiversity (in UK)

Description of dataset

The BTO/JNCC/RSPB Breeding Bird Survey (BBS) is currently the main source of information on the abundance of terrestrial birds across the UK, including each of its constituent countries. Organised by the BTO, with additional support from the RSPB and JNCC, the BBS, first introduced in 1994, uses a line transect method for recording birds. Because only three site visits per season are required, and also due to active promotion as a national monitoring scheme, good coverage of the UK was quickly achieved. By 2004, the number of squares being surveyed exceeded 2500.

BBS survey squares are selected from a list of all 1k squares in the National Grid that comprise the UK, excluding coastal squares with less than 50% land. Use of volunteers is maximized through a stratified random sampling design. Within each of the BTO’s regions, squares are selected randomly, and allocated to volunteers through a network of voluntary regional organisers. Regional differences in coverage are corrected for, in the analyses, by weighting by region. Organisers receive a list of target squares for their region, to allocate in the order generated. Squares are identified by Ordnance Survey grid references that that enable their positions to be located on a map. The same squares are surveyed year after year and new volunteers are found if the original volunteer drops out.

BBS fieldwork involves three visits to each survey square per year. The routes of the transects are planned and details of the habitat recorded during the initial visit. The survey route comprises two parallel lines, each 1 km in length and ideally 500m apart and 250m from the edge of the square. Transects are divided into ten sections, making a total of ten 200m sections. For practical reasons there is often substantial deviation from the ideal route, but this has been found to have little effect on the habitat types encountered. Habitat information is recorded using codes from an established hierarchical system common to a range of BTO schemes (Crick 1992). Observers record the primary and secondary habitat for each transect section in up to four levels of detail. Bird counts are carried out on the second and third visits. Visits are timed so that the first is in the early part of the breeding season (April to mid-May) and the second at least four weeks later (from mid-May to the end of June). Volunteers begin their counts so that they coincide with maximum bird activity but avoid concentrated song activity at dawn. Volunteers, who are expected to be able to identify birds by song and calls as well as by sight, record all the birds they see or hear as they

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walk methodically along their transect routes. Birds are noted in four distance categories, three measured at right angles to the transect line (within 25m, between 25-100m, or over 100m), as well as all flying birds. The recording birds in distance bands gives a measure of bird detectability and allows relative population density to be estimated (Bibby et al.1992, Buckland et al. 1993). The average visit time is around 90 minutes. Observers record the start and finish times, and weather conditions using three-level weather codes to describe cloud cover, rain, wind and visibility. Bird counts in heavy rain, poor visibility, or strong winds are discouraged.

Outputs

Hence, the BBS provides annually, a set of counts for the entire avifauna (more than 200 species across the UK) recorded on each sample site. These are not complete counts for the 1-km square, but distance analyses using the counts in distance bands allows the estimation of absolute densities for species for which there are sufficient data. In current work, the BTO is developing these methods to incorporate landscape variables in the estimation of densities and using spatial modelling techniques to estimate bird abundance in un-surveyed squares. These are potentially valuable tools in estimating overall species richness, species distributions and avian biomass as well as abundance.

The BBS has achieved its primary aim in providing information on population trends for a wide range of species across the UK, in its constituent countries, and on a regional basis. For population trend analyses, the measure used is the total number of adult birds of each species detected in the square, summed over all distance categories and transect sections. The current BBS model uses the maximum of the two counts (early and late) as the annual measure of abundance, as a means of simultaneously reflecting the abundance of residents and early migrants, which tend to be most abundant in the first visit, and late migrants, which tend to be most abundant in the second visit. Annual population indices are calculated using a log-linear regression model with Poisson error terms. Counts are modelled as a function of square and year effects, with interpolated estimates for site-year combinations with missing data. The maximum likelihood method is used to fit the model. Because counts of animals often violate the assumption of a Poisson distribution, the model corrects for over-dispersion. To deal with missing counts (years) in a series, the model is estimated using the observed counts, and then used to predict the missing counts, and calculate the indices from a full data set including observed and predicted counts. Because the stratified sampling design results in unequal representation of regions across the UK, annual counts are weighted by the inverse of the proportion of the area of each region that is surveyed that year.

The BBS has taken over from the CBC the role of supplying information on changes in UK terrestrial breeding bird populations, and these data are used for a variety of conservation purposes, including population alerts, red-listing, BAP assignments and wild bird indicators. For ca 100 species, the population trends are updated annually in a series of reports to the statutory agencies and on websites. BSB data are also used in

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periodic assessments of the conservation status of birds in the UK, in the constituent countries, and in Regional Government Office regions.

Another important feature of the BBS is that the data can be integrated with data from other national schemes that record productivity (e.g. Nest Record Scheme) or survivorship (Ringing or Constant Effort Sites) to determine the demographic factor associated with the changes in numbers. This information can be used to assess whether ecological requirements during the breeding season (nest sites, nestling diet) or during the winter (food resources) are likely to be limiting. This informs research and land management to reverse the trends.

One of the great advantages of the BBS is that it is possible to ascribe bird counts to particular habitats, and hence produce habitat-specific population trends. These have the potential to be better measures of conditions in different landscapes – reflecting different drivers (agricultural policies / forestry practices, etc). Moreover, because BBS data are spatially referenced, and potentially to the finer resolution of the 200m x 200m transect section level (within the 1-km square), they can be used in many spatial modelling applications to determine the distributions of birds in relation to other characteristics such as habitat type or land use. BBS data were recently used in the Farmland Bird Database project to map the distributions of the restricted-range species in order to direct Environmental Stewardship (HLS) scheme applications to sites where they are likely to have the most impact.

BBS data are now the contributors to a suite of national and country wild bird indicators, fully integrated with CBC data to capture the historical context. In indicators, birds are used as a proxy for wider biodiversity, because changes in their abundance is measurable, and there is a large body of research that relates these to changes in the environment. In 1999, the Farmland Bird Index, based on the trends in 19 characteristic farmland species, was adopted by the government as a Public Service Agreement target, with a promise to reverse declines in farmland birds by 2020. The government’s main mechanism for achieving this is the new Environmental Stewardship scheme launched in 2005 with a broad aim to enhance biodiversity on agricultural land. The scheme will include options such as set-aside and organic farming, but also a variety of new options aimed at improving biodiversity in agricultural landscapes. Importantly, the success of the broad-scale implementation of these options across the UK will be measured by changes in breeding bird populations on BBS squares. Outside of farmland, there have been other developments. The Forestry Commission includes the woodland bird indicator as one of its key ‘UK Indicators of Sustainable Forestry’ and is interested in the development of indicators to measures changes in different types of forests, such as managed or natural. In Scotland, BBS data are being used to develop an indicator for the uplands, and the England Biodiversity Strategy also includes bird indicators for towns and gardens, and for wetlands. BBS data are also used on a European scale to contribute to supranational composite bird indicators of forests and farmland. In 2004, the European Farmland Bird Indicator was accepted to the Long-list of EU Structural Indicators, and as a EU Sustainable Development Indicator. This is clear recognition of the value of birds as indicators of the quality of the environment, and of the extent and quality of bird survey

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programmes operating across much of Europe. These headline indicators will be used to assess progress towards European (and global) targets to halt biodiversity loss by 2010.

Bibby, C.J., Burgess, N.D. and Hill, D.A. 1992. Bird Census Techniques. Academic Press, London, U.K.

Braak, C.J.F. ter, A.J. van Strien, R. Meijer and T.J. Verstrael. 1994. Analysis of monitoring data with many missing values: which method? In: Proceedings Bird Numbers 1992.

Buckland, S.T., Anderson, D.R., Burnham, K.P. and Laake, J.L. 1993. Distance Sampling: Estimating Abundance of Biological Populations. Chapman & Hall, London, U.K.

Crick, H.Q.P. 1992. A bird-habitat coding system for use in Britain and Ireland incorporating aspects of land management and human activity. Bird Study 39: 1-12.

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1.4 Using integrated indices for more effective natural resource management

To be operationally sustainable, any system of environmental management needs to be based on a truly holistic assessment of all of the relevant factors influencing it. This demands detailed and reliable data from both the physical and social sciences, and the development of less deterministic models which can capture the uncertainties associated with political will and unpredictable market forces. CEH has developed significant capacity in the generation of such holistic tools, one example being the Water Poverty Index (WPI), which extends conventional water resource assessment by explicitly incorporating socioeconomic and ecological issues into the decision making process. This has received wide attention from the international research community, and is being seen as a practical tool to evaluate the complexities which underlie situations of water stress. The work to develop the WPI was first funded by DFID, and while it has been designed for use in developing countries and can be used to monitor progress towards the Millennium Development Goals, it also can be applied elsewhere.

The WPI is based on integrating information from several parameters which are selected to capture the essence of the water management problem. These are incorporated into a framework based on five key components relating to water: Resources – how much (ground and surface) water is there available, taking account

of seasonal and inter-annual variability and water quality; Access – A measure of how well provisioned the population currently is, including

for domestic use and irrigation; Capacity – institutional and community capacity to manage water resources; Use – how water is used for productive purposes and its contribution to the wider

economy; Environment – ensuring long term ecological integrity by incorporating the

environmental impact of water management activities.

These different components of the WPI are combined within a composite index structure as outlined in Box 1. Box 1. Combining variables in the WPI

The WPI is derived from the weighted average of the five components Resource (R), Access (A), Capacity (C), Use (U), and Environment (E).:

eucar

eucar

wwwwwEwUwCwAwRwWPI

where WPI is the Water Poverty Index value for a particular location, and w is the weight applied to each of the components. Each of the five main components is made up of a number of sub-components, and a weighting can be applied to indicate the importance of each variable. Components are standardised to fall in the range 0 to 100; giving a final WPI value between 0 and 100. The highest value, 100, is taken to be the best situation, that is, the lowest possible level of water poverty, while 0 is the worst. To avoid problems of subjectivity, a baseline value of the WPI should be first calculated with these weightings set equally.

Source: Sullivan et al, 2002While the framework of the WPI is fixed, the selection of variables can be made on the basis of locally relevant priorities, although of course if different variables are used in different places, comparisons between those places cannot be made. Our work has show that by making use of a standardised selection of variables, comparisons can be made

49

between places for the purposes of aiding the resource management process. This is illustrated in Table 1, and the ways in which this information can be presented to policy makers is shown in Figure 1.

Table 1. Community level WPI scores in Tanzania and South Africa

Community Component values WPIResources Access Capacity Use EnvironmentSouth AfricaWembezi (inf) Urban 50.0 48.8 46.1 18.0 39.1 40.4Wembezi (form) Urban 50.0 86.5 78.0 38.1 63.2

Ethembeni Rural 50.0 36.6 59.8 41.5 27.7 43.1KwaLatha Rural 20.0 17.0 42.1 24.5 28.9 26.5TanzaniaMajengo Urban 10.0 32.7 62.9 15.0 98.4 43.8Kijenge Urban 20.0 53.9 68.3 21.6 41.0Nkoaranga Rural 30.0 39.5 59.4 65.3 69.9 52.8Samaria Rural 20.0 20.9 44.7 37.7 56.1 35.9

Source: Sullivan et al.,2002

Figure 1. Presenting complex information to policy makers: pentagrams used to illustrate community level WPI component scores

ACCESS

RES-OURCES

ENVIRON-MENT

USE CAPACITY

0

20

40

60

80

100

Wembezi (inform.) Wembezi (formal) Ethembeni KwaLatha

WPI scores in South Africa WPI scores in Tanzania

CAPACITY

RES-OURCES

USE

ENVIRON-MENT ACCESS

0

20

40

60

80

100

Awarakotuwa Tharawaththa Agarauda Tissawa

The use of the pentagram diagram enables the full details of the WPI scores to be displayed, thus reducing misinterpretation of the single WPI score. This also reveals the strengths and weaknesses of each location.

To be useful, indices such as this should be developed using existing data where possible. An example of how this can be done is shown in Figure 2, which demonstrates how a composite index can be calculated from existing census and water resources information. This figure also shows the importance of scale in applying indices for decision making.

50

Figure 2 .WPI values generated using census data for the Escourt District, KwaZulu Natal, South Africa

This shows how data collected at a larger scale do not represent the situation as accurately as those collected at a finer resolution (Enumerator scale refers to data collected from the enumerator districts used in national census data collection).

National level application of the WPI.The WPI scores can also be calculated at the national level. While this can be of use to donor agencies and international organisations, it is less useful for internal policy making. Figure 3 shows the national level WPI scores for a number of countries including the UK.

International WPI values, selected countries, 2001 (WPImax=100)

Capacity

Access

Environment

Use

Resources

0

20

40

60

80

100

Uganda (44.03)Tanzania (48.34)Pakistan (57.8)Dominican Rep.(59.3)United Kingdom (71.5)

In the examples shown here, all of the countries have the same level of water resource availability based on the method used to determine the resource component of the WPI.

51

#

SubcatchmentScale

Enumerator Area Scale

#

SubcatchmentScale

Enumerator Area Scale

The 15% most water poor households

In spite of this however, it is clear that there is much variation in how the countries are performing generally in terms of managing these water resources effectively. This highlights the benefits for policy making of this approach, compared to conventional hydrological modeling. Clearly, assessments made at the national level cannot be representative of the variation that is found within a country. This can be addressed by applying the tool at the sub-national scale, for example at the provincial level. This is illustrated in Figure 4, which shows the variations in WPI scores across the country of Benin. Figure 4. Variation of WPI scores across the West African nation of Benin

Regional WPI Benin

22

23 - 33

34 - 39

40 - 43

44 - 46

47 - 50

51 - 55

56 - 63

1.5 Overview of UK Marine Data Sets

The UK Marine Environmental Data Network is a partnership between a number of Government Departments and Agencies and user groups with an interest in data relating to the marine environment. It has been set up under the auspices of the UK Inter-Agency Committee on Marine Science and Technology (IACMST). It is currently co-funded by the Natural Environment Research Council (NERC), the Department for Environment, Food and Rural Affairs (Defra), the Environment Agency, the Fisheries Research Services of the Scottish Executive Environment and Rural Affairs Department (FRS/SEERAD), the Met Office and the UK Hydrographic Office. In addition, other organisations are also represented on MEDAG (e.g. UKOOA, UK Marine Information

52

This figure shows the variability found across a country, while the figure below shows the national level values where the final WPI value for the whole country is 39.9

National WPI value, Benin , 2001 (WPImax=100)

Environment

Use Capacity

Access

Resources

0

20

40

60

80

100

Benin (WPI=39.2)

Clearly, sub-national values are much more meaningful and useful for policy makers. A pentagram such as the one above could be generated for each of these provincial values, enabling specific decisions to be made on water management issues for each individual district.

Council, Nature Conservation bodies (JNCC, CCW), Natural History Museum, the Crown Estate and NGO groupings (via Marine Conservation Society)).

The project operates in the form of a distributed network between the marine data managers and the focus is provided by a Marine Environmental Data Co-ordinator and an Action Group. Its primary aim is the improvement of accessibility to, and availability of, marine data for both scientific research and wealth creation. To meet this aim several catalogues and directories of marine data have been developed: these are described below. To promote these activities, the OceanNET web site (www.oceannet.org) has been set up to act as a portal to data and information about the marine environment.

The UK Directory of Marine Environmental Data Sets is a "discovery" metadata directory which includes descriptions of approximately 700 data sets collected by 130 UK laboratories. Data sets relate to physical, chemical and biological oceanography, marine meteorology, ecology, geology and geophysics, underwater acoustics, and - to a lesser extent - major marine pollution data sets. The database can be search on-line. The two figures below show the range of data set descriptions by data theme and sea area.

Data sets are catalogued irrespective of their format (e.g. digital files, analogue records, manuscript data, microfilm, geological and biological samples, etc.) and include data collected from the last century through to the present. The primary geographic area covered comprises the seas and oceans adjacent to Europe (e.g. North Atlantic, Mediterranean, Baltic, North Sea, northern sub-polar and polar seas), although wider ranging data sets are included, particularly global data sets.

3

3

15

16

8

13

54

97

64

50

176

119

314

106

74

0 50 100 150 200 250 300 350

Catalogues

Atlases/maps

Computer models

Remote sensing (satellites or aircraft)

Hydrographic surveys (navigation/engineering)

Underwater photography

Seafloor samples (eg core, dredge, grab)

Geology/geophysics/sedimentation

Fisheries

Environmental quality/impact

Marine biology

Ocean composition

Physical oceanography

Meteorology

Coastal studies

Distribution of data sets in the UK MED Directory according to the type of data (Note that a data set may cover more than one data theme).

53

925 18 9

230

103

191

99

164

56

11 13

154

9 13 16 745 58

0

50

100

150

200

250

300

Arct

ic O

cean

Gre

enla

nd S

ea

Nor

weg

ian

Sea

Bare

nts

Sea

Nor

th S

ea

Inne

rs S

eas

W o

f Sco

tland

Irish

Sea

Bris

tol C

hann

el

Engl

ish

Cha

nnel

Cel

tic S

ea

Bay

of B

isca

y

Med

iterr

anea

n Se

a

Nor

th A

tlant

ic

Sout

h A

tlant

ic

Arab

ian

Sea

Indi

an O

cean

Paci

fic O

cean

Sout

hern

Oce

ans

Wor

ldw

ide

Geographical coverage (by IHB Sea Area) of data sets currently included in the directory (Note that a data set may cover more than one sea area).

The UK Directory of Marine Environmental Data Sets is the UK contribution to the European Directory of Marine Environmental Data (EDMED), a collaborative EU project involving fourteen European countries. EDMED is a component of the SeaSearch network, which acts as a focal point for marine data and information in Europe (www.sea-search.net).

The UK Cruise Inventory contains information about research cruises carried out by UK scientists. In total the database now contains details of about 6200 cruises from the 1960s to the present day. Following a research cruise, completed Cruise Summary Reports are added to the database. In addition, in the past, paper cruise track charts usually accompanied the Cruise Summary Report. These have been electronically scanned and are stored alongside the information in the database. Now cruise reports and track charts are supplied electronically and linked to the database.

Cruise information included in the database covers ship name, organisation name, sea areas visited, cruise objectives and a brief description of all measurements made. The database can be searched on-line, by selection from menus, a map of sea areas or by a free-text search. The cruise track image and cruise reports can also be viewed.

The two figures below show details of the number of cruises added to the database over the last five years.

54

Cruise information received for cruises undertaken betw een 2000 and 2004

25 23 2548 42

48 62 6050 42

1519 21

231514

17 8

46

13

0

40

80

120

160

200

2000 2001 2002 2003 2004

CEFAS FRS NERC Others

Cruise information and Cruise Summary Reports received

102121 114

167

112

58 63 65 6239

0

40

80

120

160

200

2000 2001 2002 2003 2004Cruise Info CSR

The UK Inventory of Moored Current Meter Data contains information about 9500 current meter data series collected by 80 organisations, primarily from the continental shelf seas around the British Isles (e.g. North Sea, Irish Sea, Celtic Sea) or the eastern North Atlantic. Current meter deployments are typically 2-8 weeks duration in shelf areas but up to 6-12 months in the open ocean. The data are described in terms of position, instrument type, start date and duration of data, parameters measured, originating laboratory and data held/not held flag. In addition to searching on these keys, a map based search facility will soon be available.

55

In parallel with this, an International Inventory of Moored Current Meter Data is also available, which includes similar information from approximately 20 countries and comprises, together with the UK component, over 30000 entries.

The UK Inventory of Marine Monitoring Measurements forms the UK contribution to the European Directory of the Initial Observing System (EDIOS), an internet-based searchable directory of the ocean-observing, measuring, and monitoring systems operating in Europe and is an initiative of EuroGOOS. The directory includes information on location, measured parameters, frequency, data availability, technical information on instruments, responsible institutes and links to data-holding agencies. The EU project finished at the end of September 2004 and the first version of the EDIOS database is now available from the EDIOS web-site (www.edios.org).

The table below shows the observing networks and programmes either already included or to be included in the UK component of the Inventory. This will provide over 550 individual series from 30 different observing programmes.

UK Observing Networks and ProgrammesCEFAS Coastal Temperature Network HumberNetCEFAS Marine Environmental Real Time Observing System (MEROS)

International Bottom Trawl Survey - UK FRS Monitoring

Channel Coastal Observatory Meteorological and Wave monitoring network (METNET)

Continuous Plankton Recorder Survey Met Office Marine Automatic Weather Stations (MAWS)

Cypris Station (Irish Sea) – Port Erin Marine Laboratory

NERC/POL ACCLAIM tide gauge network

DARDNI Coastal Monitoring NERC/POL Liverpool Bay Coastal Observatory

DARDNI Northern Irish Sea trawl stations Port Erin Breakwater (Irish Sea) – Port Erin Marine Laboratory

DARDNI NW Irish Sea Nephrops Rothera (Antarctica) monitoring station – BAS

EA Anglian Region Strategic Coastal Monitoring

SAMS Tiree Passage Current Meter Time Series

Ellett Line (Rockall Section) SAMS Anton Dohrn Seamount CTD SectionFerrybox – SOC SOC Drake Passage CTD sectionFRS coastal monitoring stations. UK National Marine Monitoring ProgrammeFRS Fair Isle Munken (FIM) monitoring programme.

UK National Tide Gauge Network

FRS JONSIS stations WaveNet CEFAS DEFRA strategic wave monitoring network

FRS Nolso - Flugga (NOL) stations. Western Irish Sea Moored Instruments DARDNI

FRS slope transport current monitoring

56

Catalogues relevant to the UK inventory of marine monitoring measurements are being developed by the Marine Environmental Change Network and the UK Marine Information Council (UKMIC). Liaison has been established between the UK Marine Environmental Data Network and the MECN, which is coordinated by the Marine Biological Association of the UK (MBA) and funded by Defra. The MECN is a collaboration between organisations in England, Scotland, Wales and Northern Ireland collecting long-term time series information for UK marine waters. The goal of the network is to use long-term marine environmental data from around the British Isles and Ireland to separate natural fluctuations from global, regional and local anthropogenic (human) impacts. Further information can be found at: www.mba.ac.uk/mecn.

The UK Marine Information Council has developed a web based inventory of information on metocean networks operating around the British Isles. This service provides the most comprehensive view today on the function of these networks in terms of what parameters are measured, the location of instruments and the owners and operators of the networks. Links are also provided to contact organisations for the supply of the data. The web site, developed by HR Wallingford, can be reached through the UK MIC web site at www.ukmarine.org.

The Integrated Coastal Hydrography (ICH) project was an Invest-to-Save project, providing 75% of funds for the first two years and bringing together the UK Hyrographic Office, the Environment Agency, Ordnance Survey and the Maritime and Coastguard Agency (MCA). The Steering Group was chaired by the MEDAG Chairman. The ICH project aimed to identify and validate data capture methodologies for bathymetric data in the inter-tidal and shallow water areas, including laser bathymetry, which can penetrate 70m in clear water. In addition, the MCA are testing out multi-beam technology.

A web-enabled database of survey metadata to identify existing sources of coastal hydrography and holding information including location, age, purpose, ownership and specification used for gathering and processing bathymetric data, has been set up. The web-site will not serve the actual data – the user will need to contact the data owner for that - but it will provide sufficient information to let them gauge the value of the survey data and obtain them if required. Further details from the project web-site at: www.coastalhydrography.com.

57

Appendix 2: SPIRE Datasets

1:10 000 Scale Black and White Raster1:25 000 Scale Colour Raster1:250 000 Scale Colour Raster1:50 000 Scale Colour Raster1:50 000 Scale GazetteerBoundary-Line™ (including Wards, Parishes, Districts, Counties, Unitary Authorities etc)Including Parliamentary ConstituenciesCoastal BoundaryRivers - OS Meridian

Areas of Outstanding Natural BeautyHeritage CoastsNational Parks (including proposed boundaries)National TrailsOpen Access Land (CRoW)Flood Defence Committees - Regional and LocalInternal Drainage DistrictsNUTS, including:NUTS 1 (Government Regions);NUTS 2 (Combined Counties)Conservation Walks and Rides RegisterCountryside Stewardship Agreement HoldingsNitrate Sensitive Areas (all agreements finished)Organic Farming Scheme Agreements Organic Farming Scheme Management ParcelsEnvironmentally Sensitive AreasLess Favoured AreaMoorland LineNitrate Vulnerable ZonesDesignated Main River Network

58

Common LandFlood Risk – River (floodplains)Flood Risk – Tidal (floodplains)Catchment Pollution RiskHistoric Parks and GardensRegistered BattlefieldsScheduled Ancient MonumentsWorld Heritage SitesNational Monuments Record (NMR)Joint Character AreasNatural AreasSSSI Condition AssessmentNational Nature ReservesNatura 2000, including:SACSPA RAMSARSites of Special Scientific InterestAncient WoodlandEnglish Nature Management AgreementsLowland Grassland Inventory**Heathland Inventory**Community ForestsWoodland Grant Schemes Countryside Stewardship Managed ParcelsEnvironmentally Sensitive Area Agreements Environmentally Sensitive Area TiersProject-based Scheme LocationsTraditional County BoundariesPublic Rights of WayNational Forest1991 Urban Areas (Census)Overgrazing Assessments (HLCA)Local Wildlife SitesIACS information (historical set of points only)Marsh FritillaryPearl Bordered FritillaryCirl BuntingObjective 1Defra Regions (Government Office

59

Regions) Objective 2Moorland and Non-moorland BAP Habitats including:i) Blanket Bog;ii) Coastal and floodplain grazing marsh;iii) Coastal vegetated shingleiv) Fens v) Lowland beech and yew woodland vi) Lowland calcareous grasslandvii) Lowland dry acidic grassland viii) Lowland heathlandix) Lowland meadowsx) Lowland mixed deciduous woodlandxi) Lowland raised bogxii) Maritime cliff and slopexiii) Mudflatsxiv) Purple moor grass and rush pasturexv) Reedbedsxvi) Saline lagoonsxvii) Undetermined grasslandxviii) Undetermined woodlandxix) Upland calcareous grasslandxx) Upland hay meadowxxi) Upland heathlandxxii) Upland mixed ashwoodsxxiii) Upland oakwoodsxxiv) Wet woodlandCode-Point® (Post Codes)Code-Point® with polygonsMiniscale®AA gazetteer

60

Appendix 3: ERRF listing of environmental datasets

This document exists as an excel spreadsheet and provides details of data holdings and data managers. The Document has been supplied separately to Defra as an aid to NRP work.

61

Appendix 4: Contributors to the project

INDIVIDUALS ORGANISATION TOPIC

Andrew Baker Countryside Agency Access and landscapeHeiko Balzter CEH Soil and Vegetation CarbonMary Barkham ERFF ERFF DatabasesHelaina Black CEH SoilsIan Bradley National Soil Resources

Institute, Cranfield University

Soils

Neil Cape CEH Air qualityPeter Carey CEH Countryside Survey Ray Haines-Young Nottingham UniversityJane Hall CEH Critical LoadsMark Hill CEH/BRC Biodiversity Val Kirby Countryside Agency Access and landscape issuesJohn Kupiec Environment Agency ERFF Report and earlier

AssessmentsBrian Marker ODPM ODPM dataholdingsTerry Marsh CEH Floods and NRFAAndrew McKenzie BGS GroundwaterJohn Murphy CEH RIVPACSColin Neal CEH Water QualityCaroline O'Sullivan CEH Water Poverty IndexJohn Packman CEH Hydrological modellingTerry Parr CEH ECNMark Parry Defra SPIRE InitiativeKeith Porter English Nature BiodiversityJohn Rae Defra Air QualityBrian Reynolds CEH Data for WalesLesley Rickards BODC Marine ResourcesGeoff Smith CEH Land CoverIsabella Tindall CEH LOCAR and LOISJuliet Vickery British Trust for

OrnithologyBirds (Various data sets)

Philip White ODPM ODPM dataholdings

62

ORGANISATIONS CONSULTEDBritish Oceanographic Data CentreBritish Trust for OrnithologyBritish Geological SurveyCountryside AgencyCumbria County CouncilDefraERFFEnglish NatureEnvironment AgencyHerefordshire County CouncilInstitute of Public Rights of WayNational TrustOFWATOffice of the Deputy Prime MinistryProudman Oceanographic LaboratorySEPAVisit Britain/Tourist InformationWater UK

63

ANNEX 1:

SUMMARY TABLE FOR PROFORMA RETURNS FROM CONSULTEES

64

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK OF RESOURCE

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Countryside SurveyHeadwater Streams

Biological Quality

River Habitat Survey

Vegetation Fertility

pH

Light

Moisture

CSR

Land Cover Map Remotely Sensed Data Soil Vegetation and freshwater

Deposition and critical loads

Land Cover Broad Habitat

Hedgerow Length

Wall Length

Priority Habitats

Overall Assessment for resource

65

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Land CoverSatellite ?Survey – Prof Alice Coleman N/ASurvey – Dudley Stamp N/A

Overall Assessment for resource

66

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STATUS STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Biodiversity: Habitats and Ecosystems (including chemical composition)

ECN Ecosystems

ECN Broad Habitats

ECN Key Species and Taxa

ECN Rivers

ECN Lakes

ECN Chemical and physical analysis of soils over time.

Overall Assessment for resource

67

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Surface Water NRFA ?UK Floods Database ?

Overall Assessment for resource

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Groundwater Boreholes and wells

Aquifers ?

Level =

Quality

68

Overall Assessment for resource

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Chemical composition of water, water dynamics

LOIS

LOCAR

69

Overall Assessment for resource

70

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Rural Air SO2

NOx

O3

NH3

NHO3 ?VOCs ?PM10 ?Heavy Metals ?POPs and PAH ?Inorganic Ions

Other ?Overall Assessment for resource

71

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Soil Pollutants

Biological Quality

Chemical Quality

Physical Quality

Carbon

P Status

National Soil Inventory

National Soil Map

Auger Bores N/AProfiles N/AMaps N/ACS Map N/ARabbit Square N/AOrganic Carbon N/A

Overall Assessment for resource

72

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Biodiversity (BRC)Butterfly Monitoring

Vascular Plant

Butterflies

Other

Overall Assessment for resource

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Biodiversity (EN) Priority Habitats

Goelogical Sites

Dormice

Bats

SSSIs etc

Overall Assessment for resource

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Biodiversity: River water qualityRIVPACS

Overall Assessment for resource

73

74

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Biodiversity: Birds (BTO) Wintering Gulls

Wintering Farmland Birds

RAS

CES

NRCS

CBC

BBS

Breeding Atlas

WBS

WBBS

Herons

Non-breeding birds

Wintering Atlas

Garden Birds

Ring-recovery re-capture

Overall Assessment for resource

75

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Critical Loads Acidity

Nutrient Nitrogen

Semi-natural/Natural forested and non forested areas

N/AOverall Assessment for resource

76

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Water: Chemical composition Water Quality Uplands Lowlands

Overall Assessment for resource

77

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Carbon as derived from Earth Observation Techniques.

Soil - Land Cover Map

Soil - National Soil Map

Vegetation - Land Cover Map

Vegetation - UK Penology Observatory

Vegetation - Tree Height

Vegetation - NextMap

Vegetation - Forestry Commission

Overall Assessment for resource

78

RESOURCE DATA SET TREND QUANITY OF DATA

QUALITY OF THE DATA

INVENTORY OF STOCK

ASSESSMENT OF CURRENT CONDITION

ASSESSMENT OF SUSTAINABILITY

ASSESSMENT OF THREAT TO RESOURCE

Welsh Dataset GB Lakes

The Rothamsted Insect Survey national light-trap network

Lancaster university calcicolous grassland plots

Common Standards Monitoring (CCW)

Habitats of Wales Phase 1 Data, 1979-1997Lowlands and Uplands – one off sureyPhase 2 Lowland Grassland Survey of Wales – one off survey

Continuous plankton recorder survey

Overall Assessment for resource

79