diana c diaz g pacific essay

8/6/2019 Diana C Diaz G Pacific Essay

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COMPUTATIONAL TOOLS FOR THE ANALYSIS OF OCEANOGRAPHIC

VARIABLES AND THEIR INFLUENCE ON THE DISTRIBUTION ANDABUNDANCE OF MARINE SPECIES IN THE COLOMBIAN PACIFIC

Daz-Guevara1, D.C;

1Department of Basic Sciences, Faculty of Natural Sciences and Engineering, Universidad

Jorge Tadeo Lozano, Sede Bogot. Carrera 4 No. 22-61, Bogot, Colombia.

[email protected].

ABSTRACT

The space-time behavior of oceanographic variables such as sea surface temperature,

chlorophyll, dissolved organic matter, and the diffuse attenuation coefficient of the

Colombian Pacific Basin (CPB) was studied during the period 2003 to 2010, by means of

the computational tool SeaWiFS Data Analysis System (SeaDAS). The influence was

evaluated of these parameters on the distribution and abundance of certain pelagic species

of commercial interest to the country, and for this purpose the environmental conditionsand the catch records (which allow for the estimation of the population dynamics of the

species) were consulted and all of the information was represented in maps elaborated with

the tools PBSmapping and PBSmodelling from the software R2.11.0. With the established

methodology the analysis of the geo-referenced data was facilitated and the products were

designed to describe and understand complex relationships between them. The created

maps contain useful statistical information, and they have the advantage of being madewith free software that employs standard programming languages such as C or IDL. The

maps were constructed with a data structure defined by the typical design concepts of R,using functions and implementing the necessary algorithms to graph, plot the grids,

calculate the area of the polygons, and estimate correlations between them. Additionallywith SeaDAS, ranges were selected and isolated of optimal climatic variables for the

species, which allowed for the design of alternatives for the sustainable management of theresources. The conclusion of this project presents an approach to problems in the field of

bioclimatology, which involves the study of oceanographic and/or meteorological variables

and their effect on marine ecosystems, specifically in the case of the Colombian Pacific.

Key Words: Remote Sensors, GIS, SeaDAS, PBSmapping, Marine Resources.

INTRODUCTION

The use of remote sensors has permitted oceanographic studies to be carried out in regions

where sufficient information was previously unavailable for further knowledge of the landsystem. They are permanently used for the estimation of bio-optical variables that facilitate

all types of investigations related to the ocean. With the information collected by thesensors for example, the following factors can be estimated: sea surface temperature (SST),

clorophyll concentration (Clh), dissolved organic matter (CDOM), diffuse attenuation

coefficient (k490), and other oceanographic or meteorological variables with which it is

possible in turn to characterize bodies of water and also to determine patterns of

distribution and abundance of species present in the studied system.


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Currently remote sensing, geographical information systems (GIS), and mapping play a

major role in the formulation of strategies for the development and sustainablemanagement of natural resources (Selvaraj 2009). The present article is focused on the

application of these computational tools with the end of protecting Colombias marineresources.

The purpose is also to promote this type of work to get the attention of the individuals andinstitutions involved in this sector of the economy and to make the implementation of these

new tools and technologies effective (FAO 2007). In this vein, an application example is

presented that, beyond showing the results found, seeks to share a methodology that can be

reproduced in any case study with a similar objective.

The two tools mentioned are in essence different, as remote sensing is the medium throughwhich the information is obtained, and the GIS is what provides the organization and

availability of the data to create static maps for investigation, or for operations in real time.In the majority of the cases the acquisition of data is one of the first obstacles that needs to

be overcome, and for this reason a free method of obtaining information is presented.

The first people in the world to use remote sensors for the estimation of productive regionsof commercial interest were Kapetsky & Caddy (1985), Mooneyhan (1985), and Travaglia

& Appelkamp (1985). In Colombia there are projects in which physical and biologicalaspects of the Colombian Pacific Ocean (CPO) are described for different periods of time

through on-site information and products derived from satellite images. It is Andrade &

Barton (2000) who evaluated the color of the ocean in the Colombian Caribbean, and Melo

(2002), Orejarena et al. (2004), and Malikov & Villegas (2005) who studied the space-time

variation of physical variables in the marine areas of Colombia to calculate their primary

productivity, all using remote sensors. Also employing computational tools, DIMARs

Area of Operational Oceanography has studied the Sea Surface Temperature (SST),

surface chlorophyll a, and geostrophic currents in the Colombian Pacific Basin (CPB), as a

complement to the information obtained on-site during oceanographic cruises (Bastidas y

Rodrguez 2006).Other projects based on remote sensors of the CIOH have been carried out principally in

the Caribbean, in distinct cases such as the evaluation of the degree of pollution in the Bay

of Cartagena, the influence of the North Colombian Countercurrent on the circulation ofwaters at the continental shelf, and this currents effect on the dispersion of airborne

effluents in the Magdalena River. Remote perception studies have been carried out oncoastal oceanography, the Bay of Barbacoas, the Levee Canal, the Rosario Islands, and the

bio-ecological cartography of Treasure Island. Among others, the highlights have been theremote perceptions applied to determine the circulation of surface waters in the Gulf of

Urab and the variations of its coastline, the engineering analysis for protection of thecoasts, and the evaluation of the annual variability of organic carbon content on the surface

of the western Caribbean Sea through the registers of the CZCS.

Bio-optical variables have also been used to determine distribution patterns and estimate

the effective population size of some species (Rueda 2001, Pramo and Roa 2002, Pramo

et al. 2003, Rueda and Defeo 2003a, b, Selvaraj 2009). Herrera (2009) carried out a study

from 2006 to 2008 of richness, diversity, distribution, and relative spatial and seasonal

abundance of cetaceans in the CPB using remote sensors and information collected on-site.

Herrera (2009) found (cite textually) significant differences in relative abundance and

richness between the two climatic periods of the year, despite great inter-annual


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oceanographic differences caused by events such as El Nio and La Nia. Until now a

large part of the studies published about oceanography in this country has been based onthe compilation, processing, and purification of oceanographic data in the open ocean and

the description of products obtained by satellite sensing, all with the end of broadeningknowledge of this regionwhich is the scene of different economic activities related

principally to fishing, marine aquaculture, and maritime transport.

However, to ensure the sustainable development and management of marine resources, it isnecessary to have a decision-making system that is supported in the investigation projects.

For this reason, as mentioned at the beginning, this article presents computational tools that

facilitate the analysis of oceanographic variables which determine the distribution and

abundance of marine species and which allow for the identification of sectors that are

either over-exploited or have sufficient resources to be used appropriately.

MATERIALS AND METHODS

The area of investigation is the Colombian Pacific Basin (CPB), whose geographic limitsare: the waters of the Gulf of Panama to the north; the departments of Choc, Valle del

Cauca, Cauca, and Nario to the east; the waters of the Ecuadorian coast and the Carnegie

underwater mountain range to the south; and the Pacific Ocean, the territorial waters ofPanama, and the Cocos mountain range to the west. The CPB is located between 130N

and 710N, and between 7740W and 8400W.

For the present project two computational tools were used: SeaWiFS Data Analysis System(SeaDAS, http://seadas.gsfc.nasa.gov/) and PBSmapping-PBSmodelling (package for R,

http://cran.r-project.org/web/packages/PBSmapping/index.html). They can be implementedeasily and they have the advantage of being open source.

SeaDAS is a program designed to process, visualize, analyze, and carry out quality controlon data about the color of the ocean. It can read data from the sensors MODIS/Aqua,

MODIS/Terra, SeaWiFS, OCTS, and CZCS, and it is a useful scientific tool for analyzing

satellite images. SeaDAS allows all of the data to be processed from L0 or L1A to L3 and

SMI, can reproduce the standard available products on the Web (color and SST), and

works in the Linux, Mactintosh, and Sun Solaris operating systems, among others. It uses

three modes of operation: Graphic interface, Command lines (IDL/UNIX), and Scripts

(IDL files/UNIX shell scripts).

Furthermore, PBSmapping is designed to facilitate the compilation and analysis of geo-

referenced data. It is designed in the R language (version R 2.11.0.), allows explorations to

be carried out similar to those commonly available in the Geographic Information Systems,

contains algorithms to visualize polygons, locates catches, and converts coordinates(Schnute et. al2008).


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SCIENTIFIC NAME 2000 2001 2002 2003 2004 2005 2006 2007

ARIIDAE 488 94 82 56 64 5 10 10

BIVALVIA 10 1 4 1 2 31 20 20

BRACHYURA 38 74 596 114 551 417 450 450

CARANXSPP 568 217 223 129 229 58 120 120

CENTROPOMUS SPP 83 37 37 1 44 6 20 20CETENGRAULIS MYSTICETUS 25,099 25,028 28,879 25,269 21,170 5,081 13,000 13,000

CLUPEOIDEI 0 2,708 454 0 0 0 0 0

CYNOSCION ANALIS 317 230 211 6 138 14 30 30

EPINEPHELUS ANALOGUS 85 139 47 8 43 2 10 10

EUTHYNNUS LINEATUS 79 120 0 0 0 0 0 25

GERREIDAE 18 58 91 0 40 0 0 0

KATSUWONUS PELAMIS 5,661 1,813 2,080 12,334 5,866 11,087 21,159 17,431

LOLIGINIDAE,

OMMASTREPHIDAE87 76 68 42 25 9 10 10

LUTJANUS ARGENTIVENTRIS 182 51 107 47 51 41 40 40

LUTJANUS SPP 620 477 411 134 245 121 180 180

MERLUCCIUS

ANGUSTIMANUS0 391 0 54 61 85 70 70

MICROPOGONIAS SPP 237 155 176 107 115 35 50 50

MUGILIDAE 28 22 28 0 43 1 10 10

MUSTELUS SPP 678 520 357 1 368 339 350 350

MYCTEROPERCA XENARCHA 210 66 106 32 55 54 55 55

NATANTIA 601 4 13 0 910 7 50 50

OSTEICHTHYES 3,378 4,135 4,412 1,053 1,340 749 3,083 3,110

PENAEUSOCCIDENTALIS 1,219 979 561 846 350 325 330 330

PERCIFORMES 590 282 213 62 70 0 0 0

PLEURONECTIFORMES 160 171 79 82 7 32 20 20

SCOMBEROMORUS SIERRA 831 379 361 0 232 179 200 200

SCOMBROIDEI 24,158 43,840 0 0 35,086 22,933 10,320 10,320

SERIOLA SPP 0 91 0 0 70 4 20 20

SOLENOCERAAGASSIZII 686 522 1 688 208 339 320 320THUNNUS ALBACARES 9,758 16,085 15,975 41,824 19,603 21,908 13,006 15,797

THUNNUS OBESUS 230 103 159 1,458 978 3,000 5,240 2,940

XIPHOPENAEUSRIVETI 2,539 716 561 846 511 413 450 450

Table 1: Principally-fished species in tons (FAO) in the Eastern Colombian Pacific.

RESULTS

The first stage of the Project consisted of generating the products of the chosen bio-opticalvariables, and each image was composed of data from the average monthly multi-annual

data from the period 2002 to 2010. Temperature fronts, zones of high chlorophyll

concentration, and dissolved organic matter were identified during the year. In Table 2, thecharacteristics observed in each case are briefly described.

Variable and

Range

Description

SST (C) On average, values between 22 and 28C are observed. In the first

months of the year (January to April) SST increases from east to

west, however thermal fronts are identified on the Colombian coast

and in Panamanian waters. The rest of the year the gradient signals


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lower temperatures to the south and greater temperatures in the center

and north of the CPB.

Chlorophyll(mgm-3)

Min: 0.01

Max: 10

The values oscillate between approximately 0.5 and 7mg/m-3

for thedifferent regions with the greatest values being concentrated near the

southern Colombian coast, although they are not comparable with the

values that appear in Panamanian territory.

K490 (m-1)Min: 0.01

Max: 5

K490 indicates the waters vertical attenuation coefficient for awavelength of 490nm, and it is observed that near the Colombian

coast values between 0.3 and 1.5m-1

are maintained during the whole

year. The greatest values for the entire Basin are obtained between

January and April (0.1-1), and then go down 0.02. K=0.02

demonstrates the transmission of blue light and indicates the presence

of principally organic acids and inorganic salts in this region. K=0.2 to

2 indicates transmission of blue light through water that is cloudier,

which in turn indicates a reduction in the energy stored in the water

column, so almost all of the energy can be absorbed in the first 10m.

CDOM It is observed in the coastal region that values between 2.00 and 3.50

are maintained throughout, while in the oceanic region a decrease is

observed in the dissolved organic matter, which is usual. In this casethe variable is useful for identifying if the signal moving toward the

green is really an indicator of high chlorophyll concentration or if it isdue to the presence of dissolved organic matter whose spectral

response is very similar.

Fluorescence

(mWcm-2

m-

1sr

-1)

Min: 0Max: 0.05

This is a relative measure of the quantity of radiation that leaves the

surface of the ocean through emissions of chlorophyll fluorescence.This variable is considerably high during April and May and minimal

from September to November. When the phytoplankton is understress it emits sunlight which is absorbed as fluorescence, and this

gives information about the photosynthetic activity that is occurring.

For the CPB the values oscillate between 0.02 and 0.04.POC (mg m-3

)Min: 10

Max: 1000

This is the indicator of undissolved carbon, and during the whole yearaverage values are found to be higher than 50mgm3. The

concentrations near the Panamanian coast and along the coastlinestand out, as they can increase to 300mgm3 or more, especially in the

period from February to April.

PIC (mol m-3)

Min: 5e-05

Max: 0.02

0.02mol/m3 is the maximum concentration of inorganic particulate

matter on the coast. In the rest of the region the concentrations are

minimal and do not exceed 0.0002 mol/m3.

Table 2: Description of the annual variability of bio-optical variables in the Colombian

Pacific Ocean.

With the recorded observations it is possible to identify some sectors with well-defined

thermal fronts, especially during the period from January to April. During the second

semester they are less perceptible because of the displacement of the Intertropical

Convergence Zone (ITCZ) to the north, which intensifies the wind field over the

Colombian Pacific and generates movement in the surface water layers, thereby modifying

the temperature of the water column. The presence of these fronts can also explain the

possible inflow of water from the California current to the north and the Peruvian Current


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to the south, howeverthe characteristics ofthe Basin s seabed do not permit a considerable

exchange of deep waters from the central Pacific. Variables such as chlorophyll, CDOM,

POC, and reflectance show that during February, March, and even April the greatest

photosynthetic activity is achieved in a large part ofthe Basin s oceanic region, for which

reason it is an importanttime for the food web of this marine ecosystem. In the coastal

zone the photosynthetic activity is permanent, howeverthe principal limiting factoris the

small amount of radiation penetration in the water column according to what isdemonstrated by the values for K490, possibly due to the concentration of particulatematterin suspension and dissolved organic matter.

Figure 2: Annual variability of SST from 2002 to 2010 in the CPB.

Figure 3: Annual variability ofCDOM from 2002 to 2010 in the CPB.


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From the produced images whose succinct description is presented in Table 2, the data

were taken for different points in the Colombian Pacific, and with the ShipTrack

SeaDAS function these data were filtered and compared with some previous registers

reported in the scientific literature. This information, added to the catch data and to an

additional variable called vertical upwelling velocity (Vz), was graphed using

PBSmapping with the end of locating zones of high photosynthetic activity in the Basin

and their relationship to the catches per unit of effort (CPUE).

The following species were selected:

Species

Optim lTemperature

Range forits

Growth

Katsuwonuspelamis (Skipjack Tuna) 15-30

Thunnusalbacares (Yellowfin Tuna) 15-31

Cetengraulismysticetus (Shoal) 24-28

Thunnusobesus (Bigeye Tuna) 13-29

Table 3: Preliminarily chosen species.

With the temperature data and the Contour SeaDAS function, the regions ofthe Basin

with that temperature were identifiedinformation that was later exported toPBSmapping.

Two examples are later presented of the graphs obtained, which do not necessarily

correspond to real data as they are preliminary results that are still being developed.However, as mentioned atthe beginning, the type of analysis that can be carried out with

these computational tools is illustrated. Figure 4 shows the result ofthe overlap of catch

records and bio-optical variables, and the location of the grids indicates regions of high

photosynthetic activity. The dots are catch information and the coloris the index ofCPUE.

Figure 5 presents potential zones for fishing activity (in clear green grids) through thecorrelation between the variables from Table 2 and Vz.

Figure 4. Overlap of catch records and bio-optical variables. The location ofthe grids

indicates regions of high photosynthetic activity, the dots indicate catch information, and

the colorindicates CPUE.


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Figure 5. Determination of potential zones for fishing activity, taking into accountthevariables from Table 2 and Vz. The colorindicates the magnitude of Vz (m/s).

Discussion

The FAO (Food and Agriculture Organization ofthe United Nations) has divided the globe

into 27 principal fishing areas. The Colombian Pacific Ocean belongs to region 87

(southeastern Pacific), North subarea, and divisi n 1.11, mostly 1.21 (Figure 6).

Figure 6. Principal fishing areas according to the FAO (FAO 2007).

According to the FAO registers, fishing activity has increased considerably in Colombia,

and in Figures 7a and 7b this climb in the number of tons caught can be observed,

especially from the 1990s to the present, exceeding 140,000 tons caught and 65,000 tonsfrom aquaculture.


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Figure 7a: Tons Caughtin Colombia (FAO

2010).

Figure 7b: Aquaculture Production in

Tons (FAO 2010).

This suggests that each day marine resources are more commercialized. The presented

tools allow the effect of environmental conditions on the marine ecosystem to be

illustrated, as well as the impact these conditions have on the dynamic of the species,

especially pelagic species that during all stages of life remain in the same habitat. Tuna,billfishes, and others are pelagic and the physical factors that affect the tropical andsubtropical Pacific Ocean can exercise important effects on their distribution and

abundance (CIAT 2010). The environmental conditions cause considerable variability inthe recruitment of the resources, for example el Ni o, which produces a sinking in the

thermocline and leads to a reduction in the catch rates oftuna. A change in SST can makefish move from an area with warm or cold waters to a more favorable area.

The results obtained show a relationship between the studied variables and the location of

the species of commercial interest, but what is really important is how the different toolscan be combined in order to locate regions in which aquaculture activities could be

developed so as notto exhaust natural resources.

The presented results are only a start, and currently the final objective is the creation of

multispecies ecosystem models that represent the ecological interactions among species.

For example, personnel from CIAT have developed a model of the pelagic ecosystem in

the eastern tropical Pacific Ocean (CIAT Bulletin, Vol. 22, No. 3) to relate climatic factors

to fishing, and their effect on the trophic levels. However, the resolution of this model is

regional, a fact that makes it necessary to continue this type of work (which does not

require software licenses and can be achieved on a local scale).

Conclusion

With the methodology presented for analyzing geo-referenced data for bio-optical

variables and the catching of pelagic species in the Pacific, products and maps weredesigned with information that allows zones of high primary productivity to be estimated.They have the advantage of being made with free software that uses standard programming

languages such as C or IDL, and the maps were built with an Rdata structure using thePBSmapping package. The project shows a way of approaching problems in the field of

bioclimatology, which implies the study of oceanographic and/or meteorological variablesand their effect on marine ecosystems, specifically in the case ofthe Colombian Pacific.


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