Advances in Biodiversity Science: Predicting Species in Space and Time

Tom Stohlgren, Paul Evangelista, Amanda West, Greg Newman, Nicholas Young, Alycia Crall, Sara Simonson (NREL)

Catherine Jarnevich (USGS)Sunil Kumar, Tewodros Wakie (ARS),

Dave Barnett (NEON),The NASA DEVELOP team,

Matt Luizza (USFWS)Valerie Pretty Paint Small (Univ. Arizona)

Jeff Morisette (DOI), and many others over the past 25 years!

Contact: Paul.Evangelista@ColoState.edu Created November 9, 2017

Stohlgren, T. J., M. B. Coughenour, G. W. Chong, D. Binkley, M. Kalkhan, L. D. Schell, D. Buckley, and J. Berry. 1997. Landscape analysis of plant diversity. Landscape Ecology 12: 155-170.

1992 Leafy spurgein Beaver Meadows: Rocky Mountain NP

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Exotic Species Richness

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MikeCoughenour

GenevaChong

MohammedKalkhan

JoeBerry

DanBinkley

Stohlgren, T.J., Binkley, D., Chong, G.W., Kalkhan, M.A., Schell, L.D., Bull, K.A., Otsuki, Y., Newman, G., Bashkin, M. and Son, Y., 1999. Exotic plant species invade hot spots of native plant diversity. Ecological monographs, 69(1), pp.25-46. [cited 1081 times]

GregNewman

SaraSimonson

Teams of student

ecologists

Invasions cost us $120 Billion/year in the U.S. and $1.3 trillion/year globally; caused hundreds of species extinctions, and have high costs to human health.

Stohlgren, T.J., D. Barnett, C. Flather, P. Fuller, B. Peterjohn, J. Kartesz, and L.L. Master. 2006. Species richness and patterns of invasion in plants, birds, and fishes in the United States. Biological Invasions 8: 427-457.

From “Known Locations to Predictions”

And an iterative process as new data are added.

Stohlgren, T.J., and J. Schnase. 2006. Biological Hazards: What we need to know about invasive species. Risk Assessment Journal. 26: 163-173.

Rabbits -100%

Raccoons -99%

Opossums -99%

Bobcats -88%

Practical Applications:Burmese Pythons in Florida 1990s

CurrentDistribution

Don’t set your pet free here!

Rodda, G.H., Jarnevich, C.S. & Reed, R.N. 2009. What parts of the US mainland are climatically suitable for invasive alien pythons spreading from Everglades National Park? Biological Invasions 11:241-252.

Potential Python molurus Range in the United States

Invasive Species Examples:

Catherine Jarnevich

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2007 Potential suitable habitats for Asian Carpin continental United States

N= 56 Confirmed presence

2013 Actual Distribution of Asian Carpin continental United States

http://www.asiancarp.us/problem.htm

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Asian Carp

Catherine Jarnevich

SunilKumar

Ensemble habitat mappingof invasive plant species.

Stohlgren TJ, P. Ma, S. Kumar, M. Rocca, J.T. Morisette, C.S. Jarnevich, and N. Benson. 2010. Ensemble habitat mapping of invasive plant species. Journal of Risk Assessment 30: 224-235.

Dalmationtoadflax in

Yellowstone National Park,

Wyoming

Catherine Jarnevich

Sunil Kumar

JeffMorisette

Monique Rocca

Jarnevich, C. S. and T. J. Stohlgren. 2009. Near term climate projections for invasive species distributions. Biological Invasions 11:1373-1379.

We developed near term climate projections based on climatic trends from 1895 to 2006.

Near term projections, that may occur within a managers career, may aide management decisions in control efforts.

Risk analysis for northern expansion of Kudzu

Current 2035

Kudzu and Climate Change:

Catherine Jarnevich

Africanized Honey BeesAKA “Killer Bees”!

Stohlgren TJ, A.L. Szalanski, J. Gaskin, N. Young, A. West, C.S. Jarnevich, and A. Tripodi. 2014. From hybrid swarms to swarms of hybrids. Environment and Ecology Research 2: (8):1-10

European Honey Bees from England to Virginia in 1622.

Africanized Honey Bees from a science lab in Brazil in 1957.

Catherine Jarnevich

Nick Young

AmandaWest

RUSSIAN OLIVE INVASION AFFECTS AN INDIGENOUS CULTURE

Valerie Prettypaint Small PhD Dissertation

Crow Reservation Cottonwood tree For Sundance

Russian Olive invasion

Russian Olive ModelLoss of Cottonwood treesNear Ceremony Site

Valerie Small

Paul Evangelista

Barnett, D.T. and T. J. Stohlgren. 2016. Improving spatio-temporal hypotheses for monitoring ecological change. (Part of PhD Dissertation)

Consider three simple hypotheses: (1) Species distributions and potential habitat suitability change predictably in space; (2) Species distributions and potential habitat suitability change predictably in time; and (3) spatial and temporal trends in invasion are best measured with a field sampling design that captures biotic and abiotic gradients.

We demonstrate the utility of an iterative process that combines field sampling and modeling species.

Triage for Invasive Plant Speciesat Local Scales in Hawaii

Velvetgrass

HakalauForest National Wildlife Refuge, Hawaii

2007 2020 2050

2007 2020 2050

Dave Barnett

Kikuyugrass

Presence Locations

Modeled Distributions:Future Distributions:

Changes in habitat suitabilityRed = IncreasingYellow = StableBlue – DecreasingGrey = UnsuitableBlack = Clamping (need data)

Information on seed-source locations and changing climates is the key to accurate risk analysis of invasion potential.

Lepidium latifolium(Perennial pepperweed)

Tracy R. Holcombe, Thomas J. Stohlgren and Catherine S. Jarnevich. 2010. From Points to Forecasts: Predicting Invasive Species Habitat Suitability in the Near Term. Diversity 2010, 2:738-767.

Risk analysis under changing climateat national scales

Catherine Jarnevich

TracyHolcombe

Cats kill >1 Billion birds/year in the U.S.Science News  Feb. 23, 2013

Stohlgren, T.J., Jarnevich, C.S., and Giri, C.P., 2010. Modeling the spread of the human invader: Journal of Applied Remote Sensing, 4: 1-18.

Modeling the Human Invader

92% Accuracy

We looked at changes in “urban” 30m cells from LANDSAT from 1992 to 2001. 

Urbanization increased 7.5% (18,112 km2) in the nine year period‐‐an area the size of Massachusetts.

The spread of humans is easily predicted from growing degree days, elevation, humidity, and slope.

Wind‐blownseeds

Catherine Jarnevich

Bromberg, J.E.; Kumar, S.; and T.J. Stohlgren. 2011. Distributional changes and range predictions of downy brome (Bromus tectorum) in Rocky Mountain National Park. Invasive Plant Sci. Management 4: 173-182.

Distributional changes and range predictions of downy bromecheat grass in Rocky Mountain National Park.

• Distributions of cheatgrass are highly predictable in space and time with Maxent, a species-environmental matching model.

• New surveys found cheat grass in areas identified by the model.

1996 1999 2007

Sunil Kumar

JimBromberg

Potential niche shift for cheatgrass to 2050 in Rocky Mountain NP

West AM, S Kumar, CS Brown, TJ Stohlgren, and J Bromberg 2016 Field validation of an invasive species Maxent model. Ecological Inform. 36:126–134.

West AM, S Kumar, T Wakie, CS Brown, TJ Stohlgren, M Laituri, and J Bromberg 2015. Using high-resolution future climate scenarios to forecast Bromus tectorum invasion in Rocky Mountain National Park. PLoS One 10(2): e0117893

Sunil Kumar

JimBromberg

AmandaWest

CiniBrown

TewodrosWakie

MelindaLaituri

Using multi-date remote sensing to map cheatgrass

cover in wildlands

• Limited field data.• Detection

thresholds using standard 7.32-m plots coupled with Landsat imagery.

• Methodology is open source.

West, AM, PH Evangelista, CS Jarnevich, S Kumar, A Swallow, MW Luizza, SM Chignell. 2017. Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software. Intl. J. of Applied Earth Observations and Geoinformation 59: 135-146.

Sunil Kumar

AmandaWest

Catherine Jarnevich

Paul Evangelista

MattLuizza

Flory, A., Kumar, S., Stohlgren, T. J., and Cryan, P. (2012). Environmental conditions associated with bat White-Nose Syndrome mortality in the north-eastern United States. Journal of Applied Ecology, doi: 10.1111/j.1365-2664.2012.02129.x

Predicting Bat White-Nose Syndrome (WNS) in the northeastern US

Maxent predicted the most likely environmental surface conditions associated with bat WNS mortality with great accuracy (AUC = 0.85).Results suggest that WNS mortality is most likely to occur in landscapes that are higher in elevation and topographically heterogeneous, drier and colder during winter, and more seasonally variable than surrounding landscapes.Results provide a starting point from which to investigate and predict the potential spread and population impacts of this catastrophic emerging disease.

Sunil Kumar

PaulCryan

Abby Flory

Tick distributions and Lyme Disease

Hahn, M. B., C. S. Jarnevich, A. J. Monaghan, and R. J. Eisen. 2016. Modeling the Geographic Distribution of Ixodesscapularis and Ixodes pacificus (Acari: Ixodidae) in the Contiguous United States. J. Medical Entomology 53:1176-1191.

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Ixodes scapularis surveillance records

Ixodes scapularis habitat suitability

Catherine Jarnevich

Early Detection and Containment of Nutria

Eco-physiological model results

Carter and Leonard 2002, global distribution.

Jarnevich CS, Young NE, Sheffels TR, Carter J, Sytsma MD, Talbert C (2017) Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: an example with coypu (Myocastor coypus). NeoBiota 32: 107-125.

+ Correlative models

Photo by John and Karen Hollingsworth, USFWS, Bugwood.org

Catherine Jarnevich

Nick Young

Luizza, M.W., P. Evangelista, C. Jarnevich, H. Stewart, and A. West (2016). Integrating subsistence practice and species distribution modeling: Assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish. Environmental Management 58(1): 144-163.

Images courtesy of Fairbanksweeds.org

Current and future invasion of aquatic elodea in Alaska:Impacts on Native Alaskan fish subsistence

Current elodea habitat suitability 

Mid‐century (2040‐2059)     elodea climate suitability 

Elodea Management Concern 

AmandaWest

Catherine Jarnevich

Paul Evangelista

MattLuizza

Luizza, M.W., T. Wakie, P.H. Evangelista, and C.S. Jarnevich (2016). Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region. Ecology and Society 21(1): 22.

Using local knowledge to map invasive rubber vine: Threats topastoral livelihoods in northern Ethiopia

Images courtesy of M. Luizza

Paul Evangelista

MattLuizza

Catherine Jarnevich

TewodrosWakie

Arapahoe stonefly (Arsapnia arapahoe)

Finding a Needle in a Haystack: A very rare and cryptic Arapahoe Stonefly

Young NE, Stohlgren TJ, Fairchild M, and Belcher T (2016) Suitable Habitat of Arapahoe Stonefly (Arsapnia arapahoe) in the South Platte Watershed, Colorado Using Maximum entropy modeling.

How rare is it? Only 24 individuals detected from the last 15,000 samples.

Our models guided future sampling efforts. Successful every year.

20 additional individuals in 10 more locations; one much further south than any previous detection.

8 samples in Elkhorn Creek in 2013.

NickYoung

The NGOSs:Next Generation of Scientists

Thank you USGS, NASA, NEON, USFWS, USDA Forest Service for funding.(It’s a team effort)

Any?s

Newman, G.; Crall, A.; Laituri, M.; Graham, J.; Stohlgren, T.; Moore, J.C.; Kodrich, K.; and K. Holfelder. 2010. Teaching citizen science skills online: Implications for invasive species training programs. Applied Environmental Education & Communication 9(4): 276-286 (December 2010).

Crall, A.W.; Newman, G.J.; Stohlgren, T.J.; Holfelder, K.A.; Graham, J.; and D.M. Waller. 2011. Assessing citizen science data quality: an invasive species case study. Conservation Letters 4(6): 433-442.

AlyciaCrall

GregNewman

Finding new populations of the endangered

Mountain Nyala in Ethiopia

Landscape-scale modeling guided our team to the discovery of a new population of the endangered mountain nyala antelope. Our findings doubled the estimated global population from 1,500 to 4,000 individuals.

The integration of seasonal Landsat satellite data with our models was used to map critical mountain nyala habitat in Bale Mountains National Park.

Evangelista, P., J. Norman III., L. Behanu, S. Kumar and N. Alley. (2008). Predicting habitat suitability for the endemic mountain nyala (Tragelaphus buxtoni) in Ethiopia. Wildlife Research 35:409-416.

Evangelista, P., J. Norman, P. Swartzinski and N. Young (2012). Assessing habitat quality of the mountain nyala (Tragelaphusbuxtoni) in the Bale Mountains, Ethiopia. Current Zoology 58(4):525-535.

Paul Evangelista

Sunil Kumar

NickYoung

JohnNorman

Modeling the suitable habitat of invasive red lionfish (Pterois volitans)

We tested species distribution models in marine environments (3D) assessing the potential spread of red lionfish in the Atlantic and Pacific Oceans.

Our results showed that models performed best when occurrence points from both native and non-native ranges are used for the analyses.

Evangelista, P. N. Young, P. Schofield and C. Jarnevich (2016). Modeling the suitable habitat of invasive red lionfish (Pteroisvolitans) in the Atlantic and Pacific coasts of North, Central and South America. Aquatic Invasions 11(3):313-326.

Paul Evangelista

NickYoung

Catherine Jarnevich

Integrating local ecological knowledge

with species distribution models

to assess wildlife in Somaliland This was the first regional wildlife survey in Somaliland in over 100 years.

Over 50 mammal species were included in interviews of agro-pastoralists throughout the country.

Boosted Regression Tree and Maxent models were used to generate maps for 38 species.

Results strongly suggests that several species believed to be extirpated (e.g., cheetah, dibatag) appear to have viable populations.

Evangelista, P, A. Mohamed, I. Hussein, A. Saied, A. Mohammed and N. Young (In Review) Integrating local ecological knowledgeand species distribution modeling to detect wildlife in Somaliland. Ecosphere.

Paul Evangelista

NickYoung

Take Home Messages: • Over the past 25 years, the

NREL has become a leader in mapping and modeling harmful invasive plants, animals, and diseases; mapping native biodiversity, and locating rare and threatened species.

• Our products are in high demand, and backed by more than 250 scientific publications.

• This research would have been impossible without excellent support from the university, lab staff, and great students.

• Our most important role is training the Next Generation Of Scientists.

Questions?

Paul.Evangelista@ColoState.edu

Or

Thomas.Stohlgren@ColoState.eduCreated November 9, 2017