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Climate envelope modeling for evaluating anticipated effects of climate change on threatened and endangered species in the Greater Everglades

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Frequently anticipated questions:


What does this data set describe?

Title:
Climate envelope modeling for evaluating anticipated effects of climate change on threatened and endangered species in the Greater Everglades
Abstract:
Our proposed project works toward finding solutions to problems related to long-term conservation planning in the face of the uncertainty surrounding climate change. We propose to work with resource managers to develop tools at appropriate spatial and temporal scales to assist with decision making. This project will result in both predictive ecological models and methodology for development and use of climate-based species-habitat relationships that will aid resource managers in long-term planning for sustainability of species.
To demonstrate the process and utility of our proposed approach, we will begin by focusing on the 21 threatened and endangered (T&E) terrestrial vertebrates in South Florida. By virtue of its physical features and geography, Florida, and in particular, South Florida will be highly susceptible to climate changes, specifically with regard to already apparent sea level rise. Although methodology and developed products will be applicable to other species and regions, our initial focus is to work with partners in the southeastern region and expand the list of species of interest in that region.
For each species we will use existing information for these 21 T&E species (U.S. Fish and Wildlife Service 1999, Cox et al. 1994), augment it with up-to-date data, and identify critical limiting factors directly and indirectly influenced by climate change. This information will be provided in the form of databases, species models (including climate envelopes), maps, and a desktop application that can be used in conjunction with projections of climate change, land use, and vegetation change to examine potential impacts on T&E species and their habitats.
Recent attention to potential impacts of climate change on habitats and species has focused on development of methods and tools that not only address current habitat and landscape conditions for species, but also help resource managers to look at potential future conditions to aid in long-term planning. Key elements to our proposed work are identifying limiting factors for species with respect to their habitats, compiling and applying population and habitat models, explicitly addressing uncertainties (assumption-driven research), and developing species habitat decision support. Data collected will be useful as inputs for efforts to assess species vulnerability.
  1. How should this data set be cited?

    Stephanie S. Romañach, Laura A. Brandt, Leonard Pearlstine, Donald L. DeAngelis, Ikuko Fujisaki, Frank J. Mazzotti, 2010, Climate envelope modeling for evaluating anticipated effects of climate change on threatened and endangered species in the Greater Everglades.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -81.25
    East_Bounding_Coordinate: -80.375
    North_Bounding_Coordinate: 25.375
    South_Bounding_Coordinate: 24.875

  3. What does it look like?

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 1991
    Ending_Date: unknown
    Currentness_Reference: ground condition

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: Project

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

    2. What coordinate system is used to represent geographic features?

  7. How does the data set describe geographic features?

  8. What biological taxa does this data set concern?

    Taxonomy:
    Keywords/Taxon:
    Taxonomic_Keyword_Thesaurus: None
    Taxonomic_Keywords: mammals
    Taxonomic_Keywords: birds
    Taxonomic_Keywords: reptiles
    Taxonomic_Classification:
    Taxon_Rank_Name: Kingdom
    Taxon_Rank_Value: Animalia
    Taxonomic_Classification:
    Taxon_Rank_Name: Phylum
    Taxon_Rank_Value: Chordata
    Taxonomic_Classification:
    Taxon_Rank_Name: Subphylum
    Taxon_Rank_Value: Vertebrata
    Taxonomic_Classification:
    Taxon_Rank_Name: Class
    Taxon_Rank_Value: Mammalia
    Taxonomic_Classification:
    Taxon_Rank_Name: Subclass
    Taxon_Rank_Value: Theria
    Taxonomic_Classification:
    Taxon_Rank_Name: Infraclass
    Taxon_Rank_Value: Eutheria
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Artiodactyla
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Cervidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Capreolinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Odocoileus
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Odocoileus virginianus
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Odocoileus virginianus clavium
    Applicable_Common_Name: Key deer
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Carnivora
    Taxonomic_Classification:
    Taxon_Rank_Name: Suborder
    Taxon_Rank_Value: Feliformia
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Felidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Felinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Puma
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Puma concolor
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Puma concolor couguar
    Applicable_Common_Name: eastern cougar
    Applicable_Common_Name: eastern puma
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Lagomorpha
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Leporidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Sylvilagus
    Taxonomic_Classification:
    Taxon_Rank_Name: Subgenus
    Taxon_Rank_Value: Sylvilagus (Tapeti)
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Sylvilagus palustris
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Sylvilagus palustris hefneri
    Applicable_Common_Name: Lower Keys marsh rabbit
    Applicable_Common_Name: Lower Keys rabbit
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Rodentia
    Taxonomic_Classification:
    Taxon_Rank_Name: Suborder
    Taxon_Rank_Value: Myomorpha
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Muridae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Sigmodontinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Neotoma
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Neotoma floridana
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Neotoma floridana smalli
    Applicable_Common_Name: Key Largo woodrat
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Oryzomys
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Oryzomys palustris
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Oryzomys palustris natator
    Applicable_Common_Name: rice rat
    Applicable_Common_Name: silver rice rat
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Peromyscus
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Peromyscus gossypinus
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Peromyscus gossypinus allapaticola
    Applicable_Common_Name: Key Largo cotton mouse
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Peromyscus polionotus
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Peromyscus polionotus niveiventris
    Applicable_Common_Name: southeastern beach mouse
    Taxonomic_Classification:
    Taxon_Rank_Name: Phylum
    Taxon_Rank_Value: Chordata
    Taxonomic_Classification:
    Taxon_Rank_Name: Subphylum
    Taxon_Rank_Value: Vertebrata
    Taxonomic_Classification:
    Taxon_Rank_Name: Class
    Taxon_Rank_Value: Aves
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Ciconiiformes
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Accipitridae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Accipitrinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Rostrhamus
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Rostrhamus sociabilis
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Rostrhamus sociabilis plumbeus
    Applicable_Common_Name: Everglade Snail Kite
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Charadriidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Charadrius
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Charadrius melodus
    Applicable_Common_Name: Chorlo chiflador
    Applicable_Common_Name: Piping Plover
    Applicable_Common_Name: pluvier siffleur
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Ciconiidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Mycteria
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Mycteria americana
    Applicable_Common_Name: Wood Stork
    Applicable_Common_Name: Cig¸eÒa americana
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Falconidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Caracara
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Caracara cheriway
    Applicable_Common_Name: Crested Caracara
    Applicable_Common_Name: Northern Crested Caracara
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Laridae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Sterninae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Sterna
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Sterna dougallii
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Sterna dougallii dougallii
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Passeriformes
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Corvidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Aphelocoma
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Aphelocoma coerulescens
    Applicable_Common_Name: Scrub Jay
    Applicable_Common_Name: Chara pecho rayado
    Applicable_Common_Name: Florida Scrub Jay
    Applicable_Common_Name: Florida Scrub-Jay
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Emberizidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Ammodramus
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Ammodramus maritimus
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Ammodramus maritimus mirabilis
    Applicable_Common_Name: Cape Sable Seaside Sparrow
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Ammodramus savannarum
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Ammodramus savannarum floridanus
    Applicable_Common_Name: Florida Grasshopper Sparrow
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Piciformes
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Picidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Picinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Picoides
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Picoides borealis
    Applicable_Common_Name: Red-cockaded Woodpecker
    Taxonomic_Classification:
    Taxon_Rank_Name: Class
    Taxon_Rank_Value: Reptilia
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Crocodilia
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Crocodylidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Crocodylus
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Crocodylus acutus
    Applicable_Common_Name: American Crocodile
    Applicable_Common_Name: Cocodrilo americano
    Applicable_Common_Name: caiman de la costa
    Applicable_Common_Name: Central American alligator
    Applicable_Common_Name: cocodrilo
    Applicable_Common_Name: lagarto
    Taxonomic_Classification:
    Taxon_Rank_Name: Order
    Taxon_Rank_Value: Squamata
    Taxonomic_Classification:
    Taxon_Rank_Name: Suborder
    Taxon_Rank_Value: Autarchoglossa
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Scincidae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Eumeces
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Eumeces egregius
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Eumeces egregius lividus
    Applicable_Common_Name: Blue-tailed Mole Skink
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Neoseps
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Neoseps reynoldsi
    Applicable_Common_Name: Florida Sand Skink
    Applicable_Common_Name: Sand Skink
    Taxonomic_Classification:
    Taxon_Rank_Name: Suborder
    Taxon_Rank_Value: Serpentes
    Taxonomic_Classification:
    Taxon_Rank_Name: Infraorder
    Taxon_Rank_Value: Alethinophidia
    Taxonomic_Classification:
    Taxon_Rank_Name: Family
    Taxon_Rank_Value: Colubridae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Drymarchon
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Drymarchon couperi
    Applicable_Common_Name: Eastern Indigo Snake
    Taxonomic_Classification:
    Taxon_Rank_Name: Subfamily
    Taxon_Rank_Value: Natricinae
    Taxonomic_Classification:
    Taxon_Rank_Name: Genus
    Taxon_Rank_Value: Nerodia
    Taxonomic_Classification:
    Taxon_Rank_Name: Species
    Taxon_Rank_Value: Nerodia clarkii
    Taxonomic_Classification:
    Taxon_Rank_Name: Subspecies
    Taxon_Rank_Value: Nerodia clarkii taeniata
    Applicable_Common_Name: Atlantic Salt Marsh Snake


Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

    • Stephanie S. Romañach, Laura A. Brandt, Leonard Pearlstine, Donald L. DeAngelis, Ikuko Fujisaki, Frank J. Mazzotti

  2. Who also contributed to the data set?

    FWS, NPS, University of Florida

  3. To whom should users address questions about the data?

    Stephanie S. Romanach
    U.S. Geological Survey
    3205 College Ave.
    Davie, FL 33314
    USA

    (754) 264-6060 (voice)
    (954) 475-4125 (FAX)
    sromanach@usgs.gov


Why was the data set created?

Specific Relevance to Major Unanswered Questions and Information Needs Identified:
- Our project will contribute greatly toward meeting needs of resource managers, in line with USGS' Strategic Science Direction, 'The USGS scientists will meet the pressing needs of the U.S. Department of the Interior, policymakers, and resource managers for scientifically valid state-of-the-science information and predictive understanding of climate change and its effects. Studies of the interactions among climate, earth surface processes, and ecosystems across space and time will contribute directly to the strategic goals of the U.S. Climate Change Science Program.' - Our products and collaborative process will help with efforts to develop a national strategy for assisting fish and wildlife in adapting to climate change. This process will work toward meeting Fish and Wildlife Service (FWS) goals outlined in their draft climate change strategy and 5-year action plan. In particular, this information will assist with the goals and objectives in the draft of Adaptation and Planning and Delivering Landscape Conservation; we will provide information that can be used in a landscape conservation approach to identify key areas that must be conserved to account for climate change impacts. - Our project will assist National Park Service (NPS) with their mandates to manage for ecosystems, not for biographic islands, and to achieve management objectives through the use of science.


How was the data set created?

  1. From what previous works were the data drawn?

  2. How were the data generated, processed, and modified?

    Date: Unknown (process 1 of 2)
    This project will compile the most up-to-date information on the 21 T&E, non-marine, vertebrate species in South Florida using existing literature and databases and workshops of ecological experts (Year 1).
    Climate data will be compiled from sources that provide reliable data at the appropriate resolution (e.g., National Climatic Data Center, Worldclim database [1 km resolution]). Climate variables used will be determined by information collected on the species and may include degree-days, temperature and precipitation averages, extremes, ranges, and seasonal averages. (Years 1&2).
    Land cover/habitat information will be compiled from a variety of sources and then associations/linkages will be made among classes in the various layers (i.e., cross-walking; Year 1).
    This information will form the basis for developing climate envelope models, a tool used to examine potential species range shifts under climate change scenarios. Climate envelope models are used to predict the distribution of a species in the future if it is to live in the same range of climatic conditions that it currently inhabits.
    We will define climate envelopes over the entire geographic distribution and project those envelopes based on alternative futures (e.g., IPCC projection for 2100) for each species (Years 2&3).
    Maps for the entire geographic range of each species will be compiled and overlaid with broad land cover layers to determine presence of suitable habitat within each grid cell. Climate data will be associated with species presence and absence at each cell and a nonparametric regression tree approach, random forest predictors (Breiman 2001), will be used to correlate climate variables with species presence/absence. Twenty percent of the presence/absence data will be withheld from the modeling to use for model validation (Years 2&3).
    At the South Florida scale, climate envelopes will be combined with land cover and habitat models refined in technical workshops and used with local alternative future conditions being developed by MIT/USGS (Year 3).
    Drs. Leonard Pearlstine (NPS), Steve Friedman (NPS), and Laura Brandt (FWS) will participate in workshops, data gathering, and providing guidance to this project. Matthew Supernaw (NPS) will work closely with UF/USGS programmers to implement the models.

    Person who carried out this activity:

    Stephanie S. Romanach
    U.S. Geological Survey
    3205 College Ave.
    Davie, FL 33314
    USA

    (754) 264-6060 (voice)
    (954) 475-4125 (FAX)
    sromanach@usgs.gov

    Date: 2010 (process 2 of 2)
    Tasks for FY10:
    - Compile map layers of current species' geographic ranges - Begin compiling database of climate information important for species geographic range limits (e.g., temperature, precipitation) - Compile map layers of land cover/habitat for species geographic ranges - Comparison of potential modeling methods (e.g., support vector machines, random forests models) using 1 - 3 species as test cases - Progress (semi-annual) and final (annual) reports

    Person who carried out this activity:

    Stephanie S. Romanach
    U.S. Geological Survey
    3205 College Ave.
    Davie, FL 33314
    USA

    (754) 264-6060 (voice)
    (954) 475-4125 (FAX)
    sromanach@usgs.gov

  3. What similar or related data should the user be aware of?

    Beaumont L. J., A. J. Pitman, M. Poulsen, and L. Hughes, 2007, Where will species go? Incorporating new advance in climate modelling into projections of species distributions: Global Change Biology v. 13, n 7, P. 1368-1385.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Breiman, L., 2001, Random Forests: Machine Learning v. 45, n. 1, P. 5-32.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Cox, J., Kautz, R., MacLaughlin, M. and Gilbert, T., 1994, Closing the Gaps in Florida's Wildlife Habitat Conservation System. Office of Environmental Services: Florida Game and Fresh Water Fish Commission, Tallahassee, FL.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Huntley, B. R. E. Green, Y. C. Collingham, J. K. Hill, S. G. Willis, P. J. Bartlein, W. Cramer, W. J. M. Hagemeijer, and C. J. Thomas, 2004, The performance of models relating species geographical distributions to climate is independent of trophic level: Ecology Letters v. 7, n. 5. P. 417 - 426.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Jiguet F., A. Gadot, R. Julliard, S. Newson, and D. Couvet, 2007, Climate envelope, life history traits and the resilience of birds facing global change: Global Change Biology v. 13, n. 8, P. 1673-1685.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Lawler J. J., D. White, R. P. Neilson, and A. R. Blaustein, 2006, Predicting climate-induced range shifts: model differences and model reliability: Global Change Biology v. 12, n. 8, P. 1568-1584.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Thomas, C.D., A. Cameron, R.E. Green, M. Bakkenes, L.J. Beaumont, Y.C. Collingham, B.F.N. Erasmus, M. Ferreira de Siqueira, A. Grainger, L. Hannah, L. Hughes, B. Huntley, A.S. van Jaarsveld, G.F. Midgley, L. Miles, M.A. Ortega-Huerta, A.T. Peterson, O.L. Phillips, S.E. Williams, 2004, Extinction risk from climate change: Nature v. 427, n. 6970, P. 145-148.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Thuiller, W., S. Lavorel, M.B. Araujo, 2005, Niche properties and geographical extent as predictors of species sensitivity to climate change: Global Ecology and Biogeography v. 14, n. 4, P. 347-357.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Pearson, R.G. and T.P. Dawson, 2003, Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?: Global Ecology & Biogeography v. 12, n. 5, P. 361-371.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    U.S. Fish and Wildlife Service, 1999, South Florida Multi-Species Recovery Plan: USFW, Atlanta, GA.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011
    Drake, J.M. & J.M. Bossenbroek, Unknown, Profiling ecosystem vulnerability to invasion by zebra mussels with support vector machines: Theoretical Ecology v. 2, n. 4, P. 189-198.

    Online Links:

    Other_Citation_Details: accessed as of 08/25/2011


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

  2. How accurate are the geographic locations?

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    In year one; however funding is limited. At the end of FY10, we will submit a database with life history, range, habitat associations, and vulnerability traits for each species; compiled land cover/habitat information; and results of a comparison of modeling methods (support vector machine vs. random forests) for 1 - 3 case study species. We will submit a progress report of our work for the first half of FY10.

  5. How consistent are the relationships among the observations, including topology?

    In our effort to develop appropriate models for resource managers' needs, we will use the best and most up-to-date information and methods available. For each of the T&E species under consideration, we will develop bioclimatic models, also called 'climate envelope' models or 'niche' models. These models allow us to relate species' geographic distributions to climate factors. Determining the niche of a species allows its potential geographic range to be forecast through projection of the estimated niche boundary on a spatial domain (Drake & Bossenbroek 2009).


How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: none
Use_Constraints: none


Who wrote the metadata?

Dates:
Last modified: 19-Aug-2011
Metadata author:
Heather Henkel
U.S. Geological Survey
600 Fourth Street South
St. Petersburg, FL 33701
USA

727 803-8747 ext 3028 (voice)
727 803-2030 (FAX)
sofia-metadata@usgs.gov

Metadata standard:
FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata (FGDC-STD-001.1-1999)


Generated by mp version 2.9.14 on Tue Oct 25 16:03:09 2011