Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance
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Species-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.
We tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.
We compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.
Blackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.
LC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.
KeywordsAppalachians Breeding Bird Survey Distance sampling Landscape Conservation Cooperatives North Atlantic Point counts Removal sampling Validation Verification
We thank the U.S.G.S. Science Support Program for funding this study. No data sets were generated in this study. Data used in this study are partially available at ScienceBase, DOI 10.5066/F76Q1W53. At the time of publication, other data sets used in this study were not available or have limited availability (i.e., ongoing work, proprietary, or sensitive). Contact sources indicated in Appendix 1 for more information about these individual data sets. We thank Kevin McGarigal, Ethan Plunkett, Joanna Grand and Brad Compton from the Designing Sustainable Landscapes Project at the UMass Amherst-Landscape Ecology Lab, the North Atlantic Landscape Conservation Cooperative, and all those who provided field data: West Virginia U. Division of Forestry and Natural Resources graduate students Kyle Aldinger, Douglas Becker, Laura Farwell, Gretchen Nareff, and Jim Sheehan; Evan Adams, Biodiversity Research Institute; Erin King and Bill Thompson, U.S. Fish & Wildlife Service; Carol Croy U. S. Forest Service; Rich Bailey, West Virginia DNR; Alan Williams, Geoffrey Sanders and Adam Kozlowski, National Park Service; Frank Ammer, Frostburg State U., Emily Thomas and Margaret Brittingham, Penn State U.; David Yeaney, Western Pennsylvania Conservancy, and David King and Tim Duclos, U. Mass Amherst. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.
- Brooks RP (1997) Improving habitat suitability index models. Wildl Soc B 25:163–167Google Scholar
- Buehler DA, Hamel PB, Boves T (2013) Cerulean Warbler (Setophaga cerulea). In: Rodewald PG (ed) The birds of North America online. Cornell Lab of Ornithology, Ithaca. http://bna.birds.cornell.edu/bna/species/511. Accessed June 2016
- Burnham KP, Anderson DR (2012) Model Selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
- Caro T (2010) Conservation by proxy. Island Press, Washington, DCGoogle Scholar
- Colorado GJ, Hamel PB, Rodewald AD, Mehlman D (2012) Advancing our understanding of Cerulean Warbler (Setophaga cerulea) in the Andes. Ornitol Neotrop 23:307–315Google Scholar
- Deluca W, Holberton R, Hunt PD, Eliason BC (2013) Blackpoll warbler (Setophaga striata). In: Rodewald PG, The birds of North America online. Cornell Lab of Ornithology, Ithaca, NY. http://bna.birds.cornell.edu/bna/species/431. Accessed July 2016
- Ferree C, Anderson MG (2013) A map of terrestrial habitats of the Northeastern United States: methods and approach. The Nature Conservancy, Eastern Conservation Science, Eastern Regional Office, BostonGoogle Scholar
- Gawler SC (2008) Northeastern Terrestrial Wildlife Habitat Classification. Report to the Virginia Department of Game and Inland Fisheries on behalf of the Northeast Association of Fish and Wildlife Agencies and the National Fish and Wildlife Foundation. NatureServe, BostonGoogle Scholar
- Kroodsma D (2005) The singing life of birds. Houghton Mifflin, BostonGoogle Scholar
- Larson MA, Dijak WD, Thompson III FR, Millspaugh JJ (2003) Landscape-level habitat suitability models for twelve wildlife species in Southern Missouri. General Technical Report GTR NC-233. US Department of Agriculture, Forest Service. North Central Research Station. St. Paul, MNGoogle Scholar
- McGarigal K, Deluca WV, Compton BW, Plunkett EB, Grand J (2016) Designing sustainable landscapes: modeling focal species. Report to the North Atlantic Conservation Cooperative, US Fish and Wildlife Service, Northeast Region, Hadley, MA. http://jamba.provost.ads.umass.edu/web/lcc/DSL_documentation_species.pdf. Accessed September 2016
- North Atlantic Landscape Conservation Cooperative (2011) Executive summary. identifying representative species for the North Atlantic Landscape Conservation Cooperative (LCC). Available from https://www.fws.gov/northeast/science/pdf/Rep_Species_Executive_Summary.pdf. Accessed June 2016
- O’Neil LJ, Roberts TH, Wakeley JS, Teaford JW (1988) A procedure to modify habitat suitability index models. Wildl Soc B 16:33–36Google Scholar
- Porneluzi P, Van Horn MA, Donovan TM (2011) Ovenbird (Seiurus aurocapilla). In: Rodewald PG (ed) The birds of North America online. Cornell Lab of Ornithology, Ithaca, NY. http://bna.birds.cornell.edu/bna/species/088. Accessed July 2016
- Powers DMW (2007) Evaluation: from precision, recall and F-factor to ROC, informedness, markedness & correlation. J Mach Learn Technol 2:37–63Google Scholar
- R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/. Accessed Sept 2015
- Ralph CJ, Droege S, Sauer JR (1995) Managing and monitoring birds using point counts: standards and applications. In: Ralph CJ, Sauer JR, Droege S (eds) Monitoring bird populations by point counts. General technical report PSW-GTR-149. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Albany, CA, pp 161–169Google Scholar
- Rappole JH, McDonald MV (1994) Cause and effect in populatino declines of migratory birds. Auk 111:652–660Google Scholar
- Sauer JR, Niven DK, Hines JE, Ziolkowski Jr DJ, Pardieck KL, Fallon JE, Link WA (2017) The North American Breeding bird survey, results and analysis 1966–2015. Version 2.07.2017. USGS Patuxent Wildlife Research Center, Laurel, MD. https://www.mbr-pwrc.usgs.gov/bbs/. Accessed Mar 2017
- Sheehan J, Wood PB, Buehler DA, Keyser PD, Larkin JL, Rodewald AD, Wigley TB, Boves TJ, George GA, Bakermans GA, Beachy TA, Evans TA, McDermott ME, Newell FL, Perkins KA, White M (2014) Avian response to timber harvesting applied experimentally to manage Cerulean Warbler breeding populations. For Ecol Manag 321:5–18CrossRefGoogle Scholar
- Sólymos P, Moreno M, Lele SR (2014) detect: analyzing wildlife data with detection error. R package version 0.3–2. http://CRAN.R-project.org/package=detect. Accessed Mar 2016
- Stauffer D (2002) Linking populations and habitats: where have we been? Where are we going? In: Scott JM, Heglund PJ, Morrison ML, Haufler JB, Raphael MG, Wall WA, Samson FB (eds) Predicting species occurrences issues of accuracy and scale. Island Press, Washington, DC, pp 53–62Google Scholar
- Sweeney JM, Dijak WD (1985) Ovenbird habitat capability model for an oak-hickory forest. Proc Ann Conf of the Southeastern Assoc Fish Wildl Agencies 39:430–438Google Scholar
- US Fish & Wildlife Service (2009) North Atlantic Landscape conservation cooperative development and operations plan. Northeast Region U.S. Fish & Wildlife Service, Hadley, MAGoogle Scholar
- Van Horne B (2002) Approaches to habitat modeling: the tensions between pattern and process and between specificity and generality. In: Scott JM, Heglund PJ, Morrison ML, Haufler JB, Raphael MG, Wall WA, Samson FB (eds) Predicting species occurrences: issues of accuracy and scale. Island Press, Washington DC, pp 63–72Google Scholar
- Will TC, Ruth JM, Rosenberg KV, Krueper D, Hahn D, Fitzgerald J, Dettmers R, Beardmore CJ (2005) The five elements process: designing optimal landscapes to meet bird conservation objectives. Partners in flight technical series 1. Partners in flight. http://www.partnersinflight.org/pubs/ts/01-FiveElements.pdf. Accessed Oct 2015
- Zuur A, Ieno EN, Walker N, Saveliev AA, Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer, New YorkGoogle Scholar