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Landscape Ecology

, Volume 33, Issue 1, pp 77–91 | Cite as

Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

  • Zachary G. LomanEmail author
  • William V. Deluca
  • Daniel J. Harrison
  • Cynthia S. Loftin
  • Brian W. Rolek
  • Petra B. Wood
Research Article

Abstract

Context

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.

Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

Keywords

Appalachians Breeding Bird Survey Distance sampling Landscape Conservation Cooperatives North Atlantic Point counts Removal sampling Validation Verification 

Notes

Acknowledgements

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.

Supplementary material

10980_2017_582_MOESM1_ESM.docx (21 kb)
Supplementary material 1 (DOCX 21 kb)

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Wildlife Fisheries and Conservation BiologyUniversity of MaineOronoUSA
  2. 2.Department of Environmental ConservationUniversity of MassachusettsAmherstUSA
  3. 3.Maine Cooperative Fish and Wildlife Research UnitU.S. Geological SurveyOronoUSA
  4. 4.U.S. Geological Survey, West Virginia Cooperative Fish and Wildlife Research UnitWest Virginia UniversityMorgantownUSA

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