Latitude-enhanced species-area relationships for conservation planning
Abstract
Context
Species-area relationship models are useful in conservation planning; however these models could be strengthened with the addition of a latitudinal factor.
Objectives
We built latitude-enhanced species-area relationship models to predict species richness for a variety of common taxa in the eastern United States at local to regional scales.
Methods
We used data from complete surveys of East Coast parks in the United States to build latitude-enhanced species-area relationship models for amphibians, birds, freshwater fish, mammals, marine fish, plants, and reptiles. We used data from the published literature and United States Fish and Wildlife Refuges to independently test the accuracy of the models. We demonstrated the utility of all modeled taxa within selected East Coast Protected Areas of the United States.
Results
Our models explained 35–91% of the variation in surveyed species richness, with marine fish, freshwater fish and reptile models exhibiting the strongest relationships (pseudo-R2 = 0.91, 0.66, and 0.70, respectively). Latitude had the strongest influence in the amphibian model. During accuracy testing, all taxa exhibited significant agreement between observed and predicted species richness and explained 75–97% of the variation. Our demonstration showed that for two similarly sized US Protected Areas, the parcel l.25° lower in latitude would likely have one more bird species, four more plant species, and an additional amphibian species.
Conclusions
The latitude term added value to the species-area relationship models for most taxa and proved useful for conservation and urban planning in local to regional sized areas of the East Coast of the United States.
Keywords
Model Negative binomial regression Species richness Taxa Urban VertebratesNotes
Acknowledgements
This study was supported by funding from the United States Department of the Interior, National Park Service [Cooperative agreement: P14AC01473]. We would like to thank the people who helped in the collection of data for this project, namely: Jennifer Meller, Glen Kandia, and Joseph Rua. Ellen Creveling of The Nature Conservancy generously shared data for model construction and we very much appreciate her willingness to collaborate on this project. We would also like to thank Charles Yackulic for valuable statistical modeling input, Glen Kandia for editing assistance, and to the anonymous reviewers for their comments that helped to improve the presentation.
Supplementary material
References
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