Meixler, Marcia S. & Fisher, Kim & Sanderson, Eric W. (). Latitude-enhanced species-area relationships for conservation planning. Landscape Ecology Retrieved from https://doi.org/doi:10.7282/t3-w8jk-e164
Changes in biodiversity patterns have prompted efforts aimed at development of tools for conservation planning. Species-area relationships are useful; however these models could be strengthened with the addition of a latitudinal factor.
We built latitude-enhanced species-area relationship models to predict species richness for a variety of common taxa in the eastern United States.
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.
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). The amphibian model was the weakest and had the lowest accuracy but was the model in which latitude had the strongest influence, explaining 8% of the overall variance. 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 when comparing two similarly sized US Protected Areas, the parcel l.25 degree in latitude lower would
likely have one more bird species, four more plant species, and an additional amphibian species.
The latitude term added value to the species-area relationship models for most taxa and proved useful in explaining variation in species richness in areas of the East Coast of the United States. Our latitude-adjusted SAR approach is useful for species richness optimization in conservation planning.
SubjectsModel, Negative binomial regression, Species richness, Taxa, Vertebrates
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