The distribution of species across the landscape is of great interest to biologists, owing to a critical need to understand the connectivity of disparate habitats for species that undertake broadscale movements. Indeed, habitat quality and quantity are thought to be important drivers of occurrence and distribution, and numerous studies have demonstrated fitness-related consequences as evidenced in global population declines for both non-migratory and migratory species. Despite the interest, however, we often lack sufficient detail about habitat use, where often general location and activity information are unavailable yet essential for management.
Traditional extrinsic markers, such as tags and bands, have proven to be rather ineffective due to low returns. Intrinsic markers, such as stable isotopes, on the other hand offer greater potential because inference is not constrained by recapture. Indeed, the use of stable isotopes has led to important findings about habitat use within the spatial domain, including the location of wintering/breeding grounds and the connectivity of those habitats through the lens of life history.
Yet, isotope-inferred biogeographic assessment, while cost effective, often yields coarse spatial resolution and is best used for inference in a probability of origin framework. The commercialization of geolocator and satellite/GPS tags and collars are becoming more widely used owing to improved cost effectiveness, miniaturization, convenient recovery schemes, and high spatial data density. Importantly, these next generation extrinsic markers of wildlife movement are actually complementary to isotope-based approaches and offer a means of ground-truthing biogeographic inference while also offering improved spatial and temporal resolution. Limited electronic tag deployment in tandem with stable isotope analysis of wildlife tissues can in fact be an ideal study design that is very cost effective, yields stronger inference, and offers an improved weight of evidence via application of multiple techniques that afford error estimation and propagation.
Geology, Geophysics, and Geochemistry Stable Isotope Laboratory (GSIL)
The distribution of species across the landscape is of great interest to biologists, owing to a critical need to understand the connectivity of disparate habitats for species that undertake broadscale movements. Indeed, habitat quality and quantity are thought to be important drivers of occurrence and distribution, and numerous studies have demonstrated fitness-related consequences as evidenced in global population declines for both non-migratory and migratory species. Despite the interest, however, we often lack sufficient detail about habitat use, where often general location and activity information are unavailable yet essential for management.
Traditional extrinsic markers, such as tags and bands, have proven to be rather ineffective due to low returns. Intrinsic markers, such as stable isotopes, on the other hand offer greater potential because inference is not constrained by recapture. Indeed, the use of stable isotopes has led to important findings about habitat use within the spatial domain, including the location of wintering/breeding grounds and the connectivity of those habitats through the lens of life history.
Yet, isotope-inferred biogeographic assessment, while cost effective, often yields coarse spatial resolution and is best used for inference in a probability of origin framework. The commercialization of geolocator and satellite/GPS tags and collars are becoming more widely used owing to improved cost effectiveness, miniaturization, convenient recovery schemes, and high spatial data density. Importantly, these next generation extrinsic markers of wildlife movement are actually complementary to isotope-based approaches and offer a means of ground-truthing biogeographic inference while also offering improved spatial and temporal resolution. Limited electronic tag deployment in tandem with stable isotope analysis of wildlife tissues can in fact be an ideal study design that is very cost effective, yields stronger inference, and offers an improved weight of evidence via application of multiple techniques that afford error estimation and propagation.