Model-based integration of observed and expert-based information for assessing the geographic and environmental distribution of freshwater species

  • Domisch S
  • Wilson A
  • Jetz W
  • 55


    Mendeley users who have this article in their library.
  • 6


    Citations of this article.


Freshwater ecosystems harbor specialized and vulnerable biodiversity, and the prediction of potential impacts of freshwater biodiversity to environmental change requires knowledge of the geographic and environmental distribution of taxa. To date, however, such quantitative information about freshwater species distributions remains limited. Major impediments include heterogeneity in available species occurrence data, varying detectability of species in their aquatic environment, scarcity of contiguous freshwater-specifi c predictors, and methods that support addressing these issues in a single frame- work. Here we demonstrate the use of a hierarchical Bayesian modeling (HBM) framework that combines disparate species occurrence information with newly-developed 1 km freshwater-specifi c predictors, to account for imperfect species detec- tion and make fi ne-grain (1 km) estimates of distributions in freshwater organisms. Th e approach integrates a Bernoulli suitability and a Binomial observability process into a hierarchical zero-infl ated Binomial model. Th e suitability process includes point presence observations, records of site visits, 1 km environmental predictors and expert-derived species range maps integrated with a distance-decay function along the within-stream distance as covariates. Th e observability process uses repeated observations to estimate a probability of observation given that the species was present. Th e HBM accounts for the spatial autocorrelation in species habitat suitability projections using an intrinsic Gaussian conditional autoregres- sive model. We used this framework for three fi sh species native to diff erent regions and habitats in North America. Model comparison shows that HBMs signifi cantly outperformed non-spatial GLMs in terms of AUC and TSS scores, and that expert information when appropriately included in the model can provide an important refi nement. Such ancillary species information and an integrative, hierarchical Bayesian modeling framework can therefore be used to advance fi ne-grain habitat suitability predictions and range size estimates in the freshwater realm. Our approach is extendable in terms of data availability and generality and can be used on other freshwater organisms and regions. Freshwater

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Sami Domisch

  • Adam M. Wilson

  • Walter Jetz

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free