Hierarchical analysis of species distributions and abundance across environmental gradients.
Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Traditional statistical models that ignore autocorrelation and spatial hierarchies can result in misidentification of important ecological covariates. Here, we demonstrate the utility of a hierarchical modeling framework for testing hypotheses about the importance of abiotic factors at different spatial scales and local spatial autocorrelation for shaping species distributions and abundances. For the two orchid species studied, understory light availability and soil moisture helped to explain patterns of presence and abundance at a microsite scale (<4 m2), while soil organic content was important at a population scale (<400 m2). The inclusion of spatial autocorrelation is shown to alter the magnitude and certainty of estimated relationships between abundance and abiotic variables, and we suggest that such analysis be used more often to explore the relationships between species life histories and distributions. The hierarchical modeling framework is shown to have great potential for elucidating ecological relationships involving abiotic and biotic processes simultaneously at multiple scales.
Diez
Jeffrey M
JM
Institute of Ecology, University of Georgia, Athens, Georgia 30602, USA. diezj@lincoln.ac.nz
Pulliam
H Ronald
HR
D001499:Bayes Theorem; D017753:Ecosystem; D004777:Environment; D029595:Orchidaceae / Q000254:growth & development / Q000502:physiology*; D011157:Population Dynamics; D011158:Population Growth; D012987:Soil / Q000032:analysis*; D013045:Species Specificity; D013269:Stochastic Processes; D013472:Sunlight
D012987:Soil