Christopher A. Custer, Douglas P. Fischer, Geoffrey Smith, Aaron Henning, Megan Kepler Schall, Matthew K. Shank, Timothy A. Wertz, Tyler Wagner
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引用次数: 0
Abstract
Lotic fish species distributions are frequently predicted using remotely sensed habitat variables that characterize the adjacent landscape and serve as proxies for instream habitat. Recent advancements in statistical methodology, however, allow for leveraging fish assemblage data when predicting distributions. This is important because assemblage composition likely provides better information about instream habitat compared to landscape-derived metrics and therefore may improve predictions. To better understand the value of using multi-species fish data in species distribution modeling, we fit two conditional random fields (CRF) models to quantify the relative importance of fish assemblage co-occurrence, landscape-derived habitat variables, and interactions between these two predictor groups (i.e., effects of co-occurrence could be context-dependent) at over 1200 stream catchments in Pennsylvania, USA. We first compared predictive performance of CRF models against traditionally used single-species logistic regressions (generalized linear models; GLMs) and found that inclusion of fish assemblage data often improved predictive performance. The multi-species CRF models performed significantly better at predicting occurrence for 63% of species with an average percent increase in AUC of 25% compared to GLMs. Furthermore, the CRF identified species co-occurrences as more informative, and thus relatively more important, at predicting occurrence than the other effect types. The CRF also suggested that allowing these biotic effects to be context-dependent was important for predicting occurrence of many species. These findings illustrate the value of fish assemblage data for landscape-scale species distribution modeling and leveraging this information can improve predictions and inferences to help inform the management and conservation of freshwater fishes.
期刊介绍:
Community Ecology, established by the merger of two ecological periodicals, Coenoses and Abstracta Botanica was launched in an effort to create a common global forum for community ecologists dealing with plant, animal and/or microbial communities from terrestrial, marine or freshwater systems. Main subject areas: (i) community-based ecological theory; (ii) modelling of ecological communities; (iii) community-based ecophysiology; (iv) temporal dynamics, including succession; (v) trophic interactions, including food webs and competition; (vi) spatial pattern analysis, including scaling issues; (vii) community patterns of species richness and diversity; (viii) sampling ecological communities; (ix) data analysis methods.