Introduction 2 Methods 4 Search criteria 4 Statistical analyses and graphical outputs 4 Results 5 Discussion 10 Data limitations and considerations 10 Spatial scale 11 Abstract Adoption of the ecosystem approach to fisheries management relies on recognition of the link between fish and other components of the ecosystem, namely their physical and biological habitat. However, identifying the habi...

a r t i c l e i n f o In the present study, classification trees (CTs) and support vector machines (SVMs) were used to study habitat suitability for 30 macroinvertebrate taxa in the Du river in Northern Vietnam. The presence/absence of the 30 most common macroinvertebrate taxa was modelled based on 21 physical-chemical and structural variables. The predictive performance of the CT and SVM model...

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining ...

Introduction: Huemul (Hippocamelus bisulcus Molina) is the most threatened flag species of Southern Patagonia, where conservation efforts were not effective to avoid the retraction of its distribution area. Habitat quality modeling can assist to design better management strategies for regional conservation planning. The objective was to elaborate one habitat suitability map for huemul, defining...

in the present study, classification trees (cts-j48 algorithm) were used to study the occurrence of roach in rivers in flanders (belgium). the presence/absence of roach was modelled based on a set of river characteristics. the predictive performance of the cts models was assessed based on the percentage of correctly classified instances (cci) and cohen's kappa statistics. to find the best model...

Previous research indicated that high predictive performance in species distribution modelling can be obtained by combining both biotic and abiotic habitat variables. However, models developed for fish often only address physical habitat characteristics, thus omitting potentially important biotic factors. Therefore, we assessed the impact of biotic variables on fish habitat preferences in four ...