Occurrence data may provide unreliable thermal preferences and breadth of species

Accurate information on the thermal preference and specialization of species is needed to understand and predict spe- cies geographical range size and vulnerability to climate change. Here we estimate the position and breadth of species within thermal gradients based on the shape of the response curve of species abundance to temperature. The objective of the study is to compare the measurements of this approach based on abundance data with those of the classical approach using species＇ occur- rence data. The relationship between species＇ relative abundance and minimum winter temperature of 106 bird species wintering in the Iberian Peninsula is modeled at 100 Km2 resolution with quadratic logistic regressions. From these models we calculated the preferred temperature of species as the temperature at which the abundance is maximized, and the thermal breadth of species as the relative area under the temperature-abundance curve. We also estimated the thermal preferences and breadth of species as the average temperature and temperature range of the UTM cells in which the species are present. The abundance-temperature response curves reveal that birds prefer higher temperatures to overwinter, and are more thermally selective, than is measured by the classical approach. Moreover, response curves detect a higher inter-specific variability in both thermal preferences and ther- mal breadth of species. As occurrence data gives the same weight to cells with one or many individuals, the average temperature of the cells in which the species is present roughly reflects the average temperature in the region of study and not the environ- mental preferences of species .

Dealing with detection error in site occupancy surveys: what can we do with a single survey?

Aim Site occupancy probabilities of target species are commonly used in various ecological studies,e.g.to monitor current status and trends in biodiversity.Detection error introduces bias in the estimators of site occupancy.Existing methods for estimating occupancy probability in the presence of detection error use replicate surveys.These methods assume population closure,i.e.the site occupancy status remains constant across surveys,and independence between surveys.We present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or independence.In place of the closure assumption,this method requires covariates that affect detection and occupancy.Methods Penalized maximum-likelihood method was used to estimate the parameters.Estimability of the parameters was checked using data cloning.Parametric boostrapping method was used for computing confidence intervals.Important Findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable,situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not met.This method saves significant amounts of time,energy and money in ecological surveys without sacrificing statistical validity.Further,we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.

Incorporating within- and between-patch resource selection in identification of critical habitat for brood-rearing greater sage-grouse

Introduction:Incorporating information on animal behavior in resource-based predictive modeling(e.g.,occurrence mapping)can elucidate the relationship between process and spatial pattern and depict habitat in terms of its structure as well as its function.In this paper,we assigned location data on brood-rearing greater sage-grouse(Centrocercus urophasianus)to either within-patch(encamped)or between-patch(traveling)behavioral modes by estimating a movement-based relative displacement index.Objectives were to estimate and validate spatially explicit models of within-versus between-patch resource selection for application in habitat management and compare these models to a non-behaviorally adjusted model.Results:A single model,the vegetation and water resources model,was most plausible for both the encamped and traveling modes,including the non-behaviorally adjusted model.When encamped,sage-grouse selected for taller shrubs,avoided bare ground,and were closer to mesic areas.Traveling sage-grouse selected for greater litter cover and herbaceous vegetation.Preference for proximity to mesic areas was common to both encamped and traveling modes and to the non-behaviorally adjusted model.The non-behaviorally adjusted map was similar to the encamped model and validated well.However,we observed different selection patterns during traveling that could have been masked had behavioral state not been accounted for.Conclusions:Characterizing habitat that structured between-patch movement broadens our understanding of the habitat needs of brood-rearing sage-grouse,and the combined raster surface offers a reliable habitat management tool that is readily amenable to application by GIS users in efforts to focus sustainable landscape management.