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Nicolas Strebel

Publications and source records attributed to Nicolas Strebel.

2 recordsLinked to original sources

Non-native bird populations respond differently to their environment and exhibit shifts in ecological niche limits across continents

Aim The degree to which species' niches remain stable over space and time–the niche conservatism hypothesis–is critical for predicting species' responses to environmental change. Tests of this hypothesis typically focus on changes in niche centroids and boundaries. An outstanding question is whether species' environmental associations differ within the interior of their niche space–that is, across the full range of occupied conditions–in original versus novel geographic space. Location Europe and North America. Time Period 1997–2018. Major Taxa Studied Birds. Methods We used over 400,000 observations collected over 22 years and across 28 countries to explore whether two common songbird species—European starling ( Sturnus vulgaris ) and house sparrow ( Passer domesticus ) – exhibit niche conservatism between their native European and non-native North American ranges. We tested for niche conservatism via (1) an ordination approach that quantified change in niche shape and boundaries, and (2) generalised linear mixed effects models to quantify how abundance varied with the interaction between continent and climate or land cover variables. Results The ordination analysis indicated that both European starling and house sparrow exhibited niche conservatism between Europe and North America. However, abundance models revealed continental differences in how the species responded to temperature and land cover. The abundance models also revealed that areas with wetter conditions that were occupied by both species in their native European ranges were available but unoccupied in their non-native North American ranges (i.e., niche unfilling). Main Conclusions Our work demonstrates that species can exhibit apparent consistency in niche boundaries but varied abundance responses to the environment within niche boundaries. Expanding the study of niche conservatism to explore changes both at the edge of and within niche boundaries would improve the ability to assess and predict species' invasion risk or sensitivity to ongoing global change.

Diversity and Distributions

Integrated distance sampling models for simple point counts

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new “ IDS() ” function in the R package unmarked . Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Ecology