Biology subjects

Schifferle, K.

Publications and source records attributed to Schifferle, K..

3 recordsLinked to original sources

bioRxiv2026

North American bird occupancy dynamics attributed to climate and land use change

Evidence is accumulating that global change is altering species distributions. Yet, detailed knowledge is missing about the relative and joint contribution of different drivers to observed species responses. Here, we implemented an impact attribution framework based on counterfactual simulations to assess the impact of climate and land use change on occupancy dynamics of North American breeding birds. We used a Bayesian framework to fit process-explicit dynamic occupancy models to long-term survey data for 159 species from 1995 to 2019, and quantified predictive performance using spatial and temporal cross-validation. We then assessed the relative importance and effect direction of climate and land use change while accounting for model predictive accuracy. Results indicate that climate change negatively affected 90 % of the species and land use change negatively impacted 96 %. Climate change emerged as more important than land use change for driving changes in occupancy across species. Remarkably, the effects of both drivers were mostly antagonistic rather than acting additively or synergistically. Climate was the most important driver for bird communities in the western USA, while land use change dominated in the southeast, and combined climate and land use change in the northeast. Our analysis demonstrates that recent changes in North American bird distributions are shaped by multiple global change drivers acting in concert. The effect of recent climate and land use change were mostly antagonistic, and thus trends in bird occupancy dynamics could not be understood by studying the impact of those drivers in isolation. By disentangling the effects of climate and land use change on biodiversity trends, impact attribution approaches can improve our understanding of global change impacts and can support conservation planning and more accurate and realistic projections of biodiversity response to global change.

ecology↗

bioRxiv2025

Climatic niche conservatism in non-native plants depends on introduction history and biogeographic context

Many tools informing preventive invasion management build on the assumption that introduced species will conserve their climatic niches outside their native ranges. Previous research testing the validity of this assumption found contradictory results regarding niche conservatism vs. niche switching for non-native species. An open question is in how far these contradictions reflect context dependency, yet only few studies compared the niche dynamics of species introduced to multiple regions. Here, we used an ordination-based approach to quantify the climatic niche changes (stability, unfilling, expansion) of 316 plant species introduced to eight different regions across the world, including the Pacific region with extreme isolation between island groups. We then performed multiple phylogenetic regressions to assess how the regional context and species characteristics affect niche dynamics. Niche conservatism varied across regions, even within species. While niche expansion into previously unoccupied climates was generally low, niche unfilling varied strongly between regions. Generally, region-specific introduction history and species biogeographic attributes were more important for explaining niche changes than ecological traits. Niche expansion was consistently higher for species with small native range sizes, and niche stability increased. In contrast, niche unfilling decreased with time since introduction which could suggest that the lack of niche conservatism observed in many regions might be transient and potentially related to dispersal limitations. Overall, our results shed light on the context dependency of climatic niche changes when species are introduced to new regions, highlighting that the species and region-specific context should be accounted for when assessing the potential for niche changes. Significance StatementAs non-native species are introduced to new regions by humans, they may occupy the same climatic conditions as in their native ranges, leave parts of their native niche unfilled or expanding into previously unoccupied conditions. Knowing to which extent these niche dynamics generally occur is essential for understanding and managing biological invasions. Here, we evaluate regional differences in the climatic niche dynamics of non-native plants that were introduced to multiple regions across the world. We found marked variation across regions, influenced by factors such as the time that has passed since species were introduced, or biogeographic attributes of both the native and non-native ranges. These findings indicate that a lack of apparent niche changes is likely a temporary phenomenon.

ecology↗

bioRxiv2024

Uncertainty in blacklisting potential Pacific plant invaders using species distribution models

O_LIInvasive alien species pose a growing threat to global biodiversity, underscoring the need for evidence-based prevention strategies. Species distribution models (SDMs) are a widely used tool to estimate the potential distribution of alien species and to inform blacklists based on establishment risk. Yet, data limitations and modelling decisions can introduce uncertainty in these predictions. Here, we aim to quantify the contribution of four key sources of uncertainty in SDM-based blacklists: species occurrence data, environmental predictors, SDM algorithms, and thresholding methods for binarising predictions. C_LIO_LIFocusing on 82 of the most invasive plant species on the Hawaiian Islands, we built SDMs to quantify their establishment potential in the Pacific region. To assess uncertainty, we systematically varied four modelling components: species occurrence data (native vs. global), environmental predictors (climatic vs. edapho-climatic), four SDM algorithms, and three thresholding methods. From these models, we derived blacklists using three alternative blacklisting definitions and quantified the variance in establishment risk scores and resulting species rankings attributable to each source of uncertainty. C_LIO_LISDMs showed fair predictive performance overall. Among the sources of uncertainty, thresholding method had the strongest and most consistent influence on risk scores across all three blacklist definitions but resulted in only minor changes in blacklist rankings. In contrast, algorithm choice had the most pronounced effect on blacklist rankings, followed by smaller but important effects of species occurrence data and environmental predictors. Notably, models based only on native occurrences often underestimated establishment potential. C_LIO_LISDMs can provide valuable support for planning the preventive management of alien species. However, our findings show that blacklist outcomes are highly sensitive to modelling decisions. While ensemble modelling across multiple algorithms is a recommended best practice, our results reinforce the importance of incorporating global occurrence data when available and carefully evaluating the trade-offs of including additional environmental predictors. Given the strong influence of thresholding on risk scores, we emphasise the need for transparent, context-specific threshold selection. More broadly, explicitly assessing uncertainty in SDM outputs can improve the robustness of blacklists and support scientifically informed, precautionary decision-making, particularly in data-limited situations where pragmatic modelling choices must be taken. C_LI

ecology↗