Kiesel, J. | Search bioRxiv

bioRxiv2024

Drivers of recovery and degradation of riverine benthic macroinvertebrate communities: A nationwide analysis of time series

In response to the global freshwater biodiversity crisis this study examines the drivers, influencing recovery and degradation in riverine benthic macroinvertebrate communities across Germany. Utilizing the Asymmetric Response Concept (ARC), which posits that species tolerances to stressors, dispersal capacity, and biotic interactions are critical drivers in aquatic ecosystem recovery, we analyzed a comprehensive dataset from 1568 sites, sampled between 2004 and 2022. Our findings indicate that abiotic stress consistently influences ecological status in both recovery and degradation phases. Interspecific competition shows a stronger positive relationship with ecological status improvements during recovery phases than during degradation, underscoring its importance in the recovery process. Additionally, land use intensity has a nuanced impact: catchments with higher proportions of cropland and urban areas are more likely to recover, while forested catchments are more prone to degradation. This study supports the ARC and highlights the complex interplay of biotic and abiotic variables in shaping ecological outcomes, underscoring the importance of integrated management approaches in freshwater conservation and restoration efforts.

ecology↗

bioRxiv2024

Transferability of stream benthic macroinvertebrate distribution models to drought-related conditions

Freshwater ecosystems increasingly face pressures from climate change induced extreme events, like droughts, posing significant threats to biodiversity. While Species Distribution Models (SDMs) serve as vital tools for predicting species responses to environmental shifts, their transferability to novel environmental conditions, especially during and after drought remains poorly understood. In this study, we delve into the transferability of SDMs for freshwater macroinvertebrates from drought-free to drought-influenced conditions. We examine how sensitive the transferability is to traits such as tolerance scores according to their distribution along longitudinal gradients, as well as the used modelling method. We constructed and validated SDMs for freshwater macroinvertebrates in a central German catchment under drought-free conditions using four different algorithms (Generalised linear models; GLM, Spatial Stream Networks; SSN, Random Forests; RF, and Maximum Entropy; MaxEnt). We then projected these models to environmental conditions influenced by drought, and obtained their transferability by computing the difference in accuracy when predicting under drought-free and drought-influenced conditions (AUCgap). Our findings reveal a marked reduction in SDM accuracy under drought conditions, illustrating the challenges of accurately predicting species distributions into novel environmental conditions. Our results show a slightly better transferability when using SSN and RF. In addition, we observed that SDM transferability can be influenced by species tolerance, with sensitive and tolerant species presenting higher AUCgap (i.e. lower transferability). Furthermore, we found that when sensitive species were modelled using SSNs, the AUCgap was reduced. Our study underscores the limitations of SDMs in capturing species responses to drought and advocates for integrating ecologically relevant predictors and modelling methods that account for the stream connectivity to allow for robust predictions. These considerations could enhance the ability of SDMs to effectively estimate the impacts of extreme events on freshwater biodiversity.

ecology↗