Predicted changes in the functional structure of earthworm assemblages in France driven by climate change

Comparative Analysis of Bacterial Community Structures in Earthworm Skin, Gut, and Habitat Soil across Typical Temperate Forests

Earthworms are essential components in temperate forest ecosystems, yet the patterns of change in earthworm-associated microbial communities across different temperate forests remain unclear. This study employed high-throughput sequencing technology to compare bacterial community composition and structure in three earthworm-associated microhabitats (skin, gut, and habitat soil) across three typical temperate forests in China, and investigated the influence of environmental factors on these differential patterns. The results indicate that: (1) From warm temperate forests to cold temperate forests, the soil pH of the habitat decreased significantly. In contrast, the physicochemical properties of earthworm skin mucus exhibited different trends compared to those of the habitat soil. (2) Alpha diversity analysis revealed a declining trend in Shannon indices across all three microhabitats. (3) Beta diversity analysis revealed that the transition from warm temperate deciduous broad-leaved forest to cold temperate coniferous forest exerted the most significant impact on the gut bacterial communities of earthworms, while its influence on the skin bacterial communities was comparatively less pronounced. (4) Actinobacteria and Proteobacteria were the predominant phyla in earthworm skin, gut, and habitat soil, but the trends in bacterial community composition differed among the three microhabitats. (5) Mantel tests revealed significant correlations between bacterial community structures and climatic factors, physicochemical properties of earthworm habitat soil, and physicochemical properties of earthworm skin mucus. The findings of this study offer novel perspectives on the interplay between earthworms, microorganisms, and the environment within forest ecosystems.

Effects of climate on the distribution and conservation of commonly observed European earthworms

Belowground biodiversity distribution does not necessarily reflect aboveground biodiversity patterns, but maps of soil biodiversity remain scarce because of limited data availability. Earthworms belong to the most thoroughly studied soil organisms and-in their role as ecosystem engineers-have a significant impact on ecosystem functioning. We used species distribution modeling (SDMs) and available data sets to map the spatial distribution of commonly observed (i.e., frequently recorded) earthworm species (Annelida, Oligochaeta) across Europe under current and future climate conditions. First, we predicted potential species distributions with commonly used models (i.e., MaxEnt and Biomod) and estimated total species richness (i.e., number of species in a 5 × 5 km grid cell). Second, we determined how much the different types of protected areas covered predicted earthworm richness and species ranges (i.e., distributions) by estimating the respective proportion of the range area. Earthworm species richness was high in central western Europe and low in northeastern Europe. This pattern was mainly associated with annual mean temperature and precipitation seasonality, but the importance of predictor variables to species occurrences varied among species. The geographical ranges of the majority of the earthworm species were predicted to shift to eastern Europe and partly decrease under future climate scenarios. Predicted current and future ranges were only poorly covered by protected areas, such as national parks. More than 80% of future earthworm ranges were on average not protected at all (mean [SD] = 82.6% [0.04]). Overall, our results emphasize the urgency of considering especially vulnerable earthworm species, as well as other soil organisms, in the design of nature conservation measures.

Biodiversity modeling advances will improve predictions of nature's contributions to people

Accurate predictions of ecosystem functions and nature's contributions to people (NCP) are needed to prioritize environmental protection and restoration in the Anthropocene. However, our ability to predict NCP is undermined by approaches that rely on biophysical variables and ignore those describing biodiversity, which have strong links to NCP. To foster predictive mapping of NCP, we should harness the latest methods in biodiversity modeling. This field advances rapidly, and new techniques with promising applications for predicting NCP are still underutilized. Here, we argue that employing recent advances in biodiversity modeling can enhance the accuracy and scope of NCP maps and predictions. This enhancement will contribute significantly to the achievement of global objectives to preserve NCP, for both the present and an unpredictable future.