Conservation of species and ecosystems is increasingly difficult because anthropogenic impacts are pervasive and accelerating. Under this rapid global change, maximizing conservation success requires a paradigm shift from maintaining ecosystems in idealized past states toward facilitating their adaptive and functional capacities, even as species ebb and flow individually. Developing effective strategies under this new paradigm will require deeper understanding of the long-term dynamics that govern ecosystem persistence and reconciliation of conflicts among approaches to conserving historical versus novel ecosystems. Integrating emerging information from conservation biology, paleobiology, and the Earth sciences is an important step forward on the path to success. Maintaining nature in all its aspects will also entail immediately addressing the overarching threats of growing human population, overconsumption, pollution, and climate change.
Aim To produce a spatial clustering of Europe on the basis of species occurrence data for the land mammal fauna.
Location Europe defined by the following boundaries: 11°W, 32°E, 71°N, 35°N.
Methods Presence/absence records of mammal species collected by the Societas Europaea Mammalogica with a resolution of 50 × 50 km were used in the analysis. After pre‐processing, the data provide information on 124 species in 2183 grid cells. The data were clustered using the k‐means and probabilistic expectation maximization (EM) clustering algorithms. The resulting geographical pattern of clusters was compared against climate variables and against an environmental stratification of Europe based on climate, geomorphology and soil characteristics (EnS).
Results The mammalian presence/absence data divide naturally into clusters, which are highly connected spatially and most strongly determined by the small mammals with the highest grid cell incidence. The clusters reflect major physiographic and environmental features and differ significantly in the values of basic climate variables. The geographical pattern is a fair match for the EnS stratification and is robust between non‐overlapping subsets of the data, such as trophic groups.
Main conclusions The pattern of clusters is regarded as reflecting the spatial expression of biologically distinct, metacommunity‐like entities influenced by deterministic forces ultimately related to the physical environment. Small mammals give the most spatially coherent clusters of any subgroup, while large mammals show stronger relationships to climate variables. The spatial pattern is mainly due to small mammals with high grid cell incidence and is robust to noise from other subsets. The results support the use of spatially resolved environmental reconstructions based on fossil mammal data, especially when based on species with the highest incidence.
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