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. 2025 Aug;21(8):20250151.
doi: 10.1098/rsbl.2025.0151. Epub 2025 Aug 13.

Late Pleistocene faunal community patterns disrupted by Holocene human impacts

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Late Pleistocene faunal community patterns disrupted by Holocene human impacts

Barry W Brook et al. Biol Lett. 2025 Aug.

Abstract

We analysed fossil mammal assemblages from over 350 Late Pleistocene and Holocene sites worldwide to test whether human activities, such as agriculture, domestication and intensified land use, restructured global patterns of mammal co-occurrence. Using presence-absence data, we contrasted a novel iterative 'chase clustering' method, which is compositionally driven, against a traditional spatially constrained Ward's clustering approach. Both methods recovered continental-scale groupings in the Pleistocene, consistent with known biogeographic boundaries. Holocene land use and domestication reconfigured these historical patterns, creating novel assemblages independent of previous biogeographic constraints. Faunal turnover at the local scale varied substantially across regions, being especially pronounced in the Americas, whereas other areas showed relative stability. Even moderate expansion of domesticates altered how communities grouped, highlighting their disproportionate ecological influence. Our findings demonstrate that human-driven niche modification, beyond earlier megafaunal extinctions, profoundly reshaped mammal communities on a global scale. Recognizing these anthropogenic legacies provides essential context for anticipating how current and future human pressures might further transform biodiversity.

Keywords: Holocene; agriculture; biogeography; clustering; domestication; faunal turnover; mammal communities; zooarchaeology.

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Conflict of interest statement

We declare we have no competing interests.

Figures

Schematic of the ‘chase clustering’ algorithm, which uses compositional overlap in ecological communities to identify and refine cluster assignments.
Figure 1.
Schematic of the ‘chase clustering’ algorithm, which uses compositional overlap in ecological communities to identify and refine cluster assignments. First, sites with insufficient data are filtered out, then clusters are seeded from weighted samples. Unassigned sites join their most similar cluster. The algorithm shuffles assignments iteratively to maximize compositional coherence, retaining the best solution after multiple starts.
Late Quaternary mammal site clusters
Figure 2.
Late Quaternary mammal site clusters. Left column: Ward’s geography-weighted clustering (α = 0.31). Right column: composition-only chase clustering (γ = −0.10). Rows show datasets: Late Pleistocene (top), Holocene Wild taxa only (middle), Holocene Wild + domesticates (bottom). Colours denote cluster IDs within each row (IDs differ between rows). Ward’s six largely continental clusters change little across epochs, reflecting its spatial constraint. Chase clusters are similar to Ward in the Pleistocene but realign in the Holocene, especially when domesticates are included, highlighting compositional turnover that is not driven by geographic proximity.
Regional‐level faunal turnover from the Late Pleistocene to the Holocene at 34 multi‐site locations
Figure 3.
Regional‐level faunal turnover from the Late Pleistocene to the Holocene at 34 multi‐site locations. Domesticated species are included in Holocene locations. Circles represent proportional species turnover (losses or gains); warmer colours (red) indicate higher turnover, and cooler colours (blue/purple) indicate lower turnover. The variability highlights regionally distinct responses to human and environmental pressures.

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