Naturally time-averaged accumulations of skeletal remains—death assemblages—provide reliable, albeit temporally coarse, information on the species composition and structure of communities in diverse settings, and their mismatch with local living communities usually signals recent human-driven ecological change. Here, we present the first test of live–dead mismatch as an indicator of human stress using ostracodes. On three islands along a gradient of human population density in the Bahamas, we compared the similarity of living and death assemblages in 10 lakes with relatively low levels of human stress to live–dead similarity in 11 physically comparable lakes subject to industrial, agricultural, or other human activities currently or in the past. We find that live–dead agreement in pristine lakes is consistently excellent, boding well for using death assemblages in modern-day and paleolimnological biodiversity assessments. In most comparison of physically similar paired lakes, sample-level live–dead mismatch in both taxonomic composition and species’ rank abundance is on average significantly greater in the stressed lakes; live–dead agreement is not lower in all samples from stressed lakes, but is more variable. When samples are pooled for lake-level and island-level comparisons, stressed lakes still yield lower live–dead agreement, but the significance of the difference with pristine lakes decreases—species that occur dead-only (or alive-only) in one sample are likely to occur alive (or dead) in other samples. Interisland differences in live–dead agreement are congruent with, but not significantly correlated with, differences in human population density. This situation arises from heterogeneity in the timing and magnitudes of stresses and in the extent of poststress recovery. Live–dead mismatch in ostracode assemblages thus may be a reliable indicator of human impact at the sample level with the potential to be a widely applicable tool for identifying impacted habitats and, perhaps, monitoring the progress of their recovery.

We are living in a time of rapid biodiversity loss. Numerous studies have shown that modern extinction rates are higher than pre-human background rates. However, these studies of biodiversity decline almost exclusively focus on large vertebrates. The scientific community lacks the sufficient long-term records necessary to track biodiversity loss for many invertebrate taxa. However, aquatic, benthic, and skeletonized invertebrates have the advantage of leaving a long-term record that can readily be sampled in conjunction with living communities because the mineralized skeletons accumulate in the very same sediments in which the animals that produced them once lived. These not-quite-fossil “death assemblages” contain an underutilized record for long-term monitoring. Here, we leverage three case studies of calcareous micro- and macro-faunal remains from three aquatic environments spanning two gradients: freshwater to fully marine and polluted to pristine and remediated. We compared the death assemblages to living assemblages in these case studies using Spearman’s rho and the Jaccard–Chao agreement to determine the degree of fidelity. Death assemblages of lacustrine, calcareous microcrustaceans (Ostracoda), collected from lakes in The Bahamas and Wisconsin, USA, faithfully record human impacts, both for degradation and remediation, as determined by a mismatch in the live–dead comparisons. Likewise, the live–dead comparisons of calcareous marine macrofauna (Bivalvia) from the southern California shelf also indicate human impact, including pollution and remediation. These case studies demonstrate how death assemblages can be used to gauge the changes in community assembly and population structures at local and regional scales, even in the absence of a systemic monitoring program. Conservation, restoration, and biomonitoring efforts would benefit from the inclusion of live–dead comparisons of taxa with easily fossilized, identifiable parts. Live–dead studies, such as those presented in these case studies, can be used as tools for recognizing targets and establishing baselines for conservation, tracking community responses to remediation efforts, and identifying local species extinctions.