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Understanding the factors underpinning species abundance patterns in space and time is essential to implement effective cave conservation actions. Yet, the methods employed to monitor cave biodiversity still lack standardization, and no quantitative assessment has yet tried to optimize the amount and type of information required to efficiently identify disturbances in cave ecosystems. Using a comprehensive monitoring dataset for tropical iron caves, comprising abundance measurements for 33 target taxa surveyed across 95 caves along four years, here we provide the first evidence-based recommendations to optimize monitoring programs seeking to follow target species abundance through time. We found that seasonality did not influence the ability to detect temporal abundance trends. However, in most species, abundance estimates assessed during the dry season resulted in a more accurate detection of temporal abundance trends, and at least three surveys were required to identify global temporal abundance trends. Finally, we identified a subset of species that could potentially serve as short-term disturbance indicators. Results suggest that iron cave monitoring programs implemented in our study region could focus sampling efforts in the dry season, where detectability of target species is higher, while assuring data collection for at least three years. More generally, our study reveals the importance of long-term cave monitoring programs for detecting possible disturbances in subterranean ecosystems, and for using the generated information to optimize future monitoring efforts.

The degradation of subterranean habitats is believed to represent a serious threat for the conservation of obligate subterranean dwellers (troglobites), many of which are short-range endemics. However, while the factors influencing cave biodiversity remain largely unknown, the influence of the surrounding landscape and patterns of subterranean connectivity of terrestrial troglobitic communities have never been systematically assessed. Using spatial statistics to analyze the most comprehensive speleological database yet available for tropical caves, we first assess the influence of iron cave characteristics and the surrounding landscape on troglobitic communities from the Eastern Amazon. We then determine the spatial pattern of troglobitic community composition, species richness, phylogenetic diversity, and the occurrence of frequent troglobitic species, and finally quantify how different landscape features influence the connectivity between caves. Our results reveal the key importance of habitat amount, guano, water, lithology, geomorphology, and elevation in shaping iron cave troglobitic communities. While mining within 250 m from the caves influenced species composition, increasing agricultural land cover within 50 m from the caves reduced species richness and phylogenetic diversity. Troglobitic species composition, species richness, phylogenetic diversity, and the occurrence of frequent troglobites showed spatial autocorrelation for up to 40 km. Finally, our results suggest that the conservation of cave clusters should be prioritized, as geographic distance was the main factor determining connectivity between troglobitic communities. Overall, our work sheds important light onto one of the most overlooked terrestrial ecosystems, and highlights the need to shift conservation efforts from individual caves to subterranean habitats as a whole.