A canonical metacommunity structure over 3 decades: ecologically consistent but spatially dynamic patterns in a hurricane-prone montane forest

The Anthropocene is a time of rapid change induced by human activities, including pulse and press disturbances that affect the species composition of local communities and connectivity among them, giving rise to spatiotemporal dynamics at multiple scales. We evaluate effects of global warming and repeated intense hurricanes on gastropod metacommunities in montane tropical rainforests of Puerto Rico for each of 28 consecutive years. Specifically, we quantified metacommunity structure each year; assessed effects of global warming, hurricane-induced disturbance, and secondary succession on interannual variation in metacommunity structure; and evaluated legacies of previous land use on metacommunity structure. Gastropods were sampled annually during a 28-year period characterized by disturbance and succession associated with 3 major hurricanes (Hurricanes Hugo, Georges, and Maria). For each year, we evaluated coherence (the extent to which the environmental distributions of species are uninterrupted along a common latent environmental gradient), species range turnover, and species range boundary clumping; and conducted co-occurrence analyses for each pair of species. We used generalized linear mixed-effects model to evaluate long-term responses of the metacommunity to aspects of global warming and disturbance. Metacommunity structure was remarkably stable, with consistent patterns of species co-occurrence. Disturbance, warming, and successional stage had little effect on metacommunity structure. Despite great temporal variation in environmental conditions, groups of species tracked their niche through space and time to maintain the same general structure. Consequently, metacommunity structure was highly resistant and resilient to multiple disturbances, even those that greatly altered forest structure.

Refining sampling protocols for cavefishes and cave crayfishes to account for environmental variation

Subterranean habitats represent focal habitats in many conservation strategies; however, these environments are some of the most difficult to sample. New sampling methods, such as environmental DNA (eDNA), show promise to improve stygobiont detection, but sources of sampling bias are poorly understood. Therefore, we determined the factors affecting detection probability using traditional visual surveys and eDNA surveys for both cavefishes and cave crayfishes and demonstrated how detection affects survey efforts for these taxa. We sampled 40 sites (179 visual and 183 eDNA surveys) across the Ozark Highlands ecoregion. We estimated the detection probability of cave crayfishes and cavefishes using both survey methods under varying environmental conditions. The effectiveness of eDNA or visual surveys varied by environmental conditions (i.e., water volume, prevailing substrate, and water velocity) and the target taxa. When sampling in areas with average water velocity, no flow, and coarse substrate, eDNA surveys had a higher detection probability (0.49) than visual surveys (0.35) for cavefishes and visual surveys (0.67) had a higher detection probability than eDNA surveys (0.40) for cave crayfishes. Under the same sampling conditions, 5 visual surveys compared to 10 eDNA surveys would be needed to confidently detect cave crayfishes and 9 visual surveys compared to 4 eDNA surveys for cavefishes. Environmental DNA is a complementary tool to traditional visual surveys; however, the limitations we identified indicate eDNA currently cannot replace visual surveys in subterranean environments. Although sampling designs that account for imperfect sampling are particularly useful, they may not be practical; thus, increasing sampling efforts to offset known detection bias would benefit conservation strategies.

Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration

A fundamental goal of community ecology is to understand species-habitat relationships and how they shape metacommunity structure. Recent advances in occupancy modeling enable habitat relationships to be assessed for both common and rare species within metacommunities using multi-species occupancy models (MSOM). These models account for imperfect species detection and offer considerable advantages over other analytical tools commonly used for community analyses under the elements of metacommunity structure (EMS) framework. Here, we demonstrate that MSOM can be used to infer habitat relationships and test metacommunity theory, using amphibians. Repeated frog surveys were undertaken at 55 wetland sites in southeastern Australia. We detected 11 frog species from three families (Limnodynastidae, Myobatrachidae, and Pelodryadidae). The rarest species was detected at only one site whereas the most common species was detected at 42 sites (naive occupancy rate 0.02-0.76). Two models were assessed representing two competing hypotheses; the best-supported model included the covariates distance to the nearest site (connectivity), wetland area, presence of the non-native eastern mosquitofish (Gambusia holbrooki), proportion cover of emergent vegetation, an interaction term between Gambusia and emergent vegetation cover, and the proportion canopy cover over a site. Hydroperiod played no detectable role in metacommunity structure. We found species-habitat relationships that fit with current metacommunity theory: occupancy increased with wetland area and connectivity. There was a strong negative relationship between occupancy and the presence of predatory Gambusia, and a positive interaction between Gambusia and emergent vegetation. The presence of canopy cover strongly increased occupancy for several tree frog species, highlighting the importance of terrestrial habitat for amphibian community structure. We demonstrated how responses by amphibians to environmental covariates at the species level can be linked to occupancy patterns at the metacommunity scale. Our results have clear management implications: wetland restoration projects for amphibians and likely other taxa should maximize wetland area and connectivity, establish partial canopy cover, and eradicate Gambusia or provide aquatic vegetation to mitigate the impact of this non-native fish. We strongly advocate the use of MSOM to elucidate the habitat drivers behind animal occupancy patterns and to derive unbiased occupancy estimates for monitoring programs.

In transition: Avian biogeographic responses to a century of climate change across desert biomes

Transition zones between biomes, also known as ecotones, are areas of pronounced ecological change. They are primarily maintained by abiotic factors and disturbance regimes that could hinder or promote species range shifts in response to climate change. We evaluated how climate change has affected metacommunity dynamics in two adjacent biomes and across their ecotone by resurveying 106 sites that were originally surveyed for avian diversity in the early 20th century by Joseph Grinnell and colleagues. The Mojave, a warm desert, and the Great Basin, a cold desert, have distinct assemblages and meet along a contiguous, east-west boundary. Both deserts substantially warmed over the past century, but the Mojave dried while the Great Basin became wetter. We examined whether the distinctiveness and composition of desert avifaunas have changed, if species distributions shifted, and how the transition zone impacted turnover patterns. Avifauna change was characterized by (a) reduced occupancy, range contractions, and idiosyncratic species redistributions; (b) degradation of historic community structure, and increased taxonomic and climatic differentiation of the species inhabiting the two deserts; and (c) high levels of turnover at the transition zone but little range expansion of species from the warm, dry Mojave into the cooler, wetter Great Basin. Although both deserts now support more drier and warmer tolerant species, their bird communities still occupy distinct climatological space and differ significantly in climatic composition. Our results suggest a persistent transition zone between biomes contributes to limiting the redistribution of birds, and highlight the importance of understanding how transition zone dynamics impact responses to climate change.

PiSCES: Pi(scine) stream community estimation system

The Piscine Stream Community Estimation System (PiSCES) provides users with a hypothesized fish community for any stream reach in the conterminous United States using information obtained from Nature Serve, the US Geological Survey (USGS), StreamCat, and the Peterson Field Guide to Freshwater Fishes of North America for over 1000 native and non-native freshwater fish species. PiSCES can filter HUC8-based fish assemblages based on species-specific occurrence models; create a community abundance/biomass distribution by relating relative abundance to mean body weight of each species; and allow users to query its database to see ancillary characteristics of each species (e.g., habitat preferences and maximum size). Future efforts will aim to improve the accuracy of the species distribution database and refine/augment increase the occurrence models. The PiSCES tool is accessible at the EPA's Quantitative Environmental Domain (QED) website at https://qed.epacdx.net/pisces/.

Untangling the dynamics of persistence and colonization in microbial communities

A central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here, we introduce a dynamic statistical model, based on probit regression, that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data. We separate the fixed pairwise effects of species occurrences on persistence and colonization rates, a potential signal of direct interactions, from latent pairwise correlations in occurrence, a potential signal of shared environmental responses. We first validate our modeling framework with several simulation studies. Then, we apply the approach to a pressing epidemiological question by examining how human papillomavirus (HPV) types coexist. Our results suggest that while HPV types respond similarly to common host traits, direct interactions are sparse and weak, so that HPV type diversity depends largely on shared environmental drivers. Our modeling approach is widely applicable to microbial communities and provides valuable insights that should lead to more directed hypothesis testing and mechanistic modeling.

Inferences of environmental and biotic effects on patterns of eukaryotic alpha and beta diversity for the spring systems of Ash Meadows, Nevada

Freshwater springs are important ecosystems. In the arid regions of North America, groundwater extraction has caused the desiccation of springs and the extinction of taxa. To better describe the biodiversity of freshwater springs in the hope of establishing a sensitive approach for monitoring the predicted change in spring systems, we used high-resolution genetic methods to estimate the alpha and beta diversity of 19 springs and two reservoirs within the Ash Meadows National Wildlife Refuge in southwestern Nevada. We discovered a large number of distinct taxa based on eukaryote ribosomal gene sequences and show water temperature, spring size, and the presence or absence of non-native predators predicts alpha diversity, and temperature predicts beta diversity. Our study highlights how DNA data support inferences of environmental factors influencing community diversity and demonstrates the method may be an important tool for monitoring ecological communities.

Parasite metacommunities: Evaluating the roles of host community composition and environmental gradients in structuring symbiont communities within amphibians

Ecologists increasingly report the structures of metacommunities for free-living species, yet far less is known about the composition of symbiont communities through space and time. Understanding the drivers of symbiont community patterns has implications ranging from emerging infectious disease to managing host microbiomes. Using symbiont communities from amphibian hosts sampled from wetlands of California, USA, we quantified the effects of spatial structure, habitat filtering and host community components on symbiont occupancy and overall metacommunity structure. We built upon a statistical method to describe metacommunity structure that accounts for imperfect detection in survey data-detection error-corrected elements of metacommunity structure-by adding an analysis to identify covariates of community turnover. We applied our model to a metacommunity of eight parasite taxa observed in 3,571 Pacific chorus frogs (Pseudacris regilla) surveyed from 174 wetlands over 5 years. Symbiont metacommunity structure varied across years, showing nested structure in 3 years and random structure in 2 years. Species turnover was most consistently influenced by spatial and host community components. Occupancy generally increased in more southeastern wetlands, and snail (intermediate host) community composition had strong effects on most symbiont taxa. We have used sophisticated but accessible statistical methods to reveal that spatial components-which influence colonization-and host community composition-which mediates transmission-both drive symbiont community composition in this system. These methods allow us to associate broad patterns of community turnover to local, species-level effects, ultimately improving our understanding of spatial community dynamics.

Seasonality and microhabitat selection in a forest-dwelling salamander

Many small terrestrial vertebrates exhibit limited spatial movement and are considerably exposed to changes in local environmental variables. Among such vertebrates, amphibians at present experience a dramatic decline due to their limited resilience to environmental change. Since the local survival and abundance of amphibians is intrinsically related to the availability of shelters, conservation plans need to take microhabitat requirements into account. In order to gain insight into the terrestrial ecology of the spectacled salamander Salamandrina perspicillata and to identify appropriate forest management strategies, we investigated the salamander's seasonal variability in habitat use of trees as shelters in relation to tree features (size, buttresses, basal holes) and environmental variables in a beech forest in Italy. We used the occupancy approach to assess tree suitability on a non-conventional spatial scale. Our approach provides fine-grained parameters of microhabitat suitability and elucidates many aspects of the salamander's terrestrial ecology. Occupancy changed with the annual life cycle and was higher in autumn than in spring, when females were found closer to the stream in the study area. Salamanders showed a seasonal pattern regarding the trees they occupied and a clear preference for trees with a larger diameter and more burrows. With respect to forest management, we suggest maintaining a suitable number of trees with a trunk diameter exceeding 30 cm. A practice of selective logging along the banks of streams could help maintain an adequate quantity of the appropriate microhabitat. Furthermore, in areas with a presence of salamanders, a good forest management plan requires leaving an adequate buffer zone around streams, which should be wider in autumn than in spring.

Predicting cryptic links in host-parasite networks

Networks are a way to represent interactions among one (e.g., social networks) or more (e.g., plant-pollinator networks) classes of nodes. The ability to predict likely, but unobserved, interactions has generated a great deal of interest, and is sometimes referred to as the link prediction problem. However, most studies of link prediction have focused on social networks, and have assumed a completely censused network. In biological networks, it is unlikely that all interactions are censused, and ignoring incomplete detection of interactions may lead to biased or incorrect conclusions. Previous attempts to predict network interactions have relied on known properties of network structure, making the approach sensitive to observation errors. This is an obvious shortcoming, as networks are dynamic, and sometimes not well sampled, leading to incomplete detection of links. Here, we develop an algorithm to predict missing links based on conditional probability estimation and associated, node-level features. We validate this algorithm on simulated data, and then apply it to a desert small mammal host-parasite network. Our approach achieves high accuracy on simulated and observed data, providing a simple method to accurately predict missing links in networks without relying on prior knowledge about network structure.

The macroecology of infectious diseases: a new perspective on global-scale drivers of pathogen distributions and impacts

Identifying drivers of infectious disease patterns and impacts at the broadest scales of organisation is one of the most crucial challenges for modern science, yet answers to many fundamental questions remain elusive. These include what factors commonly facilitate transmission of pathogens to novel host species, what drives variation in immune investment among host species, and more generally what drives global patterns of parasite diversity and distribution? Here we consider how the perspectives and tools of macroecology, a field that investigates patterns and processes at broad spatial, temporal and taxonomic scales, are expanding scientific understanding of global infectious disease ecology. In particular, emerging approaches are providing new insights about scaling properties across all living taxa, and new strategies for mapping pathogen biodiversity and infection risk. Ultimately, macroecology is establishing a framework to more accurately predict global patterns of infectious disease distribution and emergence.