Time-travelling pathogens and their risk to ecological communities.

Permafrost thawing and the potential 'lab leak' of ancient microorganisms generate risks of biological invasions for today's ecological communities, including threats to human health via exposure to emergent pathogens. Whether and how such 'time-travelling' invaders could establish in modern communities is unclear, and existing data are too scarce to test hypotheses. To quantify the risks of time-travelling invasions, we isolated digital virus-like pathogens from the past records of coevolved artificial life communities and studied their simulated invasion into future states of the community. We then investigated how invasions affected diversity of the free-living bacteria-like organisms (i.e., hosts) in recipient communities compared to controls where no invasion occurred (and control invasions of contemporary pathogens). Invading pathogens could often survive and continue evolving, and in a few cases (3.1%) became exceptionally dominant in the invaded community. Even so, invaders often had negligible effects on the invaded community composition; however, in a few, highly unpredictable cases (1.1%), invaders precipitated either substantial losses (up to -32%) or gains (up to +12%) in the total richness of free-living species compared to controls. Given the sheer abundance of ancient microorganisms regularly released into modern communities, such a low probability of outbreak events still presents substantial risks. Our findings therefore suggest that unpredictable threats so far confined to science fiction and conjecture could in fact be powerful drivers of ecological change.

Long-term changes in temperate marine fish assemblages are driven by a small subset of species.

The species composition of plant and animal assemblages across the globe has changed substantially over the past century. How do the dynamics of individual species cause this change? We classified species into seven unique categories of temporal dynamics based on the ordered sequence of presences and absences that each species contributes to an assemblage time series. We applied this framework to 14,434 species trajectories comprising 280 assemblages of temperate marine fishes surveyed annually for 20 or more years. Although 90% of the assemblages diverged in species composition from the baseline year, this compositional change was largely driven by only 8% of the species' trajectories. Quantifying the reorganization of assemblages based on species shared temporal dynamics should facilitate the task of monitoring and restoring biodiversity. We suggest ways in which our framework could provide informative measures of compositional change, as well as leverage future research on pattern and process in ecological systems.

Random placement models explain species richness and dissimilarity of frog assemblages within Atlantic Forest fragments.

Understanding the effects of random versus niche-based processes on biodiversity patterns is a central theme in ecology, and an important tool for predicting effects of habitat loss and fragmentation on biodiversity. We investigated the predictive power of random processes to explain species richness and species dissimilarity of amphibian assemblages in a fragmented tropical landscape of the Atlantic Forest of South America. We analyzed a large database of amphibian abundance and occupancy, sampled in 21 forest fragments ranging in size from 1.9 to 619 ha. We compared observed species richness and species dissimilarity with the outcomes of two null (random placement) models: 1- the traditional Coleman's area-based model and 2- an abundance-based model (based on the number of individuals observed in each fragment). We applied these models for all species combined, and separately for forest-dependent and habitat-generalist species. The abundance-based model fitted the observed species richness data better than the area-based model for all species, forest-dependent species, and generalist species. The area-based and the abundance-based models were also able to significantly explain species dissimilarity for all species and for generalists, but not for forest dependent species. The traditional area-based model assigned too many individuals to large fragments, thus failing to accurately explain species richness within patches across the landscape. Although niche-based processes may be important to structuring the regional pool of species in fragmented landscapes, our results suggest that part of the variation in species richness and species dissimilarity can be successfully explained by random placement models, especially for generalist species. Evaluating which factors cause variation in the number of individuals among patches should be a focus in future studies aiming to understand biodiversity patterns in fragmented landscapes.

Compreender os efeitos de processos aleatórios versus processos baseados em nicho nos padrões de biodiversidade é um tema central em ecologia e uma ferramenta importante para prever os efeitos da perda e fragmentação de habitat na biodiversidade. Nós investigamos o poder preditivo de processos aleatórios para explicar a riqueza e a dissimilaridade de espécies de assembleias de anfíbios em uma paisagem fragmentada tropical da Mata Atlântica da América do Sul. Analisamos um grande conjunto de dados de abundância e ocupação de anfíbios, amostrados em 21 fragmentos florestais com tamanhos de 1.9 a 619 ha. Comparamos a riqueza e a dissimilaridade de espécies observadas com os resultados de dois modelos nulos (posicionamento aleatório): 1- o modelo tradicional baseado em área de Coleman e 2 - um modelo baseado em abundância (com base no número de indivíduos observados em cada fragmento). Aplicamos esses modelos para todas as espécies combinadas e separadamente para espécies dependentes de floresta e espécies generalistas de habitat. O modelo baseado em abundância ajustou-se melhor aos dados observados de riqueza de espécies do que o modelo baseado em área para todas as espécies, espécies dependentes de floresta e espécies generalistas. Os modelos baseados em área e em abundância também foram capazes de explicar significativamente a dissimilaridade de espécies para todas as espécies e para generalistas, mas não para espécies dependentes de floresta. O modelo tradicional baseado em área atribuiu muitos indivíduos a grandes fragmentos, falhando assim em explicar com precisão a riqueza de espécies dentro de manchas na paisagem. Embora processos baseados em nicho possam ser importantes para estruturar o conjunto regional de espécies em paisagens fragmentadas, nossos resultados sugerem que parte da variação na riqueza e dissimilaridade de espécies pode ser explicada com sucesso por modelos de posicionamento aleatório, especialmente para espécies generalistas. Avaliar quais fatores causam variação no número de indivíduos entre manchas deve ser um foco em estudos futuros que visem compreender os padrões de biodiversidade em paisagens fragmentadas.

Holocene shifts in the assembly of plant and animal communities implicate human impacts.

Understanding how ecological communities are organized and how they change through time is critical to predicting the effects of climate change. Recent work documenting the co-occurrence structure of modern communities found that most significant species pairs co-occur less frequently than would be expected by chance. However, little is known about how co-occurrence structure changes through time. Here we evaluate changes in plant and animal community organization over geological time by quantifying the co-occurrence structure of 359,896 unique taxon pairs in 80 assemblages spanning the past 300 million years. Co-occurrences of most taxon pairs were statistically random, but a significant fraction were spatially aggregated or segregated. Aggregated pairs dominated from the Carboniferous period (307 million years ago) to the early Holocene epoch (11,700 years before present), when there was a pronounced shift to more segregated pairs, a trend that continues in modern assemblages. The shift began during the Holocene and coincided with increasing human population size and the spread of agriculture in North America. Before the shift, an average of 64% of significant pairs were aggregated; after the shift, the average dropped to 37%. The organization of modern and late Holocene plant and animal assemblages differs fundamentally from that of assemblages over the past 300 million years that predate the large-scale impacts of humans. Our results suggest that the rules governing the assembly of communities have recently been changed by human activity.

Clockwise and counterclockwise hysteresis characterize state changes in the same aquatic ecosystem.

Incremental increases in a driver variable, such as nutrients or detritus, can trigger abrupt shifts in aquatic ecosystems that may exhibit hysteretic dynamics and a slow return to the initial state. A model system for understanding these dynamics is the microbial assemblage that inhabits the cup-shaped leaves of the pitcher plant Sarracenia purpurea. With enrichment of organic matter, this system flips within three days from an oxygen-rich state to an oxygen-poor state. In a replicated greenhouse experiment, we enriched pitcher-plant leaves at different rates with bovine serum albumin (BSA), a molecular substitute for detritus. Changes in dissolved oxygen (DO) and undigested BSA concentration were monitored during enrichment and recovery phases. With increasing enrichment rates, the dynamics ranged from clockwise hysteresis (low), to environmental tracking (medium), to novel counter-clockwise hysteresis (high). These experiments demonstrate that detrital enrichment rate can modulate a diversity of hysteretic responses within a single aquatic ecosystem, and suggest different management strategies may be needed to mitigate the effects of high vs. low rates of detrital enrichment.

Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation.

Progressive habitat transformation causes global changes in landscape biodiversity patterns, but can be hard to quantify. Rarefaction/extrapolation approaches can quantify within-habitat biodiversity, but may not be useful for cases in which one habitat type is progressively transformed into another habitat type. To quantify biodiversity patterns in such transformed landscapes, we use Hill numbers to analyse individual-based species abundance data or replicated, sample-based incidence data. Given biodiversity data from two distinct habitat types, when a specified proportion of original habitat is transformed, our approach utilises a proportional mixture of two within-habitat rarefaction/extrapolation curves to analytically predict biodiversity changes, with bootstrap confidence intervals to assess sampling uncertainty. We also derive analytic formulas for assessing species composition (i.e. the numbers of shared and unique species) for any mixture of the two habitat types. Our analytical and numerical analyses revealed that species unique to each habitat type are the most important determinants of landscape biodiversity patterns.

A balance of winners and losers in the Anthropocene.

Scientists disagree about the nature of biodiversity change. While there is evidence for widespread declines from population surveys, assemblage surveys reveal a mix of declines and increases. These conflicting conclusions may be caused by the use of different metrics: assemblage metrics may average out drastic changes in individual populations. Alternatively, differences may arise from data sources: populations monitored individually, versus whole-assemblage monitoring. To test these hypotheses, we estimated population change metrics using assemblage data. For a set of 23 241 populations, 16 009 species, in 158 assemblages, we detected significantly accelerating extinction and colonisation rates, with both rates being approximately balanced. Most populations (85%) did not show significant trends in abundance, and those that did were balanced between winners (8%) and losers (7%). Thus, population metrics estimated with assemblage data are commensurate with assemblage metrics and reveal sustained and increasing species turnover.

Trade-Offs in Cold Resistance at the Northern Range Edge of the Common Woodland Ant Aphaenogaster picea (Formicidae).

Geographic variation in low temperatures at poleward range margins of terrestrial species often mirrors population variation in cold resistance, suggesting that range boundaries may be set by evolutionary constraints on cold physiology. The northeastern woodland ant Aphaenogaster picea occurs up to approximately 45°N in central Maine. We combined presence/absence surveys with classification tree analysis to characterize its northern range limit and assayed two measures of cold resistance operating on different timescales to determine whether and how marginal populations adapt to environmental extremes. The range boundary of A. picea was predicted primarily by temperature, but low winter temperatures did not emerge as the primary correlate of species occurrence. Low summer temperatures and high seasonal variability predicted absence above the boundary, whereas high mean annual temperature (MAT) predicted presence in southern Maine. In contrast, assays of cold resistance across multiple sites were consistent with the hypothesis of local cold adaptation at the range edge: among populations, there was a 4-min reduction in chill coma recovery time across a 2° reduction in MAT. Baseline resistance and capacity for additional plastic cold hardening shifted in opposite directions, with hardening capacity approaching zero at the coldest sites. This trade-off between baseline resistance and cold-hardening capacity suggests that populations at range edges may adapt to colder temperatures through genetic assimilation of plastic responses, potentially constraining further adaptation and range expansion.

Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities.

Because biodiversity is multidimensional and scale-dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale-dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity - species richness - was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale-dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi-dimensional and multi-scale perspective informs the responses of biodiversity to ecological drivers.

Bi-dimensional null model analysis of presence-absence binary matrices.

Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either "random" or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the "Tuning Peg" algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be "tuned" in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices.

Deciphering the enigma of undetected species, phylogenetic, and functional diversity based on Good-Turing theory.

Estimating the species, phylogenetic, and functional diversity of a community is challenging because rare species are often undetected, even with intensive sampling. The Good-Turing frequency formula, originally developed for cryptography, estimates in an ecological context the true frequencies of rare species in a single assemblage based on an incomplete sample of individuals. Until now, this formula has never been used to estimate undetected species, phylogenetic, and functional diversity. Here, we first generalize the Good-Turing formula to incomplete sampling of two assemblages. The original formula and its two-assemblage generalization provide a novel and unified approach to notation, terminology, and estimation of undetected biological diversity. For species richness, the Good-Turing framework offers an intuitive way to derive the non-parametric estimators of the undetected species richness in a single assemblage, and of the undetected species shared between two assemblages. For phylogenetic diversity, the unified approach leads to an estimator of the undetected Faith's phylogenetic diversity (PD, the total length of undetected branches of a phylogenetic tree connecting all species), as well as a new estimator of undetected PD shared between two phylogenetic trees. For functional diversity based on species traits, the unified approach yields a new estimator of undetected Walker et al.'s functional attribute diversity (FAD, the total species-pairwise functional distance) in a single assemblage, as well as a new estimator of undetected FAD shared between two assemblages. Although some of the resulting estimators have been previously published (but derived with traditional mathematical inequalities), all taxonomic, phylogenetic, and functional diversity estimators are now derived under the same framework. All the derived estimators are theoretically lower bounds of the corresponding undetected diversities; our approach reveals the sufficient conditions under which the estimators are nearly unbiased, thus offering new insights. Simulation results are reported to numerically verify the performance of the derived estimators. We illustrate all estimators and assess their sampling uncertainty with an empirical dataset for Brazilian rain forest trees. These estimators should be widely applicable to many current problems in ecology, such as the effects of climate change on spatial and temporal beta diversity and the contribution of trait diversity to ecosystem multi-functionality.

Estimates of local biodiversity change over time stand up to scrutiny.

We present new data and analyses revealing fundamental flaws in a critique of two recent meta-analyses of local-scale temporal biodiversity change. First, the conclusion that short-term time series lead to biased estimates of long-term change was based on two errors in the simulations used to support it. Second, the conclusion of negative relationships between temporal biodiversity change and study duration was entirely dependent on unrealistic model assumptions, the use of a subset of data, and inclusion of one outlier data point in one study. Third, the finding of a decline in local biodiversity, after eliminating post-disturbance studies, is not robust to alternative analyses on the original data set, and is absent in a larger, updated data set. Finally, the undebatable point, noted in both original papers, that studies in the ecological literature are geographically biased, was used to cast doubt on the conclusion that, outside of areas converted to croplands or asphalt, the distribution of biodiversity trends is centered approximately on zero. Future studies may modify conclusions, but at present, alternative conclusions based on the geographic-bias argument rely on speculation. In sum, the critique raises points of uncertainty typical of all ecological studies, but does not provide an evidence-based alternative interpretation.

A global database of ant species abundances.

What forces structure ecological assemblages? A key limitation to general insights about assemblage structure is the availability of data that are collected at a small spatial grain (local assemblages) and a large spatial extent (global coverage). Here, we present published and unpublished data from 51 ,388 ant abundance and occurrence records of more than 2,693 species and 7,953 morphospecies from local assemblages collected at 4,212 locations around the world. Ants were selected because they are diverse and abundant globally, comprise a large fraction of animal biomass in most terrestrial communities, and are key contributors to a range of ecosystem functions. Data were collected between 1949 and 2014, and include, for each geo-referenced sampling site, both the identity of the ants collected and details of sampling design, habitat type, and degree of disturbance. The aim of compiling this data set was to provide comprehensive species abundance data in order to test relationships between assemblage structure and environmental and biogeographic factors. Data were collected using a variety of standardized methods, such as pitfall and Winkler traps, and will be valuable for studies investigating large-scale forces structuring local assemblages. Understanding such relationships is particularly critical under current rates of global change. We encourage authors holding additional data on systematically collected ant assemblages, especially those in dry and cold, and remote areas, to contact us and contribute their data to this growing data set.

Modulation of the heat shock response is associated with acclimation to novel temperatures but not adaptation to climatic variation in the ants Aphaenogaster picea and A. rudis.

Ecological diversification into thermally divergent habitats can push species toward their physiological limits, requiring them to accommodate temperature extremes through plastic or evolutionary changes that increase persistence under the local thermal regime. One way to withstand thermal stress is to increase production of heat shock proteins, either by maintaining higher baseline abundance within cells or by increasing the magnitude of induction in response to heat stress. We evaluated whether environmental variation was associated with expression of three heat shock protein genes in two closely-related species of woodland ant, Aphaenogaster picea and A. rudis. We compared adult workers from colonies collected from 25 sites across their geographic ranges. Colonies were maintained at two different laboratory temperatures, and tested for the independent effects of environment, phylogeny, and acclimation temperature on baseline and heat-induced gene expression. The annual maximum temperature at each collection site (Tmax) was not a significant predictor of either baseline expression or magnitude of induction of any of the heat shock protein genes tested. A phylogenetic effect was detected only for basal expression of Hsp40, which was lower in the most southern populations of A. rudis and higher in a mid-range population of possible hybrid ancestry. In contrast, a higher acclimation temperature significantly increased baseline expression of Hsc70-4, and increased induction of Hsp40 and Hsp83. Thus, physiological acclimation to temperature variation appears to involve modulation of the heat shock response, whereas other mechanisms are likely to be responsible for evolutionary shifts in thermal performance associated with large-scale climate gradients.

The evolution of heat shock protein sequences, cis-regulatory elements, and expression profiles in the eusocial Hymenoptera.

BACKGROUND: The eusocial Hymenoptera have radiated across a wide range of thermal environments, exposing them to significant physiological stressors. We reconstructed the evolutionary history of three families of Heat Shock Proteins (Hsp90, Hsp70, Hsp40), the primary molecular chaperones protecting against thermal damage, across 12 Hymenopteran species and four other insect orders. We also predicted and tested for thermal inducibility of eight Hsps from the presence of cis-regulatory heat shock elements (HSEs). We tested whether Hsp induction patterns in ants were associated with different thermal environments. RESULTS: We found evidence for duplications, losses, and cis-regulatory changes in two of the three gene families. One member of the Hsp90 gene family, hsp83, duplicated basally in the Hymenoptera, with shifts in HSE motifs in the novel copy. Both copies were retained in bees, but ants retained only the novel HSE copy. For Hsp70, Hymenoptera lack the primary heat-inducible orthologue from Drosophila melanogaster and instead induce the cognate form, hsc70-4, which also underwent an early duplication. Episodic diversifying selection was detected along the branch predating the duplication of hsc70-4 and continued along one of the paralogue branches after duplication. Four out of eight Hsp genes were heat-inducible and matched the predictions based on presence of conserved HSEs. For the inducible homologues, the more thermally tolerant species, Pogonomyrmex barbatus, had greater Hsp basal expression and induction in response to heat stress than did the less thermally tolerant species, Aphaenogaster picea. Furthermore, there was no trade-off between basal expression and induction. CONCLUSIONS: Our results highlight the unique evolutionary history of Hsps in eusocial Hymenoptera, which has been shaped by gains, losses, and changes in cis-regulation. Ants, and most likely other Hymenoptera, utilize lineage-specific heat inducible Hsps, whose expression patterns are associated with adaptive variation in thermal tolerance between two ant species. Collectively, our analyses suggest that Hsp sequence and expression patterns may reflect the forces of selection acting on thermal tolerance in ants and other social Hymenoptera.

Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant species.

BACKGROUND: The distributions of species and their responses to climate change are in part determined by their thermal tolerances. However, little is known about how thermal tolerance evolves. To test whether evolutionary extension of thermal limits is accomplished through enhanced cellular stress response (enhanced response), constitutively elevated expression of protective genes (genetic assimilation) or a shift from damage resistance to passive mechanisms of thermal stability (tolerance), we conducted an analysis of the reactionome: the reaction norm for all genes in an organism's transcriptome measured across an experimental gradient. We characterized thermal reactionomes of two common ant species in the eastern U.S, the northern cool-climate Aphaenogaster picea and the southern warm-climate Aphaenogaster carolinensis, across 12 temperatures that spanned their entire thermal breadth. RESULTS: We found that at least 2 % of all genes changed expression with temperature. The majority of upregulation was specific to exposure to low temperatures. The cool-adapted A. picea induced expression of more genes in response to extreme temperatures than did A. carolinensis, consistent with the enhanced response hypothesis. In contrast, under high temperatures the warm-adapted A. carolinensis downregulated many of the genes upregulated in A. picea, and required more extreme temperatures to induce down-regulation in gene expression, consistent with the tolerance hypothesis. We found no evidence for a trade-off between constitutive and inducible gene expression as predicted by the genetic assimilation hypothesis. CONCLUSIONS: These results suggest that increases in upper thermal limits may require an evolutionary shift in response mechanism away from damage repair toward tolerance and prevention.

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.