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Aim: Addressing global environmental challenges requires access to biodiversity data across wide spatial, temporal and taxonomic scales. Availability of such data has increased exponentially recently with the proliferation of biodiversity databases. However, heterogeneous coverage, protocols, and standards have hampered integration among these databases. To stimulate the next stage of data integration, here we present a synthesis of major databases, and investigate (a) how the coverage of databases varies across taxonomy, space, and record type; (b) what degree of integration is present among databases; (c) how integration of databases can increase biodiversity knowledge; and (d) the barriers to database integration. Location: Global. Time period: Contemporary. Major taxa studied: Plants and vertebrates. Methods: We reviewed 12 established biodiversity databases that mainly focus on geographic distributions and functional traits at global scale. We synthesized information from these databases to assess the status of their integration and major knowledge gaps and barriers to full integration. We estimated how improved integration can increase the data coverage for terrestrial plants and vertebrates. Results: Every database reviewed had a unique focus of data coverage. Exchanges of biodiversity information were common among databases, although not always clearly documented. Functional trait databases were more isolated than those pertaining to species distributions. Variation and potential incompatibility of taxonomic systems used by different databases posed a major barrier to data integration. We found that integration of distribution databases could lead to increased taxonomic coverage that corresponds to 23 years’ advancement in data accumulation, and improvement in taxonomic coverage could be as high as 22.4% for trait databases. Main conclusions: Rapid increases in biodiversity knowledge can be achieved through the integration of databases, providing the data necessary to address critical environmental challenges. Full integration across databases will require tackling the major impediments to data integration: taxonomic incompatibility, lags in data exchange, barriers to effective data synchronization, and isolation of individual initiatives.

Energy is life’s main currency. Understanding the requirements, flow, and availability of energy among organisms then becomes synonym for our understanding of the sustainability of biodiversity. In this regard, metabolic scaling and coexistence theories have been pivotal in mathematizing the energy consumption by an organism and the energy transformation across organisms, respectively. Yet, a simple formal integration of these theories has remained overdue. Here, we provide a tractable and scalable framework to link metabolic scaling relationships at the population level and the persistence of ecological communities under different environmental conditions. Specifically, this framework focuses on exploring the dependence of community feasibility on body size. This integration predicts that the exponent defining the dependence of pairwise interaction effects on body sizes, but not the distribution of body sizes itself, is linked to the optimal distribution of environmental carrying capacities compatible with community persistence. Additionally, this integration predicts that the compatibility between community persistence and distributions of environmental carrying capacities is maximized when interaction effects are homogeneous across all pairs of interacting populations. We believe this integration can open up new opportunities to increase our understanding of how metabolic scaling relationships at the population level have evolved to optimize process at the community level.

Cushion plants are specialized keystone species of alpine environments that can have a positive effect on ecosystem structure and function. However, we know relatively little about how cushion plants regulate the diversity and composition of soil microbial communities, major drivers of soil processes and ecosystem functioning. Identifying what factors drive the diversity and composition of soil microbial communities in high-elevation ecosystems is also fundamental to predict how global changes will affect their conservation and the services and functions they provide. Thus, we sampled four sites along the southern Andes following the vegetation belt of Azorella cushion species. The field sites spread along a latitudinal gradient and had contrasting levels of aridity, UV-B radiation, mean temperature and soil properties. Overall, Azorella, as well as aridity and UV-B radiation, were the major drivers of the distribution, composition and diversity of soil microbial communities in the studied ecosystems of the Chilean Andes. UV-B radiation affected particularly soil fungi, while soil properties such as pH, total C and N content, essential predictors of microbial diversity globally, had a much lower effect on the composition of soil microbial communities. Understanding the factors driving the structure and composition of microbial communities, particularly the role of cushion plants and the feedbacks between plant, climate and soil is of uttermost importance for the preservation of the functionality of high-elevation ecosystems threatened by climate change.

We propose a stochastic model for interacting species in a metacommunity in order to study the factors affecting the intensity of the competition/colonization trade-off as a coexistence mechanism in metacommunities. We particularly focus on the role of the number of local communities and the number of refuges for the inferior competitor. The stochastic component is associated with the dispersal process and is represented by Poisson random measures. Thus, this stochastic model includes two dynamic scales: a continuous one, which refers to the interactions among species, and a low frequency one, referring to dispersal following a Poisson scheme. We show the well-posedness of the model and that it is possible to study its long-term behavior using Lyapunov exponents; the extinction of a species is associated with a negative slope in the time trajectory of the Lyapunov exponent, otherwise, it is equal to zero. We show that the competition/colonization trade-off is a function of the dispersal rate of the inferior competitor, and that it becomes less intense as the number of local communities increases, while the opposite is true with an increase in the number of refuges for the inferior competitor. We also show that under a priority effect type of scenario, dispersal can reverse priority effects and generate coexistence. Our results emphasize the importance of coexistence mechanisms related to the topology of the system of local communities, and its relationship with dispersal, in affecting the result of competition in local communities.

At present, there is no simple, first principles–based, and general model for quantitatively describing the full range of observed biological temperature responses. Here we derive a general theory for temperature dependence in biology based on Eyring–Evans–Polanyi’s theory for chemical reaction rates. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence of enzyme reaction rates which takes the form of an exponential function modified by a power law and that describes the characteristic asymmetric curved temperature response. Based on a few additional principles, our model can be used to predict the temperature response above the enzyme level, thus spanning quantum to classical scales. Our theory provides an analytical description for the shape of temperature response curves and demonstrates its generality by showing the convergence of all temperature dependence responses onto universal relationships—a universal data collapse—under appropriate normalization and by identifying a general optimal temperature, around 25 ∘ C, characterizing all temperature response curves. The model provides a good fit to empirical data for a wide variety of biological rates, times, and steady-state quantities, from molecular to ecological scales and across multiple taxonomic groups (from viruses to mammals). This theory provides a simple framework to understand and predict the impact of temperature on biological quantities based on the first principles of thermodynamics, bridging quantum to classical scales.

Aim Many pinniped species have experienced drastic demographic changes due to their interaction with humans. Most studies, however, have failed to detect recent bottlenecks in otariids from genetic data. The South American Sea Lion Otaria flavescens have a long history of population changes associated with interglacial expansion and hunting to almost extinction. This study aimed at investigating these different demographic fluctuations integrating population genetics and phylogeographic approaches. Location Pacific coast of South America. Methods Eighty-five samples from the Chilean coast were collected. Eight microsatellite loci were genotyped, and D-Loop mitochondrial DNA (mtDNA) sequenced. Genetic diversity was assessed, and tests of recent genetic bottlenecks were performed. Past demographic changes were inferred based on neutrality tests, adjustment of a sudden expansion model and Bayesian skyline plots. The magnitude and timing of the different population size changes were further investigated through approximate Bayesian computation (ABC) of coalescent inferences. Results The mtDNA shows relatively high diversity (h = 0.98 and π = 0.01) compared to most otariids, corroborates the divergence between Pacific and Atlantic populations, around 80,000 years ago (ya), and revealed a secondary contact zone in the Magellan strait. Microsatellite data support a second genetic discontinuity at 40°S, associated with post-glacial colonization of Patagonia. ABC analyses confirmed that glaciation affected the effective population size (Ne) all along the Pacific Coast, between ~50,000 and 15,000 ya. A strong reduction of Ne was also inferred for the hunting period (73–66 ya from sampling). Main conclusions O. flavescens shows clear signatures of susceptibility to climatic and anthropogenic disturbances and a spatial genetic structure that should be taken into account in the context of management and conservation policies. Yet, despite a recent history of demographic bottlenecks, the genetic diversity remains high, likely a consequence of the demographic dynamics in otariids, characterized by large and connected metapopulations.

In recently deglaciated soils, microbial organisms drive soil transformations by increasing carbon (C) and nitrogen (N) pools while depleting available phosphorous (P), thus improving plant colonization and soil development. However, the rate of soil development can vary in response to local environmental conditions that affect microbial abundance and activity. In this contribution we use observational and experimental approaches to evaluate the interplay between soil biogeochemical features and microbial abundance and function after approximately seventy years of soil development in the forefield of the Exploradores Glacier that is located at the northernmost end of the Northern Patagonian Ice Field. Our findings suggest that after approximately seventy years of soil development, microbial abundance and soil C and N accumulation increase with soil age, soil bulk density and pH decreased, and microbial activity measured as soil chlorophyll a and nifH gene abundance increased. In turn, decomposition increased with fungal abundance, showing higher values in the late stages of soil development where the soil C:N ratio was higher and soil pH was lower. Overall, biogeochemical changes along this chronosequence followed the predicted pattern, with gradual increases in soil nutrients and microbial abundance, in addition to decomposition processes.

Aim: Mediterranean Chile is part of the five recognized mediterranean-type climates in the world and harbours a very rich floral diversity. Climate change has been reported as a significant threat to its biodiversity. We used the flora of Mediterranean Chile to analyse how biodiversity patterns, as measured by phylogenetic diversity, genus and species richness will respond to climate change scenarios and identify the areas that will harbour the greatest evolutionary potential and biodiversity richness. We also evaluated how these spatial patterns are depicted within the current network of protected areas. Location: Chilean Mediterranean climate-type Region, South America. Methods: Biodiversity metrics were evaluated for current and future climatic scenarios. Species distribution models were done using Maxent for 1.727 species and 571 genera. Relationships between species/genera gain, loss and turnover were evaluated. For Mediterranean endemic species, loss and gain were also related to life-form. Finally, variation in species gain, loss and turnover was evaluated in future climate change scenarios within and outside Mediterranean Chile state protected areas. Results: We found a general decrease in species richness in the entire Region towards future climate change scenarios. Phylogenetic diversity is predicted to be higher than expected by richness in the north–south of the area and lower than expected by richness in the Andes Mountain. The highest average species and genus loss is predicted to occur outside the protected areas; meanwhile, species and genus gain is higher within them. Main conclusions: Future biodiversity patterns are reported here for the first time in the Chilean Mediterranean Region. Our findings enhance the importance of the current protected areas to harbour this future variation, despite their reduced number and size along the region.

Phenology of species, the coupling of vital activities to specific times of the year, plays a main role in ecosystem functioning and is expected to be affected by global change. We analysed the temporal structure of 52 amphibian communities in South America encompassing a latitudinal range from 7o to 34o south. Phenological modularity – species tendencies to aggregate along the months – is here introduced as a ubiquitous property of biodiversity architecture. Further, we identified an increase in phenological modularity with species richness, available energy and in communities with lower thermal dependence (i.e. the rate of change in the number of species active along the year associated with the environmental temperature). These patterns are in agreement with predictions derived from several ecological hypotheses: complexity‐stability, species‐energy and metabolic ecology. However, no direct association between modularity and the phylogenetic structure of communities was observed. A structural equation model that outperformed all the plausible alternative models considered supports these results. Modularity is reported here as a main feature of the phenology of communities that depends on environmental conditions. Here, we report for the first time a putative connection between community species richness and the degree of temporal structure – phenological modularity; the thermal dependence shows that communities at low latitudes are more vulnerable to climate change; energetic environments also promote communities with phenological modularity; and latitudinal patterns of phylogenetic community structure can give us clues of which species would be important to the conservation of community processes. These results call for further theoretical analyses to support the connection between phenological modularity, community stability and vulnerability to global change.

Many multi-regional studies investigating how available habitat area, energy availability, and historical refugia drive freshwater fish diversity have emphasized Northern Hemisphere and tropical areas. Furthermore, while many such studies have examined diversity drivers on basin-scale species richness (i.e., gamma diversity), they typically have not evaluated beta diversity or phylogenetic diversity nor included representative numbers of Southern Hemisphere basins unassociated with tropical rainforests. Here, we examine 784 basins and present the first comprehensive evaluation of the driving effects of gamma diversity and the patterns of beta and phylogenetic diversity across extra-tropical Southern Hemisphere (ETSH) freshwater fish communities. We find that ETSH gamma diversity does not show a strong historical legacy associated with glaciations, and is influenced more by factors related with habitat area and available energy. Additionally, ETSH regions show high beta and phylogenetic diversity and low levels of diadromy, except New Zealand, which shows narrow species diversity and cosmopolitan species dominance. Finally, phylogenetic diversity indicates how the endemism of the three ETSH Mediterranean-climate regions is characteristic of long-term isolation and persistence. These results demonstrate ETSH freshwater fish diversity to be distinct from both the tropics and their Northern Hemisphere latitudinal counterparts.

At present, there is no simple, complete, and first principles-based model for quantitatively describing the full range of observed biological temperature responses. Here, we derive a theory exhibiting these features based on the Eyring-Evans-Polanyi theory governing chemical reaction rates, and which is applicable across all scales from the micro to the macro. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence which takes the form of an exponential function modified by a power-law. Our framework leads to six deductions applicable to any biological trait that depends on temperature, and elucidates novel aspects of universal temperature responses across the tree of life, from quantum to classical scales. All predictions are well supported by data for a wide variety of biological rates and steady states, from molecular to ecological scales and across multiple taxonomic groups. In addition, we provide novel explanations of several empirical relationships including optimal values in temperature response curves.One-Sentence SummaryWe derive a simple and universal formulae to characterize temperature responses of biological processes across the tree of life.

Urban socioeconomics and mortality Santiago, Chile, is a highly segregated city with distinct zones of affluence and deprivation. This setting offers a window on how social factors propel the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in an economically vulnerable society with high levels of income inequality. Mena et al. analyzed incidence and mortality attributed to SARS-CoV-2 to understand spatial variations in disease burden. Infection fatality rates were higher in lower-income municipalities because of comorbidities and lack of access to health care. Disparities between municipalities in the quality of their health care delivery system became apparent in testing delays and capacity. These indicators explain a large part of the variation in COVID-19 underreporting and deaths and show that these inequalities disproportionately affected younger people. Science, abg5298, this issue p. eabg5298, The consequences of health care inequalities have been exacerbated during the SARS-CoV-2 pandemic in a large, economically vulnerable city., INTRODUCTION The COVID-19 crisis has exposed major inequalities between communities. Understanding the societal risk factors that make some groups particularly vulnerable is essential to ensure more effective interventions for this and future pandemics. Here, we focus on socioeconomic status as a risk factor. Although it is broadly understood that social and economic inequality has a negative impact on health outcomes, the mechanisms by which socioeconomic status affects disease outcomes remain unclear. These mechanisms can be mediated by a range of systemic structural factors, such as access to health care and economic safety nets. We address this gap by providing an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. RATIONALE Combining publicly available data sources, we conducted a comprehensive analysis of case incidence and mortality during the first wave of the pandemic. We correlated COVID-19 outcomes with behavioral and health care system factors while studying their interaction with age and socioeconomic status. To overcome the intrinsic biases of incomplete case count data, we used detailed mortality data. We developed a parsimonious Gaussian process model to study excess deaths and their uncertainty and reconstructed true incidence from the time series of deaths with a new regularized maximum likelihood deconvolution method. To estimate infection fatality rates by age and socioeconomic status, we implemented a hierarchical Bayesian model that adjusts for reporting biases while accounting for incompleteness in case information. RESULTS We find robust associations between COVID-19 outcomes and socioeconomic status, based on health and behavioral indicators. Specifically, we show in lower–socioeconomic status municipalities that testing was almost absent early in the pandemic and that human mobility was not reduced by lockdowns as much as it was in more affluent locations. Test positivity and testing delays were much higher in these locations, indicating an impaired capacity of the health care system to contain the spread of the epidemic. We also find that 73% more deaths than in a normal year were observed between May and July 2020, and municipalities at the lower end of the socioeconomic spectrum were hit the hardest, both in relation to COVID-19–attributed deaths and excess deaths. Finally, the socioeconomic gradient of the infection fatality rate appeared particularly steep for younger age groups, reflecting worse baseline health status and limited access to health care in municipalities with low socioeconomic status. CONCLUSION Together, these findings highlight the substantial consequences of socioeconomic and health care disparities in a highly segregated city and provide practical methodological approaches useful for characterizing the COVID-19 burden and mortality in other urban centers based on public data, even if reports are incomplete and biased. Effect of socioeconomic inequalities on COVID-19 outcomes. The map on the left shows the municipalities that were included in this study, colored by their socioeconomic status score. For the comparison between COVID-19 deaths and excess deaths (top right), COVID-19–confirmed deaths are shown in light green and COVID-19–attributed deaths in dark green. Excess deaths, shown in gray, correspond to the difference between observed and predicted deaths. Predicted deaths were estimated using a Gaussian process model. The shading indicates 95% credible intervals for the excess deaths. The infection fatality rates (bottom right) were inferred by implementing a hierarchical Bayesian model, with vertical lines representing credible intervals by age and socioeconomic status., The COVID-19 pandemic has affected cities particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. Our analyses show a strong association between socioeconomic status and both COVID-19 outcomes and public health capacity. People living in municipalities with low socioeconomic status did not reduce their mobility during lockdowns as much as those in more affluent municipalities. Testing volumes may have been insufficient early in the pandemic in those places, and both test positivity rates and testing delays were much higher. We find a strong association between socioeconomic status and mortality, measured by either COVID-19–attributed deaths or excess deaths. Finally, we show that infection fatality rates in young people are higher in low-income municipalities. Together, these results highlight the critical consequences of socioeconomic inequalities on health outcomes.

Top-down and bottom-up forces determine ecosystem function and dynamics. Fisheries as a top-down force can shorten and destabilize food webs, while effects driven by climate change can alter the bottom-up forces of primary productivity. We assessed the response of a highly-resolved intertidal food web to these two global change drivers, using network analysis and bioenergetic modelling. We quantified the relative importance of artisanal fisheries as another predator species, and evaluated the independent and combined effects of fisheries and changes in plankton productivity on food web dynamics. The food web was robust to the loss of all harvested species but sensitive to the decline in plankton productivity. Interestingly, fisheries dampened the negative impacts of decreasing plankton productivity on non-harvested species by reducing the predation pressure of harvested consumers on non-harvested resources, and reducing the interspecific competition between harvested and non-harvested basal species. In contrast, the decline in plankton productivity increased the sensitivity of harvested species to fishing by reducing the total productivity of the food web. Our results show that strategies for new scenarios caused by climate change are needed to protect marine ecosystems and the wellbeing of local communities dependent on their resources.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Top-down and bottom-up forces determine ecosystem function and dynamics. Fisheries as a top-down force can shorten and destabilize food-webs, while climate-change driven effects can alter the bottom-up forces of primary productivity. We assessed the response of a highly-resolved intertidal food-web to these two global-change drivers, using network analysis and bioenergetic modelling. We quantified the relative importance of artisanal fisheries as another predator species, and evaluated the independent and combined effects of fisheries and plankton-productivity changes on food-web dynamics. The food-web was robust to the loss of all harvested species but sensible to plankton-productivity decline. Interestingly, fisheries dampened the negative impacts of decreasing plankton productivity on non-harvested species, while plankton-productivity decline increased the sensitivity of harvested species to fishing. Our results show that strategies for new scenarios caused by climate change are needed to protect marine ecosystems and the wellbeing of local communities dependent on their resources.

Earth’s biosphere is currently undergoing drastic reorganisation as a consequence of the sixth mass extinction brought on by the Anthropocene. Impacts of local and regional extirpation of species have been demonstrated to propagate through the complex interaction networks they are part of, subsequently leading to secondary extinctions, exacerbating biodiversity loss. Contemporary ecological theory has developed several measures to analyse the structure and robustness of ecological networks under biodiversity loss. However, a toolbox for direct simulation and quantification of extinction cascades and the creation of novel interactions (i.e. rewiring) remains absent.Here, we presentNetworkExtinction- a novel R package which we have developed to explore the propagation of species extinctions sequences through ecological networks as well as quantify the effects of rewiring potential in response to primary species extinctions. WithNetworkExtinctionwe have integrated ecological theory and computational simulations to develop functionality with which users may analyze and visualize the structure and robustness of ecological networks. The core functions introduced withNetworkExtinctionfocus on simulations of sequential primary extinctions and associated secondary extinctions while allowing for user-specified secondary extinction thresholds and realisation of rewiring potential.With the packageNetworkExtinction,users can estimate the robustness of ecological networks after performing species extinction routines based on several algorithms. Moreover, users can compare the number of simulated secondary extinctions against a null model of random extinctions. In-built visualizations enable graphing topological indices calculated by the deletion sequence functions after each simulation step. Finally, the user can define the degree distribution of the network by fitting different common distributions. Here, we illustrate the use of the package and its outputs by analyzing a Chilean coastal marine food web.NetworkExtinctionis a compact and easy-to-use R package with which users can quantify changes in ecological network structure in response to different patterns of species loss, thresholds, and rewiring potential. Therefore, this package is particularly useful to evaluate ecosystem responses to anthropogenic and environmental perturbations that produce non-random species extinctions.

Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post-2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from

Ecosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the diversity of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the network structure of ecosystems from time series of species abundance, but it is not clear how well can networks be reconstructed, especially in the presence of stochasticity that propagates through ecological networks. We evaluate the effects of intrinsic noise and network topology on the performance of different methods of inferring network structure from time-series data. Analysis of seven different four-species motifs using a stochastic model demonstrates that star-shaped motifs are differentially detected by these methods while rings are differentially constructed. The ability to reconstruct the network is unaffected by the magnitude of stochasticity in the population dynamics. Instead, interaction between the stochastic and deterministic parts of the system determines the path that the whole system takes to equilibrium and shapes the species covariance. We highlight the effects of long transients on the path to equilibrium and suggest a path forward for developing more ecologically sound statistical techniques.

The Neolithic or Formative Period in the New World drastically transformed the mode of production in human societies with the domestication of plants and animals. It impacted the way of life and social relations among individuals in permanent farming villages. Moreover, the emergence of elites and social inequality fostered interpersonal and inter- and intra-group violence associated with the defense of resources, socio-economic investments, and other cultural concerns. This study evaluated violence among the first horticulturalists in the Atacama Desert in northern Chile during the Neolithic transition between 1000 BCE – 600 CE. Furthermore, it analyzed trauma caused by interpersonal violence using a sample of 194 individuals. Strontium isotopic composition was examined to determine whether violence was local or among foreign parties. Settlement patterns, weapons, and rock art also were evaluated to assess expressions of violence. Skeletal and soft tissues presented the most direct evidence for violence. About 21% (n = 40) of adult individuals, particularly men, showed trauma compatible with interpersonal violence, with 50% (n = 20) of trauma appearing fatal. The findings suggested that violence was between local groups and that social and ecological constraints likely triggered violence within local communities.

Understanding how human societies interacted with environmental changes is a major goal of archaeology and other socio-natural sciences. In this paper, we assess the human-environment interactions in the Pampa del Tamarugal (PDT) basin of the Atacama Desert over the last 13,000 years. By relying on a socio-environmental model that integrates ecosystem services with adaptive strategies, we review past climate changes, shifting environmental conditions, and the continuities and discontinuities in the nature and intensity of the human occupation of the PDT. As a result we highlight the importance of certain key resources such as water, an essential factor in the long-term trajectory of eco-historical change. Without water the outcome of human societies becomes hazardous.

Summary During soil development, bacteria and fungi can be differentially affected by changes in soil biogeochemistry. Since the chemistry of parent material affects soil pH, nutrient availability, and indirectly litter quality, we hypothesize that parent material has an important influence on microbial community patterns during long-term soil development. In this paper, we tested for the effect of parent material, as well as, soil and litter properties upon microbial community patterns in three c. 20 000-year-old semi-arid chronosequences developed on sedimentary and volcanic (i.e. Andesitic and Dacitic) soils in the Dry Puna of Bolivia. We evaluated microbial patterns by analysing the terminal restriction fragment length polymorphism from amplified bacterial 16S rRNA genes, and the fungal internal transcribed spacer region, and quantitative real-time polymerase chain reaction. Soil and litter characteristics differed significantly between the Sedimentary and volcanic chronosequences. In particular, soil pH was alkaline in all stages of the Sedimentary chronosequence; whereas it changed from alkaline to near neutral across stages in both volcanic chronosequences. Composition of bacterial communities changed across volcanic chronosequences, and this change was associated with a reduction in soil pH and increases in litter quality, whereas no differences were found in the Sedimentary chronosequence. Fungal community composition, in contrast, did not change across any chronosequence. Relative microbial abundance, expressed as the fungal:bacterial ratio, declined across stages of the Sedimentary chronosequence in association with decreases in TC and TP, whereas in the Andesitic chronosequence decreases in fungal:bacterial ratios were related with increases in litter quality and declines in soil pH. Synthesis. Our results show the importance of parent material in affecting bacterial and fungal communities during soil development. Further, in semi-arid chronosequences, fungal:bacterial ratios tend to decline given that soil pH in young soils is rather alkaline. Our results also are consistent with the general framework that highlights the importance of above-ground (i.e. litter quality) and below-ground (i.e. soil properties) in affecting microbial relative abundance and community composition during soil development.

In the context of the metabolic theory of ecology (MTE), the activation energy (E) reflects the temperature dependence of metabolism and organism performance in different activities, such as calling behavior. In this contribution we test the role of temperature in affecting local amphibian community structure, particularly the number of species engaged in calling behavior across a temperature gradient. Toward this aim, we compiled phenological calling activity for 52 Neotropical anuran communities. For each community we estimated the activation energy of calling behavior (E), finding values significantly higher than previous reports. A wide range of methodological issues with the potential to produce overestimated E-values were shown to have no significant effect on reported E-values, supporting a biological interpretation of their high values and of geographic trends. Further, a path analysis related variation in E among communities with communities’ phylogenetic structure, local environmental conditions, richness, and seasonality. The decrease of activation energy at higher latitudes and less productive environments suggests that amphibians’ activity could become more dependent of internal individuals’ resources once external sources are reduced. The increase in phylogenetic attraction with latitude points to a rise in the role of niche conservatism and community filtering operating over conserved traits. Finally, flexibility in activation energy related to amphibians’ calling could be an important and poorly recognized determinant of their thermal dependence. The temporal structuring of amphians’ communities was related here with the interplay between ecological and evolutionary processes operating at different scales. Our results support the view of activation energy as an important parameter of biodiversity organization, which unravels the effects of ecological and evolutionary processes on biodiversity structure and function.

Chile was one of many countries that initiated environmental impact assessments in the 1990s, and has relied on their use for species conservation and territorial planning without the use of larger-scale environmental and ecological planning. The capacity of Chile's environmental impact assessment system (SEIA) to evaluate resident freshwater fishes and the potential impacts of water projects and aquaculture activities – two categories of projects that create direct threats to freshwater fishes – are assessed. Of the 3997 such submissions to the SEIA, only 0.6% conducted any freshwater fish assessment, and only 0.1% conducted any quantitative assessment of expected impacts from the associated project. The small number of assessments was characterized by poor study design, inconsistent sampling methodology, and species misidentification. Traditional assessments failed to include freshwater fish ecology in the general assessment framework. The new strategic environmental evaluation system only underscores the need for vastly improved field sampling protocols and assessment methodologies.

The Mediterranean climate region of central Chile is rich in biodiversity and contains highly productive agricultural lands, which creates challenges for the preservation of natural habitats and native biodiversity. Ecological data and studies for the region are also limited, making informed conservation in agricultural landscapes difficult. The increasing availability of remotely sensed data provide opportunities to relate species occurrences to measures of landscape heterogeneity even when field measures of habitat structure are lacking. When working with such remotely sensed data, it’s important to select appropriate measures of heterogeneity, including common metrics of landscape composition as well as frequently overlooked shape metrics. In this contribution we combine bird surveys with multispectral satellite imagery to develop boosted regression tree models of avian species richness, and of habitat use for 15 species across a mixed vineyard-matorral landscape in central Chile. We found a range of associations between individual species and land cover types, with the majority of species occurring most frequently in remnant habitats and ecotones rather than the interiors of large vineyard blocks. Models identified both metrics of landscape composition and patch shape as being important predictors of species occurrence, suggesting that shape metrics can complement more commonly used metrics of landscape composition. Vineyards that include corridors or islands of remnant habitat among vine blocks may increase the amount of area available to many species, although some species may still require large tracts of intact natural habitat to persist.