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Habitat loss represent a major threat to biodiversity, however, the modulation of their effects by the non-habitat matrix surrounding habitat patches is still undervalued. The landscape matrix might change community assembly in different ways. For example, low-quality matrices can accentuate environmental filtering by reducing resource availability and/or deteriorating abiotic conditions but they may also over limit dispersal of organisms and make communities more prone to ecological drift. To understand how matrix quality modulates the effects of habitat loss, we quantified the relative importance of environmental filter and ecological drift in bird occurrences across more local (400 m buffer around sampling sites) and broader (2 km focal landscapes) gradients of habitat loss embedded in low- and high-quality matrices. We used a trait-based approach to understand habitat loss filtering effects on forest specialist and habitat generalist bird occurrences. We found that low-quality matrices, composed mainly of low-productive pasturelands, increased the severity of habitat loss filtering effects for forest specialist birds, but only at the landscape scale. Bird occurrence was in general higher in high-quality matrices, i.e., more heterogeneous and with low-contrasting edges, indicating the role of the matrix quality on attenuating species extinction risks at the landscape scale probably due to mass effect. Moreover, forest specialists presented a strong negative response to habitat loss filtering across different functional traits, while generalists presented a high variability in traits response to habitat loss. We raised evidence in supporting that landscape habitat loss filtering may be relaxed or reinforced depending on the quality of the matrix, evidencing that matrix quality has a strong impact in modulating community assembly processes in fragmented landscapes. In practical terms, it means that improving matrix quality may help in maintaining the high diversity of birds even without any increase in native forest cover.

Food webs represent the energy fluxes and the nutrient cycling between interacting species that underpin several ecosystem functions. Whether and how interactions vary across environmental gradients is still largely unknown. We reviewed the literature searching for systematic relationships between structural food-web properties and environmental gradients. Temperature and biotic factors are amongst the most frequently addressed drivers of food-web structure. We also assessed the degree to which food-web ecology has accomplished a mechanistic understanding of ecosystem functioning. We found that most studies are one-off descriptions of local food webs making it difficult to achieve an understanding of the response to human or environmental gradients. The lack of a consistent theory predicting how food webs change across environmental gradients, the diversity of objectives in food-web studies, and the absence of a standardized methodology for analysing them severely limit progress in the field. Moving forward requires the establishment of a core set of testable predictions, agreed standards for data collection and analysis, and the development of geographically distributed experimental studies of food-web dynamics., FM, DGC, CPC, MGM, MBA were supported through the project StateShifts (ref. PTDC/AAG-MAA/3764/2014) funded by FCT, the Portuguese Foundation for Science and Technology. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731065 (AQUACOSM) and No 871081 (AQUACOSM-plus).

Dactylogyridae is one of the most studied families of parasitic flatworms with more than 1000 species and 166 genera described to date including ecto- and endoparasites. Dactylogyrid monogeneans were suggested as model organisms for host-parasite macroevolutionary and biogeographical studies due to the scientific and economic importance of some of their host lineages. Consequently, an array of phylogenetic research into different dactylogyrid lineages has been produced over the past years but the last family-wide study was published 16 years ago. Here, we provide a meta-analysis of the phylogenetic relationships of Dactylogyridae including representatives of all genera with available molecular data (n = 67). First, we investigate the systematic informativeness of morphological characters widely used to diagnose dactylogyrid genera through a parsimony analysis of the characters, character mapping, and phylogenetic comparative methods. Second, we provide an overview of the current state of the systematics of the family and its subfamilies, and summarise potentially poly- and paraphyletic genera. Third, we elaborate on the implications of taxonomic, citation, and confirmation bias in past studies. Fourth, we discuss host range, biogeographical, and freshwater-marine patterns. We found two well-supported macroclades which we assigned to the subfamilies Dactylogyrinae and Ancyrocephalinae. These subfamilies further include 16 well-supported clades with only a few synapomorphies that could be deduced from generic diagnoses in the literature. Furthermore, few morphological characters considered systematically informative at the genus level display a strong phylogenetic signal. However, the parsimony analysis suggests that these characters provide little information on the relationships between genera. We conclude that a strong taxonomic bias and low coverage of DNA sequences and regions limit knowledge on morphological and biogeographical evolutionary patterns that can be inferred from these results. We propose addressing potential citation and confirmation biases through a 'level playing field' multiple sequence alignment as provided by this study. This research was funded by Czech Science Foundation (GACˇ R) standard project GA19-13573S. N.K. (BOF21PD01), A.J.C.L. (BOF19OWB02) and M.P.M.V. (BOF20TT06) are financed by the Special Research Fund of Hasselt University, Belgium. Walter A. Boeger (Universidade Federal do Paraná, Brazil) is thanked for fruitful discussions on this matter

The pollution of freshwater ecosystems is threatening freshwater plant species diversity worldwide. Freshwater plants, such as the common duckweed (Lemna minor), are potentially sensitive to novel stressful environments. To test if ecotype diversity could increase resistance to stressful environments, I used seven L. minor populations and measured their growth rates with and without moderate salt stress across an ecotype diversity gradient. The L. minor populations were grown over 5 months in 92 experimental mesocosms, either in ecotype monocultures or in polyculture with either one or three conspecific ecotypes (23 unique compositions). After growing the duckweed in unperturbed conditions (phase 1), the cultures were subjected to moderate salt stress (50 mmol/L NaCl) for several weeks (phase 2). The experiment was conducted in the presence of the natural epimicrobial community associated with the different ecotypes. In phase 2, a subset of these algae added an unintentional second stressor to the experiment. The ecotypes differed in their growth rates, the fastest growing at twice the rate of others. The diversity context further shaped the ecotype growth rates. Ecotype polycultures showed higher abundances towards the end of the experiment, thus over time, as the environment deteriorated, ecotype diversity gained in importance. These findings show that within-species variation in growth rates can translate to a positive effect of ecotype diversity on population abundance. Exposure of L. minor to moderate salt levels did not significantly impact growth rates, although the effect may have been masked by reduced algal stress in the saline environments.

Mass releases of two parasitoid species, Aphidius matricariae and Ephedrus cerasicola, may provide an alternative measure to pesticides to control the rosy apple aphid Dysaphis plantaginea in organic apple orchards. As a proof of concept study, we tested if the presence of flower strips between apple tree rows could improve the action of three early parasitoid releases—and of other naturally present aphid enemies—on the control of aphid colonies and number of aphids per tree. Apple trees located at different distances from parasitoid release points were monitored in plots with and without flower strips in an organic apple orchard over two years, along the season of aphid infestation (March to July). Our case study demonstrated that the presence of flowering plant mixes in the alleyways of an apple orchard improved the biological control of D. plantaginea, with an effect size of 33.4% less aphids in plots with flower strips, compared to plots without flower strips, at the infestation peak date. We also showed a negative effect of higher distance to parasitoid release points on aphid control, but our results at the infestation peak date suggest that the presence of flowers could marginally compensate for the detrimental effect of distance, probably by improving the persistence and dispersal capacities of natural enemies. Despite high variations in aphid population dynamics between years, we conclude that combining flower strips with early parasitoid releases in apple orchards is promising for biological control of the rosy apple aphid, although the method merits to be further refined and repeated in more orchards.

International audience; Gorilla tourism supports the protection of its ecosystem, benefiting humans and wildlife populations living therein. Assessing to what degree the presence and proximity of tourists affect wildlife aids long-term benefits. Because wild animals might see human activities as stressors, we hypothesized that the increased presence and proximity of tourists leads to immediate changes in gorilla social cohesion. We constructed social networks from association rates before, during, and after tourist visits, and when tourists were very close (≤3 m) or close (>3 m) to them. Our analysis focused on this distance threshold (≤3 m and >3 m) because the 7 m rule, enforced by the national park, was violated 84% of the time. We showed that gorillas spent more time in closer association after tourists arrived and when tourists were

To mitigate the shortage of natural breeding sites in cities, nest-boxes are provided for cavity-nesters. However, these are not the breeding sites these animals originally evolved in and optimised their breeding performance to. It thus remains inconclusive if nest-boxes can provide adequate substitutes, ensuring equivalent fitness returns for breeding animals. Additionally, the majority of knowledge on the ecology of urban birds comes from nest-box populations, but no study to date directly compared fitness consequences of breeding inside nest-boxes in relation to natural-cavities in an urban context. This limits our understanding of the urban ecology of cavity-nesters and addressing its functional meaning. We investigate fitness consequences and life-history trait variation according to the nesting site type to provide a comprehensive understanding of conservation potential of nest-boxes in cities and to support/question generalisations stemming from nest-box studies on urbanization. We directly compare the reproductive performance of two small passerines, blue tits and great tits, breeding in nest-boxes as opposed to natural-cavities in a seminatural forest of a capital city using a quasi-experimental setting. We show that the effects of nest type vary between species: in blue tits, fitness proxies were negatively affected by nest-boxes (lower fledging success and fledgling numbers, longer time spent in nest and later fledging date in comparison to natural-cavities), while great tit performance appeared to be unaffected by nest type. We detected that both species breeding in nest-boxes accelerated incubation onset, but since there were no major differences in pre-hatching traits (lay date, clutch size, hatching rates) between the nest types, we attribute the fitness deterioration to post-hatching effects. Interestingly, overall breeding density of tits in urban natural-cavities was higher than observed in a primeval habitat. Nest-boxes may become an ecological trap for some species and the unaffected species can consequently outcompete them, decreasing overall biodiversity in cities. We highlight the ecological importance of old-growth tree stands, providing natural tree cavities for city-breeding animals. Due to the detected nest type-dependent variation in reproductive performance, we support the criticism regarding the unconditional extrapolation of evolutionary and ecological interpretations of nest-box studies to general populations.

Lineage-specific traits determine how plants interact with their surrounding environment. As different species may find similar phenotypic solutions through evolution to tolerate, persist in and invade environments with certain characteristics, some traits may become more common in certain types of habitats. These general patterns of geographical trait distribution point towards the existence of some rules in how plants diversify in space over time. Trait-environment correlation analyses are ways to discover general rules in plant biogeography by quantifying to what extent unrelated lineages have similar evolutionary responses to a given type of habitat. In this synthesis, I give a short historical overview on trait-environment correlation analyses, from some key observations from classic naturalists to modern approaches using trait evolution models, large phylogenies, and massive datasets of traits and distributions. I discuss some limitations of modern approaches, including the need for more realistic models, the lack of data from tropical areas, and the necessary focus on trait scoring that goes beyond macro-morphology. Overcoming these limitations will allow the field to explore new questions related to trait lability and niche evolution and to better set apart rules and exceptions in how plants diversify in space over time.

The present work exploits internet resources to update previously reported data for the distributional range and ecology of Cistanthe philhershkovitziana Hershk. (Cistanthe Spach sect. Cistanthe; Montiaceae), a conspicuous and not uncommon species of central and north-central Chile. The latitudinal range documented here is at least 4.8° greater than previously reported, extending from ca. 29°S (Huasco Province, Atacama Region) to ca. 33.8°S (San Antonio Province, Valparaiso Region). Possibly it extends further north to at least ca. 28.5°S. Morphological and ecological variability is discussed.

Evolution is increasingly found to be rapid and entangled with ecological processes in complex eco-evolutionary dynamics, calling for a common conceptual framework. Yet, ecological and evolutionary theory remain largely separated, which constrains the development of integrative research. To overcome this separation, I suggest treating the entangled dynamics as a single eco-evolutionary process rather than as separate ecological and evolutionary processes connected by feedbacks. I propose a unified conceptual framework that integrates ecological and evolutionary processes at population and community levels by considering which of them result from the same individual-based process. The resulting framework is a means to understand the entangled dynamics through the interaction of five basic eco-evolutionary processes: natural selection, drift, dispersal, gene transfer, and mutation. The framework reveals relationships between existing theories and models, provides simple means to discuss complex dynamics, and outlines a holistic approach to major topics including diversity, stability, and stochasticity. The framework thus presents a step towards conceptually uniting ecology and evolutionary biology.

1. The literature is awash with studies purporting to show how various species and data characteristics affect the performances of Species Distribution Models (SDMs). Many of these studies follow a similar template: they fit SDMs for several species, or the same species using different datasets; assess the accuracy of those SDMs using skill statistics; and then identify correlates thereof. Interpreting the findings of these studies is challenging because skill statistics can reflect species and data characteristics rather than model accuracy, and correlates of model performance are not necessarily causes. 2. Here, we took a different approach to identifying causes of variation in SDM performance. We fitted models for 535 species across 5 invertebrate groups and 1 plant group in the United Kingdom (UK), using a fairly typical SDM workflow. We measured two components of SDM performance: the variance among replicate fits and accuracy. Rather than using skill statistics, accuracy was assessed by taxon experts. We constructed Directed Acyclic Graphs (DAGs) depicting plausible effects of explanatory variables (e.g. species’ prevalence, sample size) on SDM performance, then quantified those effects using multilevel piecewise path models. 3. We found that the degree to which the available data covered species’ environmental niches was the only explanatory variable to affect SDM accuracy. We suggest that previously reported associations between sample size and SDM accuracy reflect improved coverage of species environmental niches at higher sample sizes; that is to say, niche completeness confounds the effect of sample size on SDM accuracy. We also report that the completeness of species’ environmental niches, sample size, species’ prevalence and the degree to which the available data cover species’ geographic ranges affect SDM variance. 4. Our results demonstrate the challenges associated with the high-throughput approach to modelling species’ distributions. There is no guarantee that accurate and precise SDMs can be constructed for large numbers of species unless their ranges and niches have been sampled comprehensively. Decisions about whether modelling is worthwhile should not be based on simple criteria like sample size.

Aquaculture is one of the practices that is projected to contribute to food security and the realization of UNDP SDG 2: Zero Hunger, by 2030. However, developing countries of which Kenya is no exception, are faced with the challenge of the impact of aquaculture practices on the environment (FAO, 2006). High amount of discharges which include waste food and faeces, nutrients, and in some instances medication and pesticide residues are released from cage farms. The impact of these effluents on the receiving environment depend largely on the quantity of waste discharged, the time period at which the discharge takes place, the ability of the environment to absorb the discharges and the rate at which the receiving water body is able to flush the effluent.

Based on topographic field data, an argument is advanced that Soil houses ~2.1 x 1024 taxa and supports >99.9% of global species biodiversity, mostly Bacteria or other microbes. Contradictory claims that Soil is home to only a quarter of biota while Ocean harbours 80–99% of Life on Earth are both dismissed. Earlier guesstimates of 8.8 million taxa (2.2 million or 25% marine), of 1–6 billion, or over a trillion species worldwide are likely underestimations. Recent studies show >1012 microbial OTU (just 1010 or 14 and speculated as high as 1023 species. Scaling of simple topsoil samples herein ups total to 2.1 x 1024 or 20x. Biomass at 2 x 10-13 g/cell of 2.1 x 1030 soil cells = 4 x 1017 g or 400 Gt (with 200 Gt Carbon, 48 Gt Nitrogen). An Addendum estimates microbes in gut of two key soil taxa: Megadrile earthworms (1021–1030 cells) and termites (1022–1023 cells) that strictly add to Soil’s totals. Although ranges are large, it is unclear how much 65 x 1015 earthworms contribute to Earth’s soils count of ~2.1 x 1030 cells., https://veop.files.wordpress.com/2022/09/new-addendum-file.pdf

Environmental monitoring is increasingly shifting towards a set of systems that describe changes in real-time. In ecology specifically, a series of challenges have prevented the roll-out of real-time monitoring for features such as biodiversity change or ecosystem service provision. Conservation culturomics, a field concerned with interactions between people and nature, is well-placed to demonstrate how monitoring might move towards a network of real-time platforms, given its existence almost exclusively in the digital realm. Here we describe a set of considerations associated with the development of real-time monitoring platforms for conservation culturomics. We then introduce a near real-time platform for the Species Awareness Index, a global index of changing biodiversity awareness derived from the rate of change in page views for species on Wikipedia. This platform will update automatically each month, operating in near real-time (hosted here: https://joemillard.shinyapps.io/Real_time_SAI/), with plans to make the underlying data queryable via an API independent of the platform. The real-time SAI will represent the first real-time and entirely automated conservation culturomic platform, and one of the first within the discipline of ecology. We conclude by envisioning a future for real-time monitoring, presenting a general framework for real-time monitoring in ecology, and calling for an online real-time observatory that can evolve with the structure of the web.

Ground level survey along with key informant Interviews has resulted in to identification of two rookeries and several habitat of the mangrove Horseshoe crab (Carcinoscorpius rotundicauda) in Satjelia-Lahiripur Island under Gosaba block. This is the first confirmed HSC habitat and rookeries which have been identified from the eastern side of Bidyadhari and areas around project tiger areas. Three pairs of live HSC and forty-five (45) carcasses have been found. The identified location is the lowest point of human inhabited islands in eastern part of river Matla. Key Informant Interview by Snowball sampling or chain-referral sampling method revealed that that the HSC are sighted throughout the year while the pick time of sighting may be March-June in the estuary. The study has found out that HSCs entangle regularly in the galsha or the gillnet and Chawrpata and Khalpata (Shore stake nets and channel stake nets) while the juveniles have been mostly affected by the Chawrpata (shore stakes nets) in which they entangle themselves with receding waters and both desiccate to die in profuse numbers in low tide exposures. The females were found to be morphometrically larger than the males. Higher numbers of female HSC are found to be entangling in fishing nets in the breeding season due to their higher numbers is a matter of great concern. While the local population has reported about the coexistence of this species from time immemorial but progressive accretion and generation of new mud flats suitable as breeding beaches of mangrove horse shoe crabs in contrast to the rookeries of the species in western Indian Sundarbans in Sagar Island and Namkhana which are going through steady phases of erosion at present, might definitely be played some role towards this activities. Extensive awareness, restriction in use of certain fishing gears in breeding and nursery time of HSC by declaring certain areas as community eco sensitive zones with feasible fiscal alternatives are being recommended as immediate conservation action to save the species.

Agroforestry can contribute to an increase in tree cover in historically forested tropical landscapes with associated gains in biodiversity and ecosystem functioning, but only if established on open land instead of underneath a forest canopy. However, declines in yields with increasing shade are common across agroforestry crops, driving shade-tree removal in forest-derived agroforests and hindering tree regrowth in open-land-derived agroforests. To understand trajectories of change in tree cover in forest- and open-land-derived agroforests, and the impacts of tree cover on vanilla yields, we studied 209 vanilla agroforests along an 88-year chronosequence in Madagascar. Additionally, we used remotely sensed canopy cover data to investigate tree cover change in the agricultural landscape. We found yields to vary widely but independently of canopy cover and land-use history (forest- vs. open-land-derived), averaging at 154.6 kg ha−1 year−1 (SD = 186.9). Furthermore, we found that forest- and open-land-derived vanilla agroforests gained canopy cover over time, but that only open-land-derived agroforests gained canopy height. Canopy cover increased also at the landscape scale: areas in the agricultural landscape with medium initial canopy cover gained 6.4% canopy cover over 10 years, but canopy cover decreased in areas with high initial canopy cover. These opposing trends suggest tree cover rehabilitation across areas covered by vanilla agroforests, whereas remnant forest fragments in the agricultural landscape were transformed or degraded. Our results indicate that yield-neutral tree rehabilitation through open-land-derived agroforestry could, if coupled with effective forest protection, provide benefits for both ecosystem functions and agricultural production in a smallholder-dominated agricultural landscape.

Species distribution models (SDMs) rely on species presence/absence or abundance data and environmental variables to estimate species response curves. Therefore, the quality (and quantity, i.e., sample size) of the data to describe the species distribution determines the quality of the estimate of the species-environment relationship. However, SDMs are seldom fitted on high-quality data collected strictly for that purpose. Usually, SDMs rely on a collection of opportunistic datasets sampled from previous projects or public repositories with different objectives. Here, we aim at assessing how the sampling strategy capturing the geographic distribution of a species affects the accuracy and precision of its response curves along environmental gradients, as estimated by parametric SDMs. We simulated the occurrence of two virtual plant species across the Abruzzo region (Italy). We assumed that the two virtual plants were similarly affected by precipitation, but one had a wider realised niche for temperature (i.e., higher thermal tolerance), and, as a result, a wider distribution extent. Then, we sampled occurrence data for the two species following five different sampling strategies: random, stratified, systematic, topographic, and uniform (the latter performed within the environmental space). In addition, we simulated a spatially biased sampling design by collecting presence/absence data close to roads. To account for sample size, we also repeated our simulations along a gradient of increasing sampling effort, i.e., number of sampled locations. In total, we ran 500 replicates for each combination of sampling design and effort. For each replicate, we fitted SDMs using binomial generalised linear models and extracted the model coefficients for precipitation and temperature to be compared with the true coefficients from the virtual species’ model. We evaluated the quality of the estimated response curves by computing the following measures: bias (accuracy), variance (precision), and mean squared error (accuracy and precision). Our results suggest that a proper estimate of the species response curve can be obtained when the choice of the sampling strategy is guided by the species’ ecology. In particular, species with wide tolerances to environmental drivers may be better modelled using data uniformly collected within the environmental space, while none of the tested sampling designs seemed to substantially outperform the others for modelling species with a narrow realised niche.

As the twenty-first century unfolds, the human-driven decline of life on Earth is of greater concern and, despite tremendous growth in the volume of conservation science and many local successes, shows no clear signs of improvement. As a matter of fact, the reversal of nature’s ongoing decline is only possible with urgent “transformative change” However, no transformative changes are viable without first accepting that, as many other species, we may be bound for extinction and that no time or solutions may be left to reverse nature’s decline. In light of this, I aim at provokingly inspiring the “courage of hopelessness”, while paradoxically providing the leverage to think differently. To this end I will remind that: 1) the main reports and projections about nature’s decline paint a gloomy picture for the future of contemporary societies; 2) the destructive fingerprint of modern human societies (i.e., capitalist enterprise), although being just one of the many expressions in the evolution of human cultures, is now dominant and necessarily finds its root in the human biology, thus in the way our species is cognitively coupled with the environment (i.e. conscious purpose and dualistic thinking); 3) such destructive fingerprint is particularly difficult to modify since we are naturally reluctant to change habits and beliefs even when we know they lead into error. Considering this, I suggest moving forward from the widely accepted but timed-out metaphor of conservation as a “crisis discipline”, which intrinsically suggests a temporary state and an optimistic perspective, in favour of a more “palliative” attitude towards our times.

As the most threatened vertebrate class on earth, amphibians are at the forefront of the biodiversity crisis, with the start of global amphibian declines and extinctions dating back several decades now. The Amphibian Conservation Action Plan (ACAP), the first taxonomic class-level plan of its kind, was first published in 2007 and then updated as a digital resource in 2015, with the goal of acting as a unified global strategy to save amphibians. However, although there have been resources allocated to amphibian conservation since the first ACAP, these have not been of the order of magnitude needed to adequately address the global amphibian crisis. In an effort to help improve this situation the current ACAP is adopting a different strategy: the development of two complementary documents that work to 1) synthesise developments in major themes of amphibian conservation over the last 15 years (an academic status review – this document), and 2) summarise the key take-home messages and recommendations to a broader audience in a user-friendly way (a practitioner document that will follow the status review). The purpose is thus to provide the most up-to-date evidence on threats and approaches to amphibian conservation, and from there identify gaps and priorities that can then be disseminated and adopted by stakeholders across the globe. Each chapter of this status review was developed by the matching Amphibian Specialist Group’s (ASG) thematic working groups. Led by 1-3 working group chairs and supported by working group members, chapters have also had the input of professionals outside of ASG with expertise in given themes. This document consists of two introductory chapters and twelve thematic chapters divided into three sections: • Threats - Chapters 3-7 on climate change; ecotoxicology; habitat loss; infectious diseases; and trade and sustainable use • Informing decision-making - Chapters 8-10 on communications and education; conservation planning; and surveys and monitoring • Species management - Chapters 11-14 on conservation breeding; assisted reproductive technologies and biobanking; genomics; and translocations In broad terms, each chapter covers the most important knowledge, technological and conceptual developments in a particular theme over the last decade and a half, highlighting knowledge gaps, challenges, needs and opportunities for future conservation action. Key messages 1. As a whole there is an enormous deficit in information for most amphibian species, which hampers decision-making and evidence-based, conservation action. Increased collaborations both within and outside the amphibian conservation community are urgently needed to begin to bridge some of these information gaps. Integrating different approaches can help augment information and leverage additional support to amphibian conservation. 2. While this document is global in scope it is informed by local and regional realities. Not everything that is in this document will be transferable to every region. However, those aspects that are relevant to a region can be addressed accordingly, and these results can then feedback again into a global strategy, and be readapted in other regions to benefit from the shared experience. Translation from local to global and back to local is crucial to ensure that regional experiences feed into a global framework and that this framework accurately reflects shared patterns and realities so that it can inform international conventions and organisations, especially in view of global environmental change. 3. Relative to the scope of amphibian declines and extinctions, adequate financial and human resources and necessary policy measures have largely lagged behind this decades-long crisis. Should this pattern persist, we can expect to continue losing amphibian populations and species in increasingly large numbers. It is therefore critical that amphibian conservation becomes both an integral and a conspicuous part of the biodiversity conservation agenda of international and national conservation organisations of all sizes, of national and subnational levels of government, of the various institutions that focus on biodiversity education and research, of funding entities, and of organised communities and media.

International audience; Functional diversity is widely used and widespread. However, the main packages used to compute functional diversity indices are not flexible and not adapted to the volume of data used in modern ecological analyses. We here present fundiversity, an R package that eases the computation of classical functional diversity indices. It leverages parallelization and memoization (caching results in memory) to maximize efficiency with data with thousands of columns and rows. We also did a performance comparison with packages that provide analog functions. In addition to being more flexible, fundiversity was always an order of magnitude quicker than alternatives. fundiversity aims to be a lightweight, efficient tool to compute functional diversity indices, which can be used in a variety of contexts. Because it has been designed following clear principles, it is easy to extend. We hope the wider community will adopt it and we welcome all contributions.

The U.S. Endangered Species Act (ESA) provides a framework for the protection and recovery of threatened and endangered species and their habitats in the face of anthropogenic threats. Genetic information has played a role in decision-making under the ESA for decades, most commonly informing taxonomy and the designation of distinct population segments, though detection of inbreeding also played an early role. The transition to genomic technologies has improved the precision and resolution of important population genetic metrics for at-risk species, such as genetic diversity and population structure. For other parameters, such as inbreeding, genomic data have transformed our ability to precisely measure individual level variation, as well as quantify downstream impacts on population viability. Genomic data have also democratized access to other parameters, such as estimates of evolutionary potential, that were once limited to model organisms and species amenable to experimental manipulation. In this chapter, we review how genetic data have informed decision-making under the ESA, and how the transition to genomics is improving the information that we can apply to both listing and recovery decisions. In some cases, genomic data are presenting new challenges to applied conservation under the ESA, providing an opportunity to evaluate and innovate existing practices. In all cases, falling costs and the increasing ease of genomic-scale data production in at-risk species are providing an unparalleled opportunity to improve applied conservation of threatened and endangered species and expand new frontiers for agency use of the “best available science” in ESA implementation.

Pathogen evolution is one of the least predictable components of disease emergence, particularly in nature. Here, building on principles established by the geographic mosaic theory of coevolution, we develop a quantitative, spatially-explicit framework for mapping the evolutionary risk of viral emergence. Driven by interest in diseases like SARS, MERS, and COVID-19, we examine the global biogeography of bat-origin betacoronaviruses, and find that coevolutionary principles suggest geographies of risk that are distinct from the hotspots and coldspots of host richness. Further, our framework helps explain patterns like a unique pool of merbecoviruses in the Neotropics, a recently-discovered lineage of divergent nobecoviruses in Madagascar, and--most importantly--hotspots of diversification in southeast Asia, sub-Saharan Africa, and the Middle East that correspond to the site of previous zoonotic emergence events. Our framework may help identify hotspots of future risk that have also been previously overlooked, like west Africa and the Indian subcontinent, and may more broadly help researchers understand how host ecology shapes the evolution and diversity of pandemic threats.

Policy makers require high-level summaries of biodiversity change. However, deriving such summaries from raw biodiversity data is a complex process involving several intermediary stages. In this paper, we describe a workflow for generating annual estimates of species’ occupancy at national scales from raw species occurrence data, which can be used to construct a range of policy-relevant biodiversity indicators. We describe the workflow in detail: from data acquisition, data assessment and data manipulation, through modelling, model evaluation, application and dissemination. At each stage, we draw on our experience developing and applying the workflow for almost a decade to outline the challenges that analysts might face. These challenges span many areas of ecology, taxonomy, data science, computing and statistics. In our case, a key output of the workflow is annual estimates of occupancy, with measures of uncertainty, for over 5,000 species in each of several defined “regions” (e.g., countries, protected areas, etc.) of the United Kingdom from 1970-2019. This product corresponds closely to the notion of a species distribution “Essential Biodiversity Variable” (EBV). Throughout the paper, we note where the workflow can be adapted to other situations (e.g., geographic regions or data types). We also highlight areas where the workflow can be improved; in particular, we suggest incorporation of methods to diagnose biases in the species occurrence data, to understand whether and to what extent these bias downstream products, and to mitigate them if needed. Finally, we compare the data products generated using our workflow to the first generation of species distribution EBVs and the “idealized” product as defined by others. Going forward, we hope that this paper can act as a template for research groups around the world seeking to develop similar data products.

Contemporary wildlife trade is massively facilitated by the Internet. By design, the dark web is one layer of the Internet that is difficult to monitor and lacks thorough investigation. Here, we accessed a comprehensive database of dark web marketplaces to search across c. 2 million dark web advertisements over 5 years using c. 7k wildlife trade-related search terms. We found 153 species traded in 3,332 advertisements (c. 600 advertisements per year). We characterized a highly specialized wildlife trade market, where c. 90% of dark-web wildlife advertisements were for recreational drugs. We verified that 68 species contained chemicals with drug properties. Species advertised as drugs mostly comprised of plant species, however, fungi and animals were also traded as drugs. Most species with drug properties were psychedelics (45 species), including one genera of fungi, Psilocybe, with 19 species traded on the dark web. The native distribution of plants with drug properties were clustered in Central and South America. A smaller proportion of trade was for purported medicinal properties of wildlife, clothing, decoration, and as pets. Our results greatly expand on what species are currently traded on the dark web and provide a baseline to track future changes. Given the low number of advertisements, we assume current conservation and biosecurity risks of the dark web are low. While wildlife trade is rampant on other layers of the Internet, particularly on e-commerce and social media sites, trade on the dark web may increase if these popular platforms are rendered less accessible to traders (e.g., via an increase in enforcement). We recommend focussing on surveillance of e-commerce and social media sites, but we encourage continued monitoring of the dark web periodically, to evaluate potential shifts in wildlife trade across this more occluded layer of the Internet.

Citizen science data has rapidly gained influence in urban ecology and conservation planning, but with limited understanding of how such data reflects social, economic, and political conditions and legacies. Understanding patterns of sampling bias across socioeconomic gradients is critical to accurately map and understand biodiversity patterns, and to generating representative and just environmental knowledge. In this study we explore how historic racially- explicit zoning policies (redlining) relate to biodiversity data collection across and within 195 metropolitan areas in the United States covering >30 million people across 38 states. We specifically look at birds, as they are the most widely studied group of animals, and hundreds of thousands of citizen scientists collect biodiversity data each year. We consistently find uneven bird observation sampling density across redlined areas, with so-called ‘desirable’ areas (i.e. historically white areas) having more than twice the density than areas redlined as ‘hazardous’. We further estimate the degree to which historically redlined areas are surveyed sufficiently and identify regions across all metro areas in need of enhanced bird surveying. After accounting for differences in present day vegetation, open space, population density and climate, we find significantly lower sampling density and sampling completeness in these redlined neighborhoods. Our results shed light on the importance of considering socio-political conditions in the interpretation of urban bird biodiversity estimates. We conclude by discussing specific policy implementations– such as the Justice 40 Initiative and propose a new EPA indicator – and opportunities in collaborating with bottom-up community and social justice organizations for a more representative understanding of biodiversity in urban areas.

The temporal variability of ecological properties tends to decrease with spatial scale and levels of biological organization, but how does it propagate across trophic levels? We compiled metacommunity time-series datasets spanning basal resources to top predators from 355 freshwater sites across three continents. Temporal variability in abundance decreased from producers to tertiary consumers mainly at the local scale. Population synchrony within sites increased with trophic level, whereas spatial synchrony among communities decreased. While climate and diversity controlled temporal variability similarly across trophic levels, the relationship between metacommunity variability and spatial synchrony was stronger for top consumers. Our results suggest that mobile predators can stabilize metacommunities by buffering variability originating at the base of food webs. This finding demonstrates that the trophic structure of metacommunities, which integrates variation in organismal body size, dispersal, and environmental tolerance, should be considered when investigating ecological stability.

Since the dawn of life, transfers of metabolized material between individuals have led to great innovations of evolution. When metabolized material is transferred from one individual’s body to another (as with sperm, eggs, milk, symbionts), secondary manipulative molecules that induce a physiological response in the receiver are often transferred along with the primary cargo. The bioactive and transfer-supporting components in these socially transferred materials have evolved convergently to the point where they can be used in applications across taxa and type of transfer. Because these materials’ composition is typically highly dynamic and context-dependent, their focused study will allow deeper understanding of their transformative evolutionary and physiological role. We synthesize a conceptual framework for their study, and discuss future directions.

Observations and collections of organisms form the basis of our understanding of Earth’s biodiversity and are an indispensable resource for global change studies. Geographic information is key, serving as the link between organisms and the environments they reside in. However, the geographic information associated with these records is often inaccurate, thus limiting their efficacy for research. Along these lines multiple solutions for identifying erroneous coordinate data and records georeferenced to centroids or landmarks have been developed. Another prominent, but less discussed and documented source of inaccuracies arises due to the use of gridded survey systems in many regions of the world. Here we present GridDER, a tool for identifying biodiversity records that have been designated locations on widely used grid systems. Our tool also estimates the degree of environmental heterogeneity associated with grid systems, allowing users to make informed decisions about how to use such occurrence data in global change studies. We show that a significant proportion (~13.5%; 261 million) of records on GBIF, largest aggregator of natural history collection data, are potentially gridded data, and demonstrate that our tool can reliably identify such records and quantify the associated uncertainties. GridDER can serve as a tool to not only screen for gridded points, but to quantify the geographic and environmental uncertainties associated with these records, which can be used to inform models and analyses that utilize these data, including those pertaining to global change.

Natural climate solutions are being advanced as cost-effective and safe ways to achieve net-zero emissions by protecting and enhancing carbon capture and storage in plants, and in soils and sediments in terrestrial and marine ecosystems. Current thinking holds that these solutions have the added benefit of protecting habitats and landscapes to restore and conserve animal species diversity. However this reasoning undervalues the inexorable functional role of animals in controlling the carbon cycle. We discuss the growing scientific evidence that reveals how enlisting the functional role of animals can significantly enhance natural carbon capture and storage. We call for new thinking that treats the conservation and restoration of animal species and their functional roles within ecosystems as a key way to broaden the scope of natural climate solutions and thereby help speed up the removal of CO2 from the atmosphere to prevent climate warming beyond 1.5°C.

Giant trees that have come to have their own unique identities, are often named by local people and can inspire a sense of awe and become objects of faith. Although these giant trees provide various kinds of spiritual ecosystem services that are beneficial to the spiritual well-being of the human society, the drivers of these services remain unclear. Using structural equation modeling with 5,353 giant tree records of 101 species across Japan, this study showed that macroecological processes, such as annual precipitation and temperature, drive spiritual ecosystem services obtained from giant trees directly and indirectly via tree sizes.

1. Opportunistic citizen science produces large amounts of primary biodiversity data but is underutilized in the conservation and management of protected areas despite these areas’ status as citizen science hotspots. Application of these data may be limited by the challenge of understanding sampling patterns associated with opportunistic data at a scale relevant to local area management. An improved understanding of citizen science activity patterns within protected areas could strengthen both data analysis and the local promotion and guidance of citizen science activity. 2. We investigated local-scale patterns of citizen science activity, using a case study approach to examine citizen science activity in a recreationally popular natural area that serves as a regional citizen science hotspot. We modeled the relationship between local citizen science activity and ten spatial covariates broadly related to ease of access and natural interest, factors which have been shown to drive citizen science activity at regional scales. We further compared the distribution of citizen science activity with that of professional data collection and recreational visitor activity in the study area. 3. We found that citizen science data largely complement rather than replicate openly available professional data. Citizen science participation was primarily driven by ease of access, especially the presence of trails. However, citizen science use of the trail network differed from other types of recreational trail use, including a weaker preference for well-established trails and a stronger association with developed areas. 4. This improved understanding of patterns in citizen science participation may be used to better account for spatial biases in citizen science data and to manage natural areas in a way that supports and guides future citizen science activity.

Anthropogenic changes such as land use and climate change affect species’ geographic ranges, causing range shifts, contractions, or expansions. However, data on range dynamics are insufficient, heterogeneous, and spatially and temporally biased in most regions. Integrated species distribution models (IDMs) offer a solution as they can complement good quality presence-absence data with opportunistically collected presence-only data, simultaneously accounting for heterogeneous sampling effort. However, these methods have seen limited use in the estimation of temporal change of geographic ranges and are not yet widespread as they have a steep learning curve. Here we present a generalisable model and case example to ease their adoption. Using data on presence-absence and presence-only on the yaguarundí (Herpailurus yagouaroundi), we modelled the species distribution at two time periods (2000-2013 and 2014-2021) using a Bayesian model based on Poisson point process in JAGS. Our model integrates the different types of data while accounting for varying sampling effort and spatial effect. We predicted the species range at the two time periods and quantified their changes. We found that between the two time periods, the yaguarundí has contracted its southern and northern range limits towards the equator, but expanded its area of distribution over the entire species’ range. Also, our results show that modelled geographic range (either pre or post) is not entirely consistent with the current expert range map from IUCN. Our modelling approach provides a working example with the potential to address data gaps and biases in other taxa and regions. Given the increasing number of incidental data being generated by community-derived initiatives in Latin America, IDMs can become a valuable source for species distribution modelling in the region. To our knowledge, this is the first application of the IDM approach with temporal dimension and over the entire species’ geographic range.

Communities composed of small populations are predicted to be strongly influenced by stochastic demographic events and, thus, less affected by environmental selection than those composed of large populations. However, this prediction has only been tested with computer simulations, simplified controlled experiments, and limited observational data. Here, using data on riverine fish we tested (1) if communities composed of small populations are more spatially variable and (2) if they are less related to the environment variation than communities composed of large populations. We used process-based simulations to identify β-diversity metrics and community-environment measures that were appropriate to investigate the role of assembly processes along a gradient of community size. We show that variation in species composition among small communities is higher than among large communities and that the strength of community-environment relationships is weaker in small communities. Our results indicate that community size affect the strength of ecological drift and environmental selection in metacommunities. We thus suggest that further declines in the size of populations and ecosystems can make spatial variation in biodiversity more unpredictable.

Temporal trends in species occupancy or abundance are a fundamental source of information for ecology and conservation. Model-based uncertainty in these trends is often communicated as frequentist confidence or Bayesian credible intervals; however, these are often misinterpreted in various ways, even by scientists. Research from the science of information visualisation indicates that line ensemble approaches that depict multiple outcomes compatible with a fitted model or data may be superior for the clear communication of model-based uncertainty. The discretisation of continuous probability information into frequency bins has also been shown to be useful for communicating with non-specialists. We present a simple and widely applicable approach that combines these two ideas, and which can be used to clearly communicate model-based uncertainty in species trends (or composite indicators) to stakeholders. We also show how broader ontological uncertainty can also be communicated via trend plots using risk-of-bias visualisation approaches developed in other disciplines. The techniques are demonstrated using the example of long-term plant distributional change in Britain, but are applicable to any temporal data consisting of averages and associated uncertainty measures. Our approach supports calls for full transparency in the scientific process by clearly displaying the multiple sources of uncertainty that can be estimated by researchers.

Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modeling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34-64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structure to changes in short- and long-term population growth rate using transient life table response experiments (LTREs). Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or non-breeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period. We show that both short- and longer-term population changes of British-breeding pied flycatchers are likely linked to factors acting during migration and in non-breeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.

It is important for emerging conservationists and wildlife managers to gain experience in the use of evidence-based conservation, by way of critical analysis and understanding of the context and application of conservation actions. We developed a teaching case and activity for undergraduate and graduate courses in conservation biology, wildlife management etc., although it could also be adopted for upper-level high school classes. The case is based on a recent study that assesses hatchery practices in India. Hatcheries are commonly established to protect sea turtle eggs and hatchlings from threats at the nesting beach. Guidelines for sea turtle hatcheries have been widely available and followed by sea turtle conservationists for decades, and their use has potentially contributed to successful conservation of some sea turtle populations worldwide. However, best practices in the collection, transport, and incubation of eggs, and holding and release of hatchlings should be followed to ensure hatchling production and fitness exceeds that of unprotected nests. The teaching activity builds conservation science literacy as students identify studies describing methods to assess risks to in situ clutches and mitigate threats including tidal inundation, depredation, and illegal take. A practical exercise asks students to assess threats at multiple nesting beaches on an island and propose which protection strategy (protect in situ, relocate to safer individual location on the beach, or relocate to a hatchery) would be most appropriate at different locations

1. Spectroscopy at the leaf or canopy scales is becoming one of the core tools of plant functional ecology. Remotely sensed reflectance spectra can allow ecologists to infer plant traits and strategies—and the community- or ecosystem-level processes they correlate with—continuously over unprecedented spatial scales. 2. Because of the complex entanglement of structural and chemical factors that generate spectra, it can be tricky to understand exactly what phenotypic information they contain. We discuss common approaches to estimating plant traits from spectra—radiative transfer models and multivariate empirical models—and elaborate on their strengths and limitations in terms of the causal influences of various traits on the spectrum. Many chemical traits have broad, shallow, and overlapping absorption features, and we suggest that covariance among traits may have an important role in giving empirical models the flexibility to estimate such traits. 3. While trait estimates from reflectance spectra have been used to test ecological hypotheses over the past 20 years, we review a growing body of research that uses spectra directly, without estimating specific traits. By treating positions of species in multidimensional spectral space as analogous to trait space, researchers can infer processes that structure plant communities using the information content of the full spectrum, which may be greater than any standard set of traits. We illustrate this power by showing that co-occurring grassland species are more separable in spectral space than in trait space and that the intrinsic dimensionality of spectral data is comparable to fairly comprehensive trait data sets. Nevertheless, using spectra this way may make it harder to interpret patterns in terms of specific biological processes. 4. Synthesis. Plant spectra integrate many aspects of plant function. The information in the spectrum can be distilled into estimates of specific traits, or the spectrum can be used in its own right. These two approaches may be complementary—the former being most useful when specific traits of interest are known in advance and reliable models exist to estimate them, and the latter being most useful in taking advantage of the information in the full spectrum under uncertainty about which aspects of function matter most.

Area-based conservation is a widely used approach for tackling biodiversity loss and there are ongoing discussions over what is an appropriate global conservation area coverage target. To inform such debates, we need to know the extent and ecological representativeness of the current conservation area network, but this is hampered by gaps in existing global datasets. In particular, while data on privately and communally managed protected areas (PAs) and OECMs (other effective area-based conservation measures) are often available at the national level, it can take many years to incorporate these into official datasets. This suggests a complementary approach is needed, based on selecting a sample of countries and using their national-scale datasets to produce more accurate metrics. However, every country added to the sample increases the costs of data collection, collation and analysis. To address this, here we present a data collection framework underpinned by a spatial prioritisation algorithm, which identifies a minimum set of countries that are also representative of 10 factors that influence conservation area establishment and biodiversity patterns. We then illustrate this approach to identify a representative set of sampling units that cover 10% of the terrestrial realm, selecting 25 countries (choosing the same 10% area at random selected a mean of 162 countries). These sampling units could be the focus of future data collation on different types of conservation area. Analysing these data could produce quicker, more accurate estimates of global conservation area coverage and ecological representativeness, complementing existing international reporting systems.

Pongamia pinnata (L.) Pierre (Pongamia) is a tree native to Southeast Asia. Recently, interest in Pongamia focused on its potential as a biofuel source as its seeds contain around 40% oil. However, Pongamia has multiple applications beyond biofuel production. It is a legume, can form symbiotic associations with mycorrhizal fungi, has been shown to be tolerant to drought, salinity, and heavy metals in soil, and has potential to mitigate climate change. Additionally, Pongamia oil has medicinal properties, can be used as biopesticide, insect repellent, to produce soap, and as a source of edible grade vegetable oil. The seed cake can be used as a source of bioenergy, food and feed protein, and organic fertiliser, and the flowers are a good source of pollen and nectar. Pongamia can also bring socio-economic benefits as its ability to restore degraded and contaminated land provides opportunities for local communities through novel valorisation pathways. These multiple applications have potential to form part of a circular bioeconomy in line with sustainable development goals. Although research on the multiple applications of Pongamia has grown considerably, knowledge gaps remain. Here, we critically review the available literature on Pongamia and highlight gaps in knowledge in which future research should focus on to ensure that the full potential of this versatile tree can be achieved. We argue that harnessing the multiple applications of Pongamia in a holistic manner, with collaboration among key stakeholders, is crucial for the successful application of its benefits far beyond biofuel production.

1. Estimates of temporal change of biodiversity, and its components loss and gain, are needed at local and geographical scales. However, we lack them because of data in-completeness, heterogeneity, and lack of temporal replication. Hence, we need a tool to integrate heterogeneous data and to account for their incompleteness. 2. We introduce spatiotemporal machine learning interpolation that can estimate cross-scale biodiversity change and its components. The approach naturally captures the expected and complex interactions between scale (grain), geography, data types, and drivers of change. As such it can integrate inventory data from reserves or countries with data from atlases and local survey plots. We present two flavors, both blending tree-based machine learning (random forests, boosted trees) with advances in ecolog-ical scaling: The first combines machine learning with species-area relationships (SAR method), the second with occupancy-area relationships (OAR method). 3. Using simulated data and an empirical example of global mammals and European plants, we show that tree-based machine learning effectively captures temporal biodi-versity change, loss, and gain across a continuum of spatial grains. This can be done despite the lack of time series data (i.e., it does not require temporal replication at sites), temporal biases in the amount of data, and highly uneven sampling area. These estimates can be mapped at any desired spatial resolution. 4. In all, this is a user-friendly and computationally fast approach with minimal require-ments on data format. It can integrate heterogeneous biodiversity data to obtain esti-mates of temporal biodiversity change, loss, and gain, that would otherwise be invisi-ble in the raw data alone.

Zu et al (Science, 19 Jun 2020, p. 1377) propose that an ‘information arms-race’ between plants and herbivores explains plant-herbivore communication at the community level. However, our analysis shows that key assumptions of the proposed model either a) conflict with standard evolutionary theory or b) are not supported by the available evidence. We also show that the presented statistical patterns can be explained more parsimoniously (e.g. through a null model) without invoking an unlikely process of community selection.

Indicators supporting implementation of the post-2020 Global Biodiversity Framework (GBF) are likely to be used not only to monitor progress toward achieving agreed goals and targets, but also to help prioritise specific actions to address shortfalls in this achievement as efficiently as possible. To perform this dual role, adopted indicators must be derived from data of sufficient rigour and spatial resolution to inform decision-making at national and subnational scales. They also need to account for relevant interdependencies between, and within, individual goals and targets. Here we focus on a particularly prominent set of such dependencies – the impact that area-based actions under draft GBF Targets 1, 2 and 3 will have on outcomes for ecosystem area and integrity (including connectivity) under Goal A, and for the flow-on effect that these changes will, in combination, have on the persistence of species diversity. We show how these various linkages can now be addressed across all forests globally, by coupling state-of-the-art mapping of ecosystem integrity with the integrative analytical capability of an advanced habitat-based biodiversity indicator. Results generated for the world’s forest-supporting countries demonstrate that rigorous consideration of the above interdependencies can profoundly alter understanding of the present state of forest biodiversity, and of the spatial distribution of priorities for area-based action, relative

Society is confronted by interconnected threats to ecological sustainability. Among these is the devastation of forests by destructive non-native pathogens and insects introduced through global trade, leading to the loss of critical ecosystem services and a global forest health crisis. We argue that the forest health crisis is a public good social dilemma and propose a response framework that incorporates principles of collective action. This framework will enable scientists to better engage policymakers and empower the public to advocate for proactive biosecurity and forest health management. Collective action in forest health will feature broadly inclusive stakeholder engagement to build trust and set goals; accountability for destructive pest introductions; pooled support for weakest-link partners; and inclusion of intrinsic and non-market values of forest ecosystems in risk assessment. We provide short-term and longer-term measures that incorporate the above principles to shift the societal and ecological forest health paradigm to a more resilient state.

Zooplankton provide critical food for threatened and endangered fish species in the San Francisco Estuary (estuary). Reduced food supply has been implicated in the Pelagic Organism Decline of the early 2000s and further changes in zooplankton abundance, seasonality, and distribution may continue to threaten declining fishes. While we have a wealth of monitoring data, we know little about the abundance trends of many estuary zooplankton species. To fill these gaps., we reviewed past research and then examined trends in seasonality and abundance from 1972 to present of three key but understudied zooplankton species (Bosmina longirostris, Acanthocyclops spp., and Acartiella sinensis) that play important roles in the estuary food web. All three species were found in the stomach contents of important estuarine fishes. We fit Bayesian generalized additive mixed models of each species’ relationships with salinity, seasonality, year, and geography on an integrated database of zooplankton monitoring in the upper estuary. We found marked changes in the seasonality and overall abundance of each study species. B. longirostris no longer peaks in abundance in the fall months, Acanthocyclops spp. dramatically declined in all months and lost its strong relationship with salinity, and A. sinensis adult abundance has become increasingly driven by salinity while juveniles have developed wider seasonal abundance peaks. In this process, we have documented the relationship of each species with salinity and seasonality since the beginning of monitoring or their introduction, thus increasing our understanding of their ecology and importance in the estuary. These results can inform food web models, be paired with fish data to model the contributions of these species toward fish abundance trends, and be mirrored to elucidate other species’ trends in future studies.

Human impacts on the Earth’s biosphere are driving the global biodiversity crisis. Governments are preparing to agree on a set of actions intended to halt the loss of biodiversity and put it on a path to recovery by 2050. We provide evidence that the proposed actions can bend the curve for biodiversity, but only if these actions are implemented urgently and in an integrated manner.

Empirical quantification of biodiversity changes remains a challenge even in well surveyed groups such as birds. This may be because the change depends on spatio-temporal scales, specifically on spatial grain (i.e. area of a sampling unit), geographic extent (i.e. size of the area of interest), temporal grain (i.e. duration of a sampling event), and temporal extent (i.e. length of the time series). Further, different metrics of biodiversity may exhibit different trends. Here we review global literature assessing the temporal trends of avian biodiversity from ca 1900 AD to present, focusing on studies summarising trends across many locations within a larger region (i.e. spatially replicated). From each study we extracted direction of average trend (increase, decrease, stable), spatial and temporal grains and extents at which trends have been assessed, metrics of biodiversity, and location. We then discuss the trends as a function of the spatio-temporal grains and extents they are defined at. We found 59 trends of 12 metrics, where each trend is an average of trends from multiple sites (spatial replicates). There was a tendency of biodiversity metrics to increase at local and regional spatial scales, and to not increase globally. We thus confirmed that biodiversity dynamics can have opposite trends at different spatial scales. Concerning temporal grain, it was poorly documented across the studies, with inconsistent definitions, and we suggest a common framework to better understand the link between temporal scales and biodiversity dynamics. We have also identified underrepresented regions (those outside North America and Europe), periods (those before the 70’s), and biodiversity metrics that need further attention. We highlight the importance of considering both spatial and temporal scaling jointly in any assessment of biodiversity change, and provide guidelines for how to do this effectively both in birds, and in other taxa.

1. The patterns of successional change of decomposer communities is unique in that resource availability predictably decreases as decomposition proceeds. Saproxylic (i.e., deadwood-dependent) beetles are a highly diverse and functionally important decomposer group, and their community composition is affected by both deadwood characteristics and other environmental factors. Understanding how communities change along faunal succession is important as this process influences terrestrial carbon dynamics. 2. Here, we evaluate how beta-diversity of saproxylic beetle communities change with succession, as well as the effects of different major drivers of beta-diversity, such as deadwood tree species, spatial distance between locations and forest structure. 3. We studied spatial beta-diversity (i.e., dissimilarity of species composition between deadwood logs in the same year) of saproxylic beetle communities over eight years of wood decomposition. Our study included 379 experimental deadwood logs comprising 13 different tree species in 30 forest stands in Germany with differences in forest structure that is influenced by management regimes. We hypothesized that the effect of tree species dissimilarity, measured by phylogenetic distance, on spatial beta-diversity decreases over time, while the effects of spatial distance between logs (1m to ~600km) and differences in forest structure increase. 4. Spatial beta-diversity of saproxylic beetle communities was high throughout the first eight years of succession and even increased slightly over time except when focusing on dominant species (i.e., q = 2 in the Hill number calculation). Beta-diversity increased with increasing phylogenetic distance between tree species, spatial distance, and differences in forest structure. While effects of space and forest structure were constant over time, the effect of phylogenetic distance decreased over time. 5. Our results show that the strength of the different drivers of saproxylic beetle community beta-diversity changes along deadwood succession. Beta-diversity of early decay communities was strongly associated with differences between tree species. Although this effect decreased over time, beta-diversity remained high throughout succession. Possible explanations for this pattern include differences in decomposition rates and fungal communities between logs or the priority effect of early successional communities. Our results suggest that saproxylic beetle diversity can be promoted by high diversity in tree species and forest structural characteristics.

Metawebs, i.e. networks of potential interactions within a species pool, are a powerful abstraction to understand how large-scales species interaction networks are structured. Because metawebs are typically expressed at large spatial and taxonomic scales, assembling them is a tedious and costly process; predictive methods can help circumvent the limitations in data deficiencies, by providing ‘draft’ metawebs. One way to improve the predictive ability is to maximize the information used for prediction, by using graph embeddings rather than the list of species interactions. Graph embedding is an emerging field in machine learning that holds great potential for ecological problems. In this perspective, we outline how the challenges associated with inferring metawebs line-up with the advantages of graph embeddings; furthermore, because metawebs are inherently spatial objects, we discuss how the choice of the species pool has consequences on the reconstructed network, but also embeds hypotheses about which human-made boundaries are ecologically meaningful.

Ecology and evolutionary biology, like other scientific fields, are experiencing an exponential growth of academic manuscripts. As domain knowledge accumulates, scientists will need new computational approaches for identifying relevant literature to read and include in formal literature reviews and meta-analyses. Importantly, these approaches can also facilitate automated, large-scale data synthesis tasks and build structured databases from the information in the texts of primary journal articles, books, grey literature, and websites. The increasing availability of digital text, computational resources, and machine-learning based language models have led to a revolution in text analysis and Natural Language Processing (NLP) in recent years. NLP has been widely adopted across the biomedical sciences, but is rarely used in ecology and evolutionary biology. Applying computational tools from text mining and NLP will increase the efficiency of data synthesis, improve the reproducibility of literature reviews, formalize analyses of research biases and knowledge gaps, and promote data-driven discovery of patterns across ecology and evolutionary biology. Here we present recent use cases from ecology and evolution, and discuss future applications, limitations, and ethical issues.

We present an innovative framework for assessing fluvial aquatic species conservation under conditions of an impending regime shift using the case example of the Upper Colorado River Endangered Fish Recovery Program (UCREFRP). We assess the effectiveness of the program actions first, the ecoregional impact of the program second and the adaptive management paradigm in this context third, using mixed qualitative and quantitative approaches. Assessment of program effectiveness utilizes annual flow regime variability, and year-by-year summation of categories (hydrological, technological, ecological) of management interventions as predictive variables of abundance-based beta diversity indices of fish communities in six key Upper Basin sites. Results show that fish community beta diversity metrics are most responsive to hydrological and technological interventions such as e-flows through reservoir reoperation, and not on natural flow variability. Assessment of the program actions against the adaptive management paradigm uses a Resistance-Resilience-Transformation (RRT) scale. We find a backsliding from resilience-building actions to resistive strategies, where more transformative actions are required. Assessment of the effectiveness of the adaptive management paradigm shows that program policies and actions need to account more for compounded effects of multiple environmental and anthropogenic stressors to maintain the ecological health of the river into the future.