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Despite decades of global commitments, and increasingly urgent warning of environmental instability, the demand for land to support economic production is still increasing. Isolated and disorganized actions will not be enough to avert ecosystem failures. As many developers are already required to compensate for their ecological impacts through restoration, many see markets trading biodiversity credits as a financial mechanism to counteract degradation and drive investment in conservation. The challenge stems from a desire to recognize the multidimensional nature of biodiversity that contributes to ecosystem integrity without making suitable offsets intractable to supply. Instead, most regulators have opted to streamline ecological assessment, and undermine ecological rigour, in favour of promoting offset supply and economic efficiency. As a result, all evidence suggests offset trading programs have so far failed to mitigate losses, let alone support “nature positive” outcomes. To overcome this disconnect, and support more effective and equitable biodiversity markets, we propose credits be defined by theirreplaceabilityof a site, a metric long-established in the domain of systematic conservation planning. Irreplaceability avoids the limitations of like-for-like trading, reduces costs of offsetting to developers and society, ensures farmers willing to sell are fairly rewarded for loss of earnings, and that sites critical to achieving conservation goals are safeguarded. We developed an ecological-economic model of a biodiversity offset market to demonstrate irreplaceability guarantees no net loss of biodiversity and is the most efficient metric for guiding investment toward the recovery of Nature.

Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) Fundacao de Apoio a Pesquisa do Distrito Federal (FAPDF), Fundacao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM), BIODIVERSA/FAPEAM, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ), Bundesministerium fuer Bildung und Forschung, Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), FAPEAM-Program POSGRAD, Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG), INPA/MCTI 465540/2014-7, Leibniz Competition 0621187/2017, Leibniz-Gemeinschaft R20F0002, Instituto Nacional de Pesquisas da Amazpnia, unidade de~pesquisa Ministerio da Ciencia, Tecnologia e Inovacoes (INPA/MCTI) 403758/2021-1, Programa Peixe Vivo of the Companhia Energetica de Minas Gerais 033W034A, Royal Society of New Zealand, Tertiary Education Commission, Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Foundation for Science and Technology, Associate LaboratoryARNET J45/2018, CEEC

Significance Too often, ecological monitoring studies are designed without understanding whether they have sufficient statistical power to detect changes beyond natural variability. The Peace–Athabasca Delta is North America’s largest inland delta, within a World Heritage area, and is currently threatened by human development. Using multispecies occupancy models we show that the wetland macroinvertebrate community is highly diverse, and spatial and temporal turnover are so high that composition is nearly random, emphasizing stochastic processes of assembly. Using DNA metabarcoding, our study detected more taxa, both overall and per sample, than traditional morphology-based sample processing, increasing our power to detect ecosystem change. Improving data quality and quantifying error are key to delivering effective monitoring and understanding the dynamic structure of the metacommunity., The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large scales. The Peace–Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification and DNA metabarcoding. By using multispecies occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera and quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were nearly random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

Given the magnitude and rate of ongoing climate change, the physiological capacity of species to tolerate extreme conditions will play a key role in influencing outcomes for biodiversity. It is also possible that species will respond to changes in climate by shifting their physiological tolerances, through genetic adaptation. How these processes influence biodiversity outcomes will be crucial in determining the most suitable management responses to retain diversity into the future. Here we assess how accounting for physiological tolerances, genetic adaptation and community assembly processes such as species replacement, influence projected climate change outcomes for the flora of Tasmania (all 2051 plant species). We incorporate these processes into the M‐SET metacommunity model and compare four different assumptions of species niches: realized niches, broader physiological tolerances and low or high capacity for genetic adaptation. Accounting for physiological tolerances rather than realized niches had the largest impact on projected outcomes, with 358 fewer species extinctions in the hottest climate scenario (mean = 30 extinctions). In contrast, adding the capacity for species physiological tolerances to shift through genetic adaptation resulted in little additional benefits for biodiversity outcomes, even under an optimistic level of adaptive capacity. We find that this is due largely to community assembly processes such as species replacement restricting the ability of species to persist and adapt in situ, as has been suggested from theoretical metacommunity models applied in simple artificial settings. Our results highlight the importance of accounting for species physiological tolerances and community‐level processes in biodiversity projections, while the potential role for genetic adaptation may be small, requiring further exploration in alternative contexts.

Aim: Observed, realized niche space often underestimates species’ physiological tolerances due to interactions with other species, dispersal constraints, and because some combinations of influential environmental factors do not currently exist in the real world. Conversely, correlative ecological niche models rely on the assumption that the range of environmental conditions encompassed by a species’ geographic distribution accurately reflects their environmental tolerances, including community-level approaches like generalized dissimilarity modelling (GDM). We extend GDM to better understand what effect broader environmental tolerances could have on compositional turnover under climate change. Innovation: We show how GDM can be adjusted as a function of best-available estimates of the average ratio between realized and potential niche widths to modify projected temporal turnover. We demonstrate this approach by using the estimated niche ratios of Australian plant species (n = 7,184) relative to thermal extremes, and the rate at which this ratio varied with temperature. The modified GDMs showed existing thermal tolerance could reduce the turnover predicted by standard models under climate change by up to 11%. We further show how the reduction in expected turnover by 2090 will influence where a greater proportion of the current community will persist in a region. Main conclusions: We suggest that standard spatial GDMs and their modified versions represent the extremes of ecological niche perspectives (i.e., realized and potential) and the range of tolerance communities may have when responding to environmental change. GDM projections therefore identify the range of uncertainty associated with a critical model assumption, and as climate change continues, ongoing community monitoring could be used to validate the balance between the two possibilities.

Metabarcoding is capable of delivering consistent and accurate fine-resolution biodiversity data, and offers great promise for improving aspects of environmental assessment and research. Even so, many ecologists are keen to make further inferences about species’ abundances and the number of sequence reads has proven to be a poor proxy for abundance. The conservative interpretation has been to treat metabarcoding data as presence/absence, and although such data are less rich, occurrence and abundance are only different expressions of the same phenomenon. Interestingly if we assume the probability of detecting individuals is constant, it should be possible to use changes in the frequency of detection to infer changes in the underlying abundance. We tested the possibility that changes in the abundance structure of benthic macroinvertebrate communities could be recovered using replicated metabarcoding. We conducted 5 monthly surveys from Jun-Nov 2019 at the Catamaran Brook, a small tributary of the Little Southwest Miramichi River in New Brunswick, Canada. Each survey collected 30 benthic samples divided between control and treatment cages that excluded predatory fish. A further 6 samples were taken for traditional microscopic identification and counting. Analysis of the metabarcoding data demonstrated that we could recover plausible changes in abundance from occurrence data, including significant responses to both seasonal dynamics and the experimental exclusion of predators. The microscopy samples merely confirmed that count data are highly stochastic, and therefore while specific estimates of expected abundance from our model are highly uncertain, they capture those differences we could validate. In summary, while we confirmed that occurrence data are more robust for routine bioassessment, it is possible to recover fine-resolution changes in abundance that can inform ecological studies using metabarcoding.

Transformative advances in metagenomics are providing an unprecedented ability to characterize the enormous diversity of microorganisms and invertebrates sustaining soil health and water quality. These advances are enabling a better recognition of the ecological linkages between soil and water, and the biodiversity exchanges between these two reservoirs. They are also providing new perspectives for understanding microorganisms and invertebrates as part of interacting communities (i.e. microbiomes and zoobiomes), and considering plants, animals, and humans as holobionts comprised of their own cells as well as diverse microorganisms and invertebrates often acquired from soil and water. The Government of Canada's Genomics Research and Development Initiative (GRDI) launched the Ecobiomics Project to coordinate metagenomics capacity building across federal departments, and to apply metagenomics to better characterize microbial and invertebrate biodiversity for advancing environmental assessment, monitoring, and remediation activities. The Project has adopted standard methods for soil, water, and invertebrate sampling, collection and provenance of metadata, and nucleic acid extraction. High-throughput sequencing is located at a centralized sequencing facility. A centralized Bioinformatics Platform was established to enable a novel government-wide approach to harmonize metagenomics data collection, storage and bioinformatics analyses. Sixteen research projects were initiated under Soil Microbiome, Aquatic Microbiome, and Invertebrate Zoobiome Themes. Genomic observatories were established at long-term environmental monitoring sites for providing more comprehensive biodiversity reference points to assess environmental change.

Reptiles are rarely included in urban freshwater biodiversity monitoring and conservation. We explored the global persistence of freshwater dependent turtles, lizards, crocodilians and snakes in cities with a population greater than 100,000 using species occurrence data in online databases from a five-year period (2013&ndash, 2018). We then used ecological niche models to help identify the locations of suitable habitats for three freshwater reptile species in Sydney, Australia. Our Global analysis showed that sightings of a majority of known species of crocodilians and freshwater turtles were recorded in databases within this 5-year period in contrast to about one in three freshwater lizard species and one in ten freshwater snake species and that freshwater reptiles were observed within 50 km of the center of 40% of the 3525 cities. While global databases hold substantial recent species occurrence records for some regions, they contain very little data for large parts of the world. Modelling showed that potential suitable habitat for the three freshwater species in Sydney was distributed across areas with different levels of urban development. The persistence of populations of freshwater reptiles in and around a large proportion of the world&rsquo, s cities show that this group can play an important role in urban biodiversity conservation.

Aim Despite recognition that realized distributions inherently underestimate species' physiological tolerances, we are yet to identify the extent of these differences within diverse taxonomic groups. The degree to which species could tolerate environmental conditions outside their observed distributions may have a significant impact on the perceived extinction risk in ecological models. More information on this potential error is required to improve our confidence in management strategies. Location Australia. Time Period 1983–2012. Major Taxa Studied Plants. Methods To quantify the scale and spatial patterns of this disparity, we estimated the existing tolerance to thermal extremes of 7,124 Australian plants, more than one-third of the native continental flora, using data from cultivated records at 128 botanical gardens and nurseries. Hierarchical Bayesian beta regression was used to assess whether factors such as realized niches, traits or phylogeny could predict the incidence or magnitude of niche truncation (underestimation of thermal tolerances), while controlling for sources of collection bias. Results Approximately half of the cultivated species analysed could tolerate temperature extremes beyond those experienced in their native range. Niche truncation was predictable from the breadth and extremes of their realized niches and by traits such as plant growth form. Phylogenetic relationships with niche truncation were weak and appeared more suited to predicting thermal tolerances directly. Main conclusions This study highlights a widespread disparity between realized and potential thermal limits that may have significant implications for species' capacity to persist in situ with a changing climate. Identifying whether thermal niche truncation is the result of biotic interactions, dispersal constraints or other environmental factors could provide significant insight into community assembly at macroecological scales. Estimating niche truncation may help to explain why certain ecological communities are more resilient to change and may potentially improve the reliability of model projections under climate change.

A critical requirement in assessing progress towards global biodiversity targets is improving our capacity to measure changes in biodiversity. Global biodiversity declined between 2000 and 2010, and there are indications that the decline was greater in freshwater than in terrestrial or marine systems. However, the data, tools and methods available during that decade were inadequate to reliably quantify this decline. Recent advances in freshwater monitoring make a global assessment now close to becoming feasible. Here we identify priorities for freshwater biodiversity assessment for 2020 and 2030, based on the Essential Biodiversity Variables (EBV) framework. We identify 22 priority activities for 2020 under three of the EBV classes (species populations, community composition, and ecosystem structure), which include: a globally systematic approach to collecting and assessing species data, collating existing and new data within global platforms, coordinated effort towards mapping wetland extent at high spatial resolution, linking in-situ data to modelling across regions, and mobilising citizen science for the collection and verification of data. Accomplishing these will allow the state of global biodiversity to be assessed according to a Red List Index with expanded geographic and taxonomic cover, an improved freshwater Living Planet Index with a greater number and phylogenetic range of species, measures of alpha and beta diversity, and globally-consistent estimates of wetland extent. To assess variables in the other EBV classes (genetic composition, species traits, and ecosystem function) we identify 15 priorities, which include development of environmental DNA methods, species-traits databases, eco-informatics and modelling over the next 15 years.

Aim: To assess how climate change may decouple the ecosystems used by a migratory fish, and how decoupling influences priorities for stream restoration. Location: Australia. Methods: We modelled changes in habitat suitability under climate change in both riverine and marine habitats for a threatened diadromous species, the Australian Grayling Prototroctes maraena, using niche models. The loss of riverine habitats for Grayling was compared with or without considering the impact of climate change on adjacent marine habitats. We also asked whether considering marine climate change changed the locations where removing dams had the greatest benefit for Grayling conservation. Results: Climate change is expected to cause local extinction in both marine and river habitats regardless of whether dams are retained or removed at the trailing edge of the Grayling's range (north-eastern). Decoupling of habitats was most apparent in the eastern and south-eastern portion of the Grayling's range, where ocean warming may cause a decline in the suitability of marine habitats for larvae, while many freshwater habitats retained suitable habitat for adults. Removing dams to restore connectivity between ocean and freshwater habitats was predicted to have the greatest benefit for Grayling in southern portions of their range. Under climate change, the priorities for barrier removal gradually shift towards dams at higher elevation because of increasing suitability of freshwater habitats at higher elevations. Main conclusions: Our study highlights the importance of assessing climate range shifts in multiple ecosystems for migratory species and can help inform priorities for stream restoration under a changing climate.

Summary Freshwater ecosystems appear to be sensitive to even minor climatic shifts, and the dendritic nature of rivers as well as patchy distribution of habitats within the terrestrial landscape could limit the ability of species to track suitable climate conditions. Although the importance of dispersal is recognised in theory, there is great uncertainty when quantifying the capacity of species to shift their distributions in response to climate change. The influence of dispersal capacity on species’ vulnerability to climate change was assessed, using the modelled projections of 527 freshwater species in New South Wales (NSW), Australia. Species’ future ranges were calculated by iteratively identifying colonisation of accessible habitats and loss of suitable habitats within network models. The accessibility of new habitats was based on a given dispersal mode (aquatic, semi-terrestrial and aerial). The relative impact of dispersal parameters on projected range were evaluated alongside other known sources of uncertainty (climate and emissions scenarios, modelling algorithm and biological group), analysed collectively in a generalised additive mixed-model, and spatially to locate regions of NSW where projections are associated with the most uncertainty. Our simulations (1.4 million scenario combinations) suggest at least a third of species will lose more than half their range under climate change. Nevertheless, we emphasise the broad uncertainty that any average encapsulates. Dispersal capacity only had a minor impact on projected range shifts relative to other modelling assumptions but the network-pathways and maps of uncertainty have value for conservation planning at large scales. Projected range losses initially decreased rapidly as dispersal rates increased but the benefits are reduced above 2–3 km year−1. Taxa restricted to dispersal within the stream network (aquatic) were more vulnerable to climate change than taxa with semi-terrestrial or aerial dispersal and maps of variation due to dispersal mode and rate indicate where habitat connectivity would be most beneficial. This study demonstrates the breadth of uncertainties that challenge plans for improving ecosystem adaptation under climate change and highlights where in the landscape those differences were consistent. We emphasise the need for freshwater conservation studies to be ecologically representative, to focus on broad-scale connectivity for taxa that can move between catchments, and an accessible network of refugia for taxa with more limited dispersal.

An ongoing challenge for ecological studies has been the collection of data with high precision and accuracy at a suitable scale to detect and manage critical global change processes. A major hurdle has been the time-consuming and challenging process of sorting and identification of organisms, but the rapid development of DNA metabarcoding as a biodiversity observation tool provides a potential solution. As high-throughput sequencing becomes more rapid and cost-effective, a “big data” revolution is anticipated, based on higher and more accurate taxonomic resolution, more efficient detection, and greater sample processing capacity. These advances have the potential to amplify the power of ecological studies to detect change and diagnose its cause, through a methodology termed “Biomonitoring 2.0.” Despite its promise, the unfamiliar terminology and pace of development in high-throughput sequencing technologies has contributed to a growing concern that an unproven technology is supplanting tried and tested approaches, lowering trust among potential users, and reducing uptake by ecologists and environmental management practitioners. While it is reasonable to exercise caution, we argue that any criticism of new methods must also acknowledge the shortcomings and lower capacity of current observation methods. Broader understanding of the statistical properties of metabarcoding data will help ecologists to design, test and review evidence for new hypotheses. We highlight the uncertainties and challenges underlying DNA metabarcoding and traditional methods for compositional analysis, specifically comparing the interpretation of otherwise identical bulk-community samples of freshwater benthic invertebrates. We explore how taxonomic resolution, sample similarity, taxon misidentification, and taxon abundance affect the statistical properties of these samples, but recognize these issues are relevant to applications across all ecosystem types. In conclusion, metabarcoding has the capacity to improve the quality and utility of ecological data, and consequently the quality of new research and efficacy of management responses.

The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large-scales. The Peace-Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed, and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification, and DNA metabarcoding. Using multi-species occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification, and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera, and for the first time, quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were near random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales, but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

Aim: Studies of climate change impacts on animal distributions typically consider only the direct impacts of a changing climate, under the assumption that future areas of suitable climate will otherwise remain ecologically suitable. Here we assess both the direct and indirect impacts of climate change on rain forest ant communities, where substantial shifts are projected to occur for both climate and habitat types. Location: Australian Wet Tropics (AWT). Methods: Generalized Dissimilarity Modelling was used to model turnover in the composition of ~300 rain forest ant species sampled at 150 sites across six mountains spanning five degrees of latitude. Ants were sampled within the leaf litter, on the litter surface and on tree trunks. By modelling the rate of turnover among sites, we determined the current effective area of similar ecological environments (SEE) for ant communities and consequently the expected change in species persistence when habitat shifts under two climate projections for the years 2035, 2055 and 2085. We compared results when SEE considered only the direct effects of a changing climate, with those when changes in habitat were also included. Results: The rain forest ant communities modelled will lose a substantial proportion of SEE under both climate change scenarios. Under combined direct (changes in climate) and indirect (changes in rain forest habitat) impacts of climate change, >90% of the communities in the region were predicted to lose up to half their similar habitats compared with 50%–60% when only considering direct climate change impacts. The highest risk of reduction in area of SEE is projected in drier inland areas of the AWT, where profound compositional turnover is linked to dramatic changes in rain forest vegetation, including extensive conversion into savanna. Main conclusions: Our findings emphasize the importance of incorporating habitat suitability into future projections of species turnover under a changing climate, particularly for habitats where vegetation structure is projected to undergo profound change.

An ongoing challenge for ecological studies has been the collection of data with high precision and accuracy at a sufficient scale to detect effects relevant to management of critical global change processes. A major hurdle for many workflows has been the time-consuming and challenging process of sorting and identification of organisms, but the rapid development of DNA metabarcoding as a biodiversity observation tool provides a potential solution. As high-throughput sequencing becomes more rapid and cost-effective, a ‘big data’ revolution is anticipated, based on higher and more accurate taxonomic resolution, more efficient detection, and greater sample processing capacity. These advances have the potential to amplify the power of ecological studies to detect change and diagnose its cause, through a methodology termed ‘Biomonitoring 2.0’.Despite its promise, the unfamiliar terminology and pace of development in high-throughput sequencing technologies has contributed to a growing concern that an unproven technology is supplanting tried and tested approaches, lowering trust among potential users, and reducing uptake by ecologists and environmental management practitioners. While it is reasonable to exercise caution, we argue that any criticism of new methods must also acknowledge the shortcomings and lower capacity of current observation methods. Broader understanding of the statistical properties of metabarcoding data will help ecologists to design, test and review evidence for new hypotheses.We highlight the uncertainties and challenges underlying DNA metabarcoding and traditional methods for compositional analysis, focusing on issues of taxonomic resolution, sample similarity, taxon misidentification, sample contamination, and taxon abundance. Using the example of freshwater benthic ecosystems, one of the most widely-applied non-microbial applications of DNA metabarcoding to date, we explore the ability of this new technology to improve the quality and utility of ecological data, recognising that the issues raised have widespread applicability across all ecosystem types.

In September 2017, a workshop was held at Wageningen University and Research to determine the current state of knowledge of multiple stressor effects on aquatic ecosystems and to assess how to improve prediction of these effects. We developed a theoretical framework that integrates species-level responses to stressors to predict how these effects propagate through higher levels of biological organisation. Here, we present the application of the framework for drainage ditch ecosystems in the Netherlands. We used food webs to assess single and multiple stressor effects of common stressors on ditch communities. We reviewed the literature for the effects of targeted stressors (nutrients, pesticides, dredging and mowing, salinization, and siltation) on each functional group present in the food web and qualitatively assessed the relative sensitivity of groups. Using this information, we created a stressor-response matrix of positive and negative direct effects of each stressor-functional group combination. Fungicides, salinization, and sedimentation were identified as particularly detrimental to most groups, although destructive management practices, such as dredging with almost complete community removal, would take precedence depending on frequency. Using the stressor-response matrix we built, first, a series of conceptual null models of single stressor effects on food web structure and, second, a series of additive null models to illustrate potential paired-stressor effects. We compared these additive null models with published studies of the same pairs of combined single stressors to explore more complex interactions. Our approach serves as a first-step to considering multiple stressor scenarios in systems that are understudied or data-poor and as a baseline from which more complex models that include indirect effects and quantitative data may be developed. We make specific suggestions for appropriate management strategies that could be taken to support the biodiversity of these systems for individual stressors and their combined impacts.

A workshop was held in Wageningen, The Netherlands, in September 2017 to collate data and literature on three aquatic ecosystem types (agricultural drainage ditches, urban floodplains, and urban estuaries), and develop a general framework for the assessment of multiple stressors on the structure and functioning of these systems. An assessment framework considering multiple stressors is crucial for our understanding of ecosystem responses within a multiply stressed environment, and to inform appropriate environmental management strategies. The framework consists of two components: (i) problem identification and (ii) impact assessment. Both assessments together proceed through the following steps: 1) ecosystem selection; 2) identification of stressors and quantification of their intensity; 3) identification of receptors or sensitive groups for each stressor; 4) identification of stressor-response relationships and their potential interactions; 5) construction of an ecological model that includes relevant functional groups and endpoints; 6) prediction of impacts of multiple stressors, 7) confirmation of these predictions with experimental and monitoring data, and 8) potential adjustment of the ecological model. Steps 7 and 8 allow the assessment to be adaptive and can be repeated until a satisfactory match between model predictions and experimental and monitoring data has been obtained. This paper is the preface of the MAEGA (Making Aquatic Ecosystems Great Again) special section that includes three associated papers which are also published in this volume, which present applications of the framework for each of the three aquatic systems.

Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.

Ecological networks are powerful tools for visualizing biodiversity data and assessing ecosystem health and function. Constructing these networks requires considerable empirical efforts, and this remains highly challenging due to sampling limitations and the laborious and notoriously limited, error-prone process of traditional taxonomic identification. Recent advancements in high-throughput gene sequencing and high-performance computing provide new ways to address these challenges. DNA metabarcoding, a method of bulk taxonomic identification from DNA extracted from environmental samples, can generate detailed biodiversity information through a standardizable analytical pipeline for species detection. When this biodiversity information is annotated with prior knowledge on taxon interactions, body size, and trophic position, it is possible to generate trait-based networks, which we call “heuristic food webs”. Although curating trait matrices for constructing heuristic food webs is a laborious, often intractable process using manual literature surveys, it can be greatly accelerated via text mining, allowing knowledge of relevant traits to be gathered across large databases. To explore this possibility, we employed a General Architecture for Text Engineering (GATE) system to create a hybrid text-mining pipeline combining rule-based and machine-learning modules. This pipeline was then used to query online repositories of published papers for missing data on a key trait, body size, that could not be gathered from existing trophic link libraries of freshwater benthic macroinvertebrates. Combining text-mined body size information with feeding information from existing sources allowed us to generate a database of over 20,000 pairwise trophic interactions. Next, we developed a pipeline that uses taxa lists generated from DNA metabarcoding and annotates this matrix with trophic information from existing databases and text-mined body size data. In this way, we generated heuristic food webs for wetland sites within a large delta complex formed by the confluence of the Peace and Athabasca rivers in northern Alberta: the Peace–Athabasca delta. Finally, we used these putative food webs and their network properties to resolve spatial and temporal differences between the benthic subwebs of wetlands in the Peace and Athabasca sectors of the delta complex. Specifically, we asked two questions. (1) How do food web properties (e.g. number of links, linkage density, trophic height) differ between the wetlands of the Peace and Athabasca deltas? (2) How do food web properties change temporally in wetlands of the two deltas? We discuss using DNA-generated, trait-based food webs as a powerful tool for rapid bioassessment, assess the limitations of our current approach, and outline a path forward to make this powerful tool more widely available for land managers and conservation biologists.

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services., This Perspective is a product of the EO-BESS Working Group, organized by H.B., D.R. and B.C. and funded by the UK Natural Environment Research Council.

1. Climate change represents a major challenge for conservation in the future and undermines protection within reserve boundaries. Freshwater biodiversity is still under-represented within reserves world-wide, and connectivity among reserves will become increasingly crucial if species are to persist under climate change. 2. We tested the likely benefits of including predicted species distributions in systematic reserve design for rivers under climate change and the impact of varying connectivity requirements on future representation. 3. We used the modelled distribution of 126 east Australian Odonata to identify reserve networks using data for current or future (2055 and 2085) distributions either by filling gaps additively, or as separate targets in a single solution. We then assessed the potential improvements to species representation in the future using different types of connectivity penalties that emphasized either longitudinal riverine connections or connections to all neighbouring subcatchments. 4. Solutions that did not include future distributions in the planning stages were 16 to 30% less likely to protect the same species by 2055 and 2085, respectively. Inclusion of species' future distributions in the design phase leads to short-term increases in cost, but in the longer term fewer additional areas are required to meet targets and this strategy is likely to be significantly more efficient than implementing systematic design in stages. In addition, solely targeting riverine connectivity was significantly less likely to protect current species in the future than if cross-catchment connections were included. 5. Synthesis and applications. Where protected areas can be expanded to assist species adaptation to climate change, significant gains in efficiency are possible if longer term goals are considered when selecting sites. Furthermore, to improve the representation of species under future climates, reserve selection should consider inter-catchment connectivity, although the nature of optimal solutions will depend heavily on the range of taxa included, their dispersal capacity, and the availability of climatic refugia.

Land‐use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land‐use mapping. Assessments of land‐use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land‐use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land‐use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km2) estimates of five land‐use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio‐realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine‐grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land‐use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio‐realms produced global fine‐grained layers from the 2005 time step of the Land‐use Harmonization dataset. Coarse‐scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R 2: 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land‐use layers improved discrimination of all five classes at PREDICTS sites (P

Aim Freshwater ecosystems are highly vulnerable to the effects of climate change. Where long‐term datasets are available, shifts in species phenology, species distributions and community structure consistent with a climate change signal have already been observed. Identifying trends across the wider landscape, to guide management in response to this threat, is limited by the resolution of sampling. Standard biomonitoring of macroinvertebrates for water‐quality purposes is currently not well suited to the detection of climate change effects, and there are risks that substantial changes will occur before a management response can be made. This study investigated whether dragonflies, frequently recommended as general indicators of ecological health, are also suitable as indicators of climate change. Location Data were analysed from standard bio‐assessment monitoring at over 850 sites spanning a 9° latitudinal gradient in eastern Australia. Methods Using variation partitioning, we analysed the proportion of assemblage turnover in dragonflies and other macroinvertebrate assemblages that can be explained by climate and other environmental drivers. We also tested whether the utility of dragonflies as indicators improved at higher taxonomic resolution and whether the turnover of dragonfly assemblages was congruent with that of other groups. Results Climate explained three times as much variation in turnover of dragonfly species than dragonfly and other macroinvertebrate assemblages at family level. The dissimilarity of dragonflies and varying turnover in each macroinvertebrate assemblage meant surrogacy amongst groups were low. Main conclusions On the basis of the influence of climate on turnover of macroinvertebrate assemblages, dragonfly species distribution appears highly sensitive to climatic factors, making this taxon a potential useful indicator of climate change responses. However, the low surrogacy amongst assemblages also suggests that a shift in the focus of conservation management from specific taxa to the functional composition of assemblages across a diverse range of habitats is needed.

Summary 1. As the climate changes, species are expected to shift to higher latitudes and altitudes where suitable habitat is available if dispersal is not constrained by geographic barriers. We analyse patterns of turnover in freshwater macroinvertebrate assemblages to identify which communities are most likely to be at risk from climate change, and the location of geographic barriers that could impede such adaptive range shifts. 2. We analysed macroinvertebrate data from standard biological assessments at the family level, from surveys of all coastal basins of New South Wales, Australia, covering a latitudinal gradient of more than 1000 km. We used variance partitioning to separate the variation in composition explained by climate, among-site distance, human disturbance and other stream factors. 3. Montane stream assemblages showed high turnover in response to climatic variation. Turnover in coastal-fringe streams was least affected by climate, but strongly correlated with distance and stream variables. Significant shifts in assemblage composition occurred between habitats within catchments and across catchment boundaries. 4. Montane stream assemblages are most vulnerable to climate change because their distribution is most responsive to climatic factors, and elevated sites are isolated from one another, reducing the scope for altitudinal migration. Dispersal limitations in coastal-fringe assemblages will also increase their vulnerability to habitat loss from sea-level rise. For all stream classes, the separation of many neighbouring catchment assemblages, owing to either limited dispersal or the lack of suitable habitat, is likely to constrain adaptive range shifts. This would lead to an overall reduction in beta diversity among reaches and subsequently to a reduction in landscape-level gamma diversity.

SummaryAdnectins are targeted biologics derived from the tenth type III domain of human fibronectin (10Fn3), a member of the immunoglobulin superfamily. Target-specific binders are selected from libraries generated by diversifying the three 10Fn3 loops that are analogous to the complementarity determining regions of antibodies. The crystal structures of two Adnectins were determined, each in complex with its therapeutic target, EGFR or IL-23. Both Adnectins bind different epitopes than those bound by known monoclonal antibodies. Molecular modeling suggests that some of these epitopes might not be accessible to antibodies because of the size and concave shape of the antibody combining site. In addition to interactions from the Adnectin diversified loops, residues from the N terminus and/or the β strands interact with the target proteins in both complexes. Alanine-scanning mutagenesis confirmed the calculated binding energies of these β strand interactions, indicating that these nonloop residues can expand the available binding footprint.

There are two major competing explanations for the counter-intuitive presence of bright coloration in certain orb-web spiders. Bright coloration could lure insect prey to the web vicinity, increasing the spider's foraging success. Alternatively, the markings could function as disruptive camouflage, making it difficult for the insect prey to distinguish spiders from background colour variation. We measured the prey capture rates of wasp spiders, Argiope bruennichi , that were blacked out, shielded from view using a leaf fragment, or left naturally coloured. Naturally coloured spiders caught over twice the number of prey as did either blacked-out or leaf-shielded spiders, and almost three times as many orthopteran prey. Spectrophotometer measurements suggest that the bright yellow bands on the spider's abdomen are visible to insect prey, but not the banding on the legs, which could disguise the spider's outline. Thus, our results provide strong support for the hypothesis that bright coloration in the wasp spider acts as a visual lure for insect prey and weak support for the hypothesis that the arrangement of the banding pattern across the spider's body disguises the presence of the spider on the web.

Recently, there has been a surge in interest in how beta-diversity is defined and applied (e.g., [1]). Socolar et al. [2] have rightly recognised the fundamental importance of considering beta-diversity for conserving biodiversity, and clearly explain the various ways in which beta-diversity may respond to contrasting ecological and anthropogenic forces. However, there are many ways in which beta-diversity already underpins much of modern conservation science and practice, although differences in terminology means that this may not always be explicit.

Aim Invertebrates are often overlooked in assessments of climate change impacts. Odonata (dragonflies and damselflies) are a significant component of freshwater macroinvertebrate diversity and are likely to be highly responsive to a changing climate. We investigate whether climate change could lead to significant alteration of continental patterns of diversity and whether vulnerable species are taxonomically clustered. Location Australia. Methods Habitat suitability of 270 odonate species was modelled, and a simplified phylogeny was developed based on taxonomic relationships and expert opinion. These maps were then combined to compare species richness, endemism, taxonomic diversity (TD) and taxonomic endemism (TE) under climate change scenarios, and estimate turnover in species composition. Based on the concentration of vulnerable species in regions associated with Gondwanan relicts, we tested the possibility that a focus on species loss would underestimate loss of evolutionary diversity. Results Species richness of Australian Odonata is concentrated in the Wet Tropics, central‐north Australia and south‐east Queensland. Several additional regions support endemic assemblages, including the Victorian alpine region, the Pilbara and far south‐western Australia. Major shifts in composition are expected across most of the east coast in response to climate change, and Tasmania has the potential to become a major refuge for mainland species. For many regions, the loss of TD is greater than expected based on the changes in species richness, and the loss of suitable habitat was unevenly distributed among families. However, the potential loss of evolutionary diversity among vulnerable species was not significantly different from random. Main conclusions The major shifts in the distribution of Australian odonate diversity predicted to occur under climate change imply major challenges for conservation of freshwater biodiversity overall. Although major evolutionary losses may be avoided, climate change is still a serious threat to Australia's Odonata and poses an even greater threat to Australian freshwater biodiversity as a whole.

Climate change is expected to have substantial impacts on the composition of freshwater communities, and many species are threatened by the loss of climatically suitable habitat. In this study we identify Australian Odonata (dragonflies and damselflies) vulnerable to the effects of climate change on the basis of exposure, sensitivity and pressure to disperse in the future. We used an ensemble of species distribution models to predict the distribution of 270 (85%) species of Australian Odonata, continent-wide at the subcatchment scale, and for both current and future climates using two emissions scenarios each for 2055 and 2085. Exposure was scored according to the departure of temperature, precipitation and hydrology from current conditions. Sensitivity accounted for change in the area and suitability of projected climatic habitat, and pressure to disperse combined measurements of average habitat shifts and the loss experienced with lower dispersal rates. Streams and rivers important to future conservation efforts were identified based on the sensitivity-weighted sum of habitat suitability for the most vulnerable species. The overall extent of suitable habitat declined for 56-69% of the species modelled by 2085 depending on emissions scenario. The proportion of species at risk across all components (exposure, sensitivity, pressure to disperse) varied between 7 and 17% from 2055 to 2085 and a further 3-17% of species were also projected to be at high risk due to declines that did not require range shifts. If dispersal to Tasmania was limited, many south-eastern species are at significantly increased risk. Conservation efforts will need to focus on creating and preserving freshwater refugia as part of a broader conservation strategy that improves connectivity and promotes adaptive range shifts. The significant predicted shifts in suitable habitat could potentially exceed the dispersal capacity of Odonata and highlights the challenge faced by other freshwater species.

Anti-drug antibody (ADA) responses are a concern for both drug efficacy and safety, and high drug concentrations in patient samples may inhibit ADA assays. We evaluated strategies to improve drug tolerance of surface plasmon resonance (SPR) assays that detect ADAs against a bispecific Adnectin drug molecule that consists of an anti-VEGFR2 domain linked to an anti-IGF-1R domain (V-I-Adnectin). Samples containing ADAs against V-I-Adnectin and various drug concentrations were tested in the presence of 1 M guanidine hydrochloride (Gdn), at pH values ranging from 4.5 to 7.4 and temperatures of up to 37 °C. Temperature had a negligible effect in weakening the affinity of interaction of monoclonal antibodies with polyethylene glycol(PEG)–V-I-Adnectin and did not increase drug tolerance of the ADA assay. Low pH increased drug tolerance of the assay relative to pH 7.4 but caused nonspecific binding of the drug during competition experiments. The chaotropic agent Gdn lowered the affinity of interaction between an anti-V-Adnectin monoclonal antibody and the drug (from KD = 0.93 nM to KD = 348 nM). That decrease in the affinity of drug–ADA interaction correlated with an increase of assay drug tolerance. Conditions that lower drug–ADA interaction affinity could also be used to develop drug-tolerant SPR assays for other systems.