Systematic nature positive markets.

Environmental markets are a rapidly emerging tool to mobilize private funding to incentivize landholders to undertake more sustainable land management. How units of biodiversity in these markets are measured and subsequently traded creates key challenges ecologically and economically because it determines whether environmental markets can deliver net gains in biodiversity and efficiently lower the costs of conservation. We developed and tested a metric for such markets based on the well-established principle of irreplaceability from systematic conservation planning. Irreplaceability as a metric avoids the limitations of like-for-like trading and allows one to capture the multidimensional nature of ecosystems (e.g., habitats, species, ecosystem functioning) and simultaneously achieve cost-effective, land-manager-led investments in conservation. Using an integrated ecological modeling approach, we tested whether using irreplaceability as a metric is more ecologically and economically beneficial than the simpler biodiversity offset metrics typically used in net gain and no-net-loss policies. Using irreplaceability ensured no net loss, or even net gain, of biodiversity depending on the targets chosen. Other metrics did not provide the same assurances and, depending on the flexibility with which biodiversity targets can be achieved, and how they overlap with development pressure, were less efficient. Irreplaceability reduced the costs of offsetting to developers and the costs of ecological restoration to society. Integrating economic data and systematic conservation planning approaches would therefore assure land managers they were being fairly rewarded for the opportunity costs of conservation and transparently incentivize the most ecologically and economically efficient investments in nature recovery.

Mercados sistemáticos que favorecen a la naturaleza Resumen Los mercados ambientales se están convirtiendo rápidamente en una herramienta para movilizar el financiamiento privado que incentiva a los terratenientes a realizar un manejo de suelo más sustentable. La forma de medir las unidades de biodiversidad y su intercambio subsecuente en estos mercados genera retos ecológicos y económicos importantes pues determina si el mercado ambiental puede generar ganancias netas de biodiversidad y reducir eficientemente el costo de la conservación. Desarrollamos y probamos una medida para dichos mercados con base en el principio bien establecido del carácter irremplazable tomado de la planeación sistemática de la conservación. Si se usa como medida, este carácter evita las limitantes del comercio en términos comparables y permite que se capture la naturaleza multidimensional de los ecosistemas (p. ej.: hábitats, especies, funcionamiento) y a la vez consigue inversiones rentables llevadas por el gestor para la conservación. Usamos una estrategia de modelado ecológico integrado para probar si usar el carácter irremplazable como medida tiene más beneficios ecológicos y económicos que las medidas más simples de compensación de la biodiversidad que se usan comúnmente en las políticas sin pérdida neta y de ganancia neta. El uso del carácter irremplazable aseguró que no hubiera pérdida neta o incluso ganancia neta de la biodiversidad según el objetivo elegido. Las otras medidas no proporcionaron la misma seguridad y fueron menos eficientes según la flexibilidad con la cual se logran los objetivos de biodiversidad y cómo se traslapan con la presión del desarrollo. El carácter irremplazable redujo los costos de la compensación para los desarrolladores y los costos de la restauración ecológica para la sociedad. Por lo tanto, la integración de los datos económicos y las estrategias de planeación sistemática de la conservación les asegurarían a los gestores de los terrenos que se les está compensando de manera justa por los costos de oportunidad de conservación e incentivaría con transparencia las inversiones con mayor eficiencia ecológica y económica en la recuperación de la naturaleza.

DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness.

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.

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change.

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.

Novel community data in ecology-properties and prospects.

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

Altering drug tolerance of surface plasmon resonance assays for the detection of anti-drug antibodies.

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 K(D)=0.93 nM to K(D)=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.

'Small Data' for big insights in ecology.

Big Data science has significantly furthered our understanding of complex systems by harnessing large volumes of data, generated at high velocity and in great variety. However, there is a risk that Big Data collection is prioritised to the detriment of 'Small Data' (data with few observations). This poses a particular risk to ecology where Small Data abounds. Machine learning experts are increasingly looking to Small Data to drive the next generation of innovation, leading to development in methods for Small Data such as transfer learning, knowledge graphs, and synthetic data. Meanwhile, meta-analysis and causal reasoning approaches are evolving to provide new insights from Small Data. These advances should add value to high-quality Small Data catalysing future insights for ecology.

Qualifying the effects of single and multiple stressors on the food web structure of Dutch drainage ditches using a literature review and conceptual models.

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.

Towards a general framework for the assessment of interactive effects of multiple stressors on aquatic ecosystems: Results from the Making Aquatic Ecosystems Great Again (MAEGA) workshop.

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.

Function of bright coloration in the wasp spider Argiope bruennichi (Araneae: Araneidae).

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.

Connecting Earth observation to high-throughput biodiversity data.

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.

Downscaling land-use data to provide global 30″ estimates of five land-use classes.

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 km(2)) 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 < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R (2) improvement of 0.12 compared with the Land-use Harmonization data. The downscaling method presented here produced the first global land-use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land-use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse-resolution data for other environmental variables.

Continental-scale assessment of risk to the Australian odonata from climate change.

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.