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Aim Rivers belong to the most threatened ecosystems on Earth. Historical anthropogenic alterations have, and future climate change will further affect rivers and the species therein. While many studies have projected climate change effects on species, little is known about the severity of these changes compared to historical alterations. Here, we used a unique 300-year time series of hydrological and climate data to explore the vulnerability of 48 native fish species in the upper Danube River Basin to past and potential future environmental changes. Location Upper Danube River Basins (Germany and Austria). Methods We applied a climate niche factor analysis and calculated species-specific vulnerability estimates based on modelled and observed hydrological and climate data from 1800 to 2100. We compared the estimated species vulnerabilities between two historical time intervals (1800–1830 and 1900–1930) and a future time interval (2070–2100, including the two representative concentration pathways 4.5 and 8.5) to an observed reference time interval (1970–2000). In addition, we identified the main environmental drivers of species vulnerability and their change over the past 200 years and for the predicted 100 years in the future. Results Our results showed that (i) in the past, species vulnerability was mainly driven by changes in discharge, while (ii) future potential vulnerabilities would be due to temperature. Moreover, we found that (iii) future environmental conditions for riverine fish species driven by temperature would change at a similar magnitude as past hydrological changes, driven by anthropogenic river alterations. Future changes, projected for the RCP 4.5, would result in moderate species vulnerability, whereas for the RCP 8.5, the vulnerability for all species would substantially increase compared to the historical conditions. Main Conclusion Accounting for an extended timeline uncovers the extent of historical pressures and provides unprecedente

River ecosystem services (rESS) such as the provision of drinking water, fish and other foods, flood protection, or spaces for recreation are important to human well-being. We present methods, tools, and resources for measuring, mapping, assessing, and reporting on status and trends in rESS. Within this framing, we show current approaches to integrate rESS in river basin management and to address the societal implications of trade-offs and synergies between different services, ecosystem processes, and other human uses. We position rESS in the wider context of global policies as e.g. the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the post-2020 biodiversity framework, and the United Nation's Sustainable Development Agenda. Finally, we suggest ways to advance rESS in terms of policy, science and knowledge, and management practice.

Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty‐four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life‐history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges‐Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life‐history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectiv

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards. © 2020, The Author(s).

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90-m digital-elevation model by using the GRASS-GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land-use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1 93.2 and 0.61 0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can h

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty‐four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life‐history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges‐Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life‐history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectiv

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90-m digital-elevation model by using the GRASS-GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land-use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1 93.2 and 0.61 0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can h

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards. © 2020, The Author(s).

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty‐four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life‐history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges‐Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life‐history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectiv

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty‐four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life‐history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges‐Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life‐history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectiv

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards. © 2020, The Author(s).

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90-m digital-elevation model by using the GRASS-GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land-use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1 93.2 and 0.61 0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can h

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requiremen

Intermittent rivers and ephemeral streams (IRES) may represent over half the global stream network, but their contribution to respiration and carbon dioxide (CO2) emissions is largely undetermined. In particular, little is known about the variability and drivers of respiration in IRES sediments upon rewetting, which could result in large pulses of CO2. We present a global study examining sediments from 200 dry IRES reaches spanning multiple biomes. Results from standardized assays show that mean respiration increased 32-fold to 66-fold upon sediment rewetting. Structural equation modeling indicates that this response was driven by sediment texture and organic matter quantity and quality, which, in turn, were influenced by climate, land use, and riparian plant cover. Our estimates suggest that respiration pulses resulting from rewetting of IRES sediments could contribute significantly to annual CO2 emissions from the global stream network, with a single respiration pulse potentially increasing emission by 0.2 0.7%. As the spatial and temporal extent of IRES increases globally, our results highlight the importance of recognizing the influence of wetting-drying cycles on respiration and CO2 emissions in stream networks. (c)2019. American Geophysical Union. All Rights Reserved.

Understanding and predicting the ecological consequences of different management alternatives is becoming increasingly important to support environmental management decisions. Ecological models could contribute to such predictions, but in the past this was often not the case. Ecological models are often developed within research projects but are rarely used for practical applications. In this synthesis paper, we discuss how to strengthen the role of ecological modeling in supporting environmental management decisions with a focus on methodological aspects. We address mainly ecological modellers but also potential users of modeling results. Various modeling approaches can be used to predict the response of ecosystems to anthropogenic interventions, including mechanistic models, statistical models, and machine learning approaches. Regardless of the chosen approach, we outline how to better align the modeling to the decision making process, and identify six requirements that we believe are important to increase the usefulness of ecological models for management support, especially if management decisions need to be justified to the public. These cover: (i) a mechanistic understanding regarding causality, (ii) alignment of model input and output with the management decision, (iii) appropriate spatial and temporal resolutions, (iv) uncertainty quantification, (v) sufficient predictive performance, and (vi) transparent communication. We discuss challenges and synthesize suggestions for addressing these points. © 2019 The Author(s)

Floating matter (FM) is a pivotal, albeit neglected, element along river corridors contributing to their ecological integrity. FM consists of particulate matter of natural (e.g. wood, branches, leaves, seeds) and anthropogenic (e.g. plastic, human waste) origin as well as of organisms that, due to its properties, is able to float on the water surface. In this paper, we provide a comprehensive overview of the FM cycle and the fundamental environmental functions FM provides along rivers. Indeed, FM serves as an important geomorphological agent, a dispersal vector for animals and plant propagules, a habitat, a resource, and a biogeochemical component. Furthermore, we collected data on the amount of FM accumulating at dams and in reservoirs, and related it to key characteristics of the respective catchments. River fragmentation truncates the natural dynamics of FM through its extraction at damming structures, alteration in the flow regime, and low morphological complexity, which may decrease FM retention. Finally, we identify key knowledge gaps in relation to the role FM plays in supporting river integrity, and briefly discuss FM management strategies. (c) 2019, Springer Nature Switzerland AG.

Climate change and human pressures are changing the global distribution and the extent of intermittent rivers and ephemeral streams (IRES), which comprise half of the global river network area. IRES are characterized by periods of flow cessation, during which channel substrates accumulate and undergo physico-chemical changes (preconditioning), and periods of flow resumption, when these substrates are rewetted and release pulses of dissolved nutrients and organic matter (OM). However, there are no estimates of the amounts and quality of leached substances, nor is there information on the underlying environmental constraints operating at the global scale. We experimentally simulated, under standard laboratory conditions, rewetting of leaves, riverbed sediments, and epilithic biofilms collected during the dry phase across 205 IRES from five major climate zones. We determined the amounts and qualitative characteristics of the leached nutrients and OM, and estimated their areal fluxes from riverbeds. In addition, we evaluated the variance in leachate characteristics in relation to selected environmental variables and substrate characteristics. We found that sediments, due to their large quantities within riverbeds, contribute most to the overall flux of dissolved substances during rewetting events (56% 98%), and that flux rates distinctly differ among climate zones. Dissolved organic carbon, phenolics, and nitrate contributed most to the areal fluxes. The largest amounts of leached substances were found in the continental climate zone, coinciding with the lowest potential bioavailability of the leached OM. The opposite pattern was found in the arid zone. Environmental variables expected to be modified under climate change (i.e. potential evapotranspiration, aridity, dry period duration, land use) were correlated with the amount of leached substances, with the strongest relationship found for sediments. These results show that the role of IRES should be accounted for in g

Aim: Systematic conservation planning is vital for allocating protected areas given the spatial distribution of conservation features, such as species. Due to incomplete species inventories, species distribution models (SDMs) are often used for predicting species habitat suitability and species probability of occurrence. Currently, SDMs mostly ignore spatial dependencies in species and predictor data. Here, we provide a comparative evaluation of how accounting for spatial dependencies, that is, autocorrelation, affects the delineation of optimized protected areas. Location: Southeast Australia, Southeast U.S. Continental Shelf, Danube River Basin. Methods: We employ Bayesian spatially explicit and non-spatial SDMs for terrestrial, marine and freshwater species, using realm-specific planning unit shapes (grid, hexagon and subcatchment, respectively). We then apply the software gurobi to optimize conservation plans based on species targets derived from spatial and non-spatial SDMs (10% 50% each to analyse sensitivity), and compare the delineation of the plans. Results: Across realms and irrespective of the planning unit shape, spatially explicit SDMs (a) produce on average more accurate predictions in terms of AUC, TSS, sensitivity and specificity, along with a higher species detection probability. All spatial optimizations meet the species conservation targets. Spatial conservation plans that use predictions from spatially explicit SDMs (b) are spatially substantially different compared to those that use non-spatial SDM predictions, but (c) encompass a similar amount of planning units. The overlap in the selection of planning units is smallest for conservation plans based on the lowest targets and vice versa. Main conclusions: Species distribution models are core tools in conservation planning. Not surprisingly, accounting for the spatial characteristics in SDMs has drastic impacts on the delineation of optimized conservation plans. We therefore encourage practitione

Green and Blue Infrastructure (GBI) is a network designed and planned to deliver a wide range of ecosystem services and to protect biodiversity. Existing GBI designs lacked a systematic method to allocate restoration zones. This study proposes a novel approach for systematically selecting cost-effective areas for restoration on the basis of biodiversity, ecosystem services, and ecosystem condition to give an optimal spatial design of GBI. The approach was tested at a regional scale, in a transboundary setting encompassing the Intercontinental Biosphere Reserve of the Mediterranean in Andalusia (Spain) Morocco (IBRM), across three aquatic ecosystems: freshwater, coastal and marine. We applied Marxan with Zones to stakeholder-defined scenarios of GBI in the IBRM. Specifically, we aimed to identify management zones within the GBl that addressed different conservation, restoration and exploitation objectives. Although almost all conservation targets were achieved, our results highlighted that the proportion of conservation features (i.e., biodiversity, ecosystem services) that would be compromised in the GBl, and the proportion of provisioning services that would be lost due to conservation (i.e., incidental representation) are potentially large, indicating that the probability of conflicts between conservation and exploitation goals in the area is high. The implementation of restoration zones improved connectivity across the GBI, and also achieved European and global policy targets. Our approach may help guide future applications of GBI to implement the flexible conservation management that aquatic environments require, considering many areas at different spatial scales, across multiple ecosystems, and in transboundary contexts. © 2018

Freshwater ecosystems are under a constant risk of being irreversibly damaged by human pressures that threaten their biodiversity, the sustainability of ecosystem services (ESs), and human well-being. Despite the implementation of various environmental regulations, the challenges of safeguarding freshwater assets have so far not been tackled successfully. A promising way forward to stop the loss of freshwater biodiversity and to sustain freshwater-based ESs is by implementing ecosystem-based management (EBM), an environmental planning and adaptive management approach that jointly considers social and ecological needs. Responsible for considerable recent success in sustainably managing and conserving marine ecosystems, EBM has not yet been championed for fresh waters. A major reason for the delayed uptake of EBM in fresh waters is likely to be its complexity, requiring planners to be familiar with the latest developments in a range of different research areas. EBM would therefore benefit from becoming more tangible to receive attention on the ground. To facilitate uptake, eight core research areas for EBM and their innovations are introduced, and the way in which they feed into the workflow that guides the EBM planning stage is explained. The workflow links biodiversity distributions with ES supply-and-demand modelling and SMART (specific, measurable, attainable, relevant, and timely) target planning, including scenario- and cross-realm perspectives, the prioritization of management alternatives, spatial prioritization of biodiversity conservation and ES areas, and the quantification of uncertainties. Given the extensive resources, time, and technical capacity required to implement the full workflow, a light and an ultralight version of the workflow are also provided. Applied in concert, the eight well-known research areas allow for better planning and operationalizing, and eventually for implementing EBM in freshwater ecosystems. EBM has great potential to increase

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requiremen

Freshwater ecosystems are under a constant risk of being irreversibly damaged by human pressures that threaten their biodiversity, the sustainability of ecosystem services (ESs), and human well-being. Despite the implementation of various environmental regulations, the challenges of safeguarding freshwater assets have so far not been tackled successfully. A promising way forward to stop the loss of freshwater biodiversity and to sustain freshwater-based ESs is by implementing ecosystem-based management (EBM), an environmental planning and adaptive management approach that jointly considers social and ecological needs. Responsible for considerable recent success in sustainably managing and conserving marine ecosystems, EBM has not yet been championed for fresh waters. A major reason for the delayed uptake of EBM in fresh waters is likely to be its complexity, requiring planners to be familiar with the latest developments in a range of different research areas. EBM would therefore benefit from becoming more tangible to receive attention on the ground. To facilitate uptake, eight core research areas for EBM and their innovations are introduced, and the way in which they feed into the workflow that guides the EBM planning stage is explained. The workflow links biodiversity distributions with ES supply-and-demand modelling and SMART (specific, measurable, attainable, relevant, and timely) target planning, including scenario- and cross-realm perspectives, the prioritization of management alternatives, spatial prioritization of biodiversity conservation and ES areas, and the quantification of uncertainties. Given the extensive resources, time, and technical capacity required to implement the full workflow, a light and an ultralight version of the workflow are also provided. Applied in concert, the eight well-known research areas allow for better planning and operationalizing, and eventually for implementing EBM in freshwater ecosystems. EBM has great potential to increase

Intermittent rivers and ephemeral streams (IRES) may represent over half the global stream network, but their contribution to respiration and carbon dioxide (CO2) emissions is largely undetermined. In particular, little is known about the variability and drivers of respiration in IRES sediments upon rewetting, which could result in large pulses of CO2. We present a global study examining sediments from 200 dry IRES reaches spanning multiple biomes. Results from standardized assays show that mean respiration increased 32-fold to 66-fold upon sediment rewetting. Structural equation modeling indicates that this response was driven by sediment texture and organic matter quantity and quality, which, in turn, were influenced by climate, land use, and riparian plant cover. Our estimates suggest that respiration pulses resulting from rewetting of IRES sediments could contribute significantly to annual CO2 emissions from the global stream network, with a single respiration pulse potentially increasing emission by 0.2 0.7%. As the spatial and temporal extent of IRES increases globally, our results highlight the importance of recognizing the influence of wetting-drying cycles on respiration and CO2 emissions in stream networks. (c)2019. American Geophysical Union. All Rights Reserved.

Green and Blue Infrastructure (GBI) is a network designed and planned to deliver a wide range of ecosystem services and to protect biodiversity. Existing GBI designs lacked a systematic method to allocate restoration zones. This study proposes a novel approach for systematically selecting cost-effective areas for restoration on the basis of biodiversity, ecosystem services, and ecosystem condition to give an optimal spatial design of GBI. The approach was tested at a regional scale, in a transboundary setting encompassing the Intercontinental Biosphere Reserve of the Mediterranean in Andalusia (Spain) Morocco (IBRM), across three aquatic ecosystems: freshwater, coastal and marine. We applied Marxan with Zones to stakeholder-defined scenarios of GBI in the IBRM. Specifically, we aimed to identify management zones within the GBl that addressed different conservation, restoration and exploitation objectives. Although almost all conservation targets were achieved, our results highlighted that the proportion of conservation features (i.e., biodiversity, ecosystem services) that would be compromised in the GBl, and the proportion of provisioning services that would be lost due to conservation (i.e., incidental representation) are potentially large, indicating that the probability of conflicts between conservation and exploitation goals in the area is high. The implementation of restoration zones improved connectivity across the GBI, and also achieved European and global policy targets. Our approach may help guide future applications of GBI to implement the flexible conservation management that aquatic environments require, considering many areas at different spatial scales, across multiple ecosystems, and in transboundary contexts. © 2018

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requiremen

Floating matter (FM) is a pivotal, albeit neglected, element along river corridors contributing to their ecological integrity. FM consists of particulate matter of natural (e.g. wood, branches, leaves, seeds) and anthropogenic (e.g. plastic, human waste) origin as well as of organisms that, due to its properties, is able to float on the water surface. In this paper, we provide a comprehensive overview of the FM cycle and the fundamental environmental functions FM provides along rivers. Indeed, FM serves as an important geomorphological agent, a dispersal vector for animals and plant propagules, a habitat, a resource, and a biogeochemical component. Furthermore, we collected data on the amount of FM accumulating at dams and in reservoirs, and related it to key characteristics of the respective catchments. River fragmentation truncates the natural dynamics of FM through its extraction at damming structures, alteration in the flow regime, and low morphological complexity, which may decrease FM retention. Finally, we identify key knowledge gaps in relation to the role FM plays in supporting river integrity, and briefly discuss FM management strategies. (c) 2019, Springer Nature Switzerland AG.

Climate change and human pressures are changing the global distribution and the extent of intermittent rivers and ephemeral streams (IRES), which comprise half of the global river network area. IRES are characterized by periods of flow cessation, during which channel substrates accumulate and undergo physico-chemical changes (preconditioning), and periods of flow resumption, when these substrates are rewetted and release pulses of dissolved nutrients and organic matter (OM). However, there are no estimates of the amounts and quality of leached substances, nor is there information on the underlying environmental constraints operating at the global scale. We experimentally simulated, under standard laboratory conditions, rewetting of leaves, riverbed sediments, and epilithic biofilms collected during the dry phase across 205 IRES from five major climate zones. We determined the amounts and qualitative characteristics of the leached nutrients and OM, and estimated their areal fluxes from riverbeds. In addition, we evaluated the variance in leachate characteristics in relation to selected environmental variables and substrate characteristics. We found that sediments, due to their large quantities within riverbeds, contribute most to the overall flux of dissolved substances during rewetting events (56% 98%), and that flux rates distinctly differ among climate zones. Dissolved organic carbon, phenolics, and nitrate contributed most to the areal fluxes. The largest amounts of leached substances were found in the continental climate zone, coinciding with the lowest potential bioavailability of the leached OM. The opposite pattern was found in the arid zone. Environmental variables expected to be modified under climate change (i.e. potential evapotranspiration, aridity, dry period duration, land use) were correlated with the amount of leached substances, with the strongest relationship found for sediments. These results show that the role of IRES should be accounted for in g

Aim: Systematic conservation planning is vital for allocating protected areas given the spatial distribution of conservation features, such as species. Due to incomplete species inventories, species distribution models (SDMs) are often used for predicting species habitat suitability and species probability of occurrence. Currently, SDMs mostly ignore spatial dependencies in species and predictor data. Here, we provide a comparative evaluation of how accounting for spatial dependencies, that is, autocorrelation, affects the delineation of optimized protected areas. Location: Southeast Australia, Southeast U.S. Continental Shelf, Danube River Basin. Methods: We employ Bayesian spatially explicit and non-spatial SDMs for terrestrial, marine and freshwater species, using realm-specific planning unit shapes (grid, hexagon and subcatchment, respectively). We then apply the software gurobi to optimize conservation plans based on species targets derived from spatial and non-spatial SDMs (10% 50% each to analyse sensitivity), and compare the delineation of the plans. Results: Across realms and irrespective of the planning unit shape, spatially explicit SDMs (a) produce on average more accurate predictions in terms of AUC, TSS, sensitivity and specificity, along with a higher species detection probability. All spatial optimizations meet the species conservation targets. Spatial conservation plans that use predictions from spatially explicit SDMs (b) are spatially substantially different compared to those that use non-spatial SDM predictions, but (c) encompass a similar amount of planning units. The overlap in the selection of planning units is smallest for conservation plans based on the lowest targets and vice versa. Main conclusions: Species distribution models are core tools in conservation planning. Not surprisingly, accounting for the spatial characteristics in SDMs has drastic impacts on the delineation of optimized conservation plans. We therefore encourage practitione

Understanding and predicting the ecological consequences of different management alternatives is becoming increasingly important to support environmental management decisions. Ecological models could contribute to such predictions, but in the past this was often not the case. Ecological models are often developed within research projects but are rarely used for practical applications. In this synthesis paper, we discuss how to strengthen the role of ecological modeling in supporting environmental management decisions with a focus on methodological aspects. We address mainly ecological modellers but also potential users of modeling results. Various modeling approaches can be used to predict the response of ecosystems to anthropogenic interventions, including mechanistic models, statistical models, and machine learning approaches. Regardless of the chosen approach, we outline how to better align the modeling to the decision making process, and identify six requirements that we believe are important to increase the usefulness of ecological models for management support, especially if management decisions need to be justified to the public. These cover: (i) a mechanistic understanding regarding causality, (ii) alignment of model input and output with the management decision, (iii) appropriate spatial and temporal resolutions, (iv) uncertainty quantification, (v) sufficient predictive performance, and (vi) transparent communication. We discuss challenges and synthesize suggestions for addressing these points. © 2019 The Author(s)

Global aquatic biodiversity keeps declining rapidly, despite international efforts providing a variety of policies and legislations that identify goals for, and give directions to protecting the world's aquatic fauna and flora. With the H2020 project AQUACROSS, we have made an unprecedented effort to unify policy strategies, knowledge, and management concepts of freshwater, coastal, and marine ecosystems to support the achievement of the targets set by the EU Biodiversity Strategy to 2020. AQUACROSS has embraced the concept of ecosystem-based management (EBM), which approaches environmental management from a social-ecological system perspective to protect biodiversity and to sustainably harvest ecosystem services. This special issue includes contributions resulting from AQUACROSS, which either tackle selected EBM challenges from a theoretical point of view or apply EBM in one of the selected case studies across Europe. In this article, we introduce relevant topics, address the most important lessons learnt, and suggest where research should go with aquatic EBM. We hope that this special issue will foster and facilitate the uptake of EBM in aquatic ecosystems and, therewith, provide the on-ground applications needed for evaluating EBM's utility to safeguard aquatic biodiversity. © 2019

Freshwater ecosystems are under a constant risk of being irreversibly damaged by human pressures that threaten their biodiversity, the sustainability of ecosystem services (ESs), and human well-being. Despite the implementation of various environmental regulations, the challenges of safeguarding freshwater assets have so far not been tackled successfully. A promising way forward to stop the loss of freshwater biodiversity and to sustain freshwater-based ESs is by implementing ecosystem-based management (EBM), an environmental planning and adaptive management approach that jointly considers social and ecological needs. Responsible for considerable recent success in sustainably managing and conserving marine ecosystems, EBM has not yet been championed for fresh waters. A major reason for the delayed uptake of EBM in fresh waters is likely to be its complexity, requiring planners to be familiar with the latest developments in a range of different research areas. EBM would therefore benefit from becoming more tangible to receive attention on the ground. To facilitate uptake, eight core research areas for EBM and their innovations are introduced, and the way in which they feed into the workflow that guides the EBM planning stage is explained. The workflow links biodiversity distributions with ES supply-and-demand modelling and SMART (specific, measurable, attainable, relevant, and timely) target planning, including scenario- and cross-realm perspectives, the prioritization of management alternatives, spatial prioritization of biodiversity conservation and ES areas, and the quantification of uncertainties. Given the extensive resources, time, and technical capacity required to implement the full workflow, a light and an ultralight version of the workflow are also provided. Applied in concert, the eight well-known research areas allow for better planning and operationalizing, and eventually for implementing EBM in freshwater ecosystems. EBM has great potential to increase

Climate change and human pressures are changing the global distribution and the extent of intermittent rivers and ephemeral streams (IRES), which comprise half of the global river network area. IRES are characterized by periods of flow cessation, during which channel substrates accumulate and undergo physico-chemical changes (preconditioning), and periods of flow resumption, when these substrates are rewetted and release pulses of dissolved nutrients and organic matter (OM). However, there are no estimates of the amounts and quality of leached substances, nor is there information on the underlying environmental constraints operating at the global scale. We experimentally simulated, under standard laboratory conditions, rewetting of leaves, riverbed sediments, and epilithic biofilms collected during the dry phase across 205 IRES from five major climate zones. We determined the amounts and qualitative characteristics of the leached nutrients and OM, and estimated their areal fluxes from riverbeds. In addition, we evaluated the variance in leachate characteristics in relation to selected environmental variables and substrate characteristics. We found that sediments, due to their large quantities within riverbeds, contribute most to the overall flux of dissolved substances during rewetting events (56% 98%), and that flux rates distinctly differ among climate zones. Dissolved organic carbon, phenolics, and nitrate contributed most to the areal fluxes. The largest amounts of leached substances were found in the continental climate zone, coinciding with the lowest potential bioavailability of the leached OM. The opposite pattern was found in the arid zone. Environmental variables expected to be modified under climate change (i.e. potential evapotranspiration, aridity, dry period duration, land use) were correlated with the amount of leached substances, with the strongest relationship found for sediments. These results show that the role of IRES should be accounted for in g

Green and Blue Infrastructure (GBI) is a network designed and planned to deliver a wide range of ecosystem services and to protect biodiversity. Existing GBI designs lacked a systematic method to allocate restoration zones. This study proposes a novel approach for systematically selecting cost-effective areas for restoration on the basis of biodiversity, ecosystem services, and ecosystem condition to give an optimal spatial design of GBI. The approach was tested at a regional scale, in a transboundary setting encompassing the Intercontinental Biosphere Reserve of the Mediterranean in Andalusia (Spain) Morocco (IBRM), across three aquatic ecosystems: freshwater, coastal and marine. We applied Marxan with Zones to stakeholder-defined scenarios of GBI in the IBRM. Specifically, we aimed to identify management zones within the GBl that addressed different conservation, restoration and exploitation objectives. Although almost all conservation targets were achieved, our results highlighted that the proportion of conservation features (i.e., biodiversity, ecosystem services) that would be compromised in the GBl, and the proportion of provisioning services that would be lost due to conservation (i.e., incidental representation) are potentially large, indicating that the probability of conflicts between conservation and exploitation goals in the area is high. The implementation of restoration zones improved connectivity across the GBI, and also achieved European and global policy targets. Our approach may help guide future applications of GBI to implement the flexible conservation management that aquatic environments require, considering many areas at different spatial scales, across multiple ecosystems, and in transboundary contexts. © 2018

Understanding and predicting the ecological consequences of different management alternatives is becoming increasingly important to support environmental management decisions. Ecological models could contribute to such predictions, but in the past this was often not the case. Ecological models are often developed within research projects but are rarely used for practical applications. In this synthesis paper, we discuss how to strengthen the role of ecological modeling in supporting environmental management decisions with a focus on methodological aspects. We address mainly ecological modellers but also potential users of modeling results. Various modeling approaches can be used to predict the response of ecosystems to anthropogenic interventions, including mechanistic models, statistical models, and machine learning approaches. Regardless of the chosen approach, we outline how to better align the modeling to the decision making process, and identify six requirements that we believe are important to increase the usefulness of ecological models for management support, especially if management decisions need to be justified to the public. These cover: (i) a mechanistic understanding regarding causality, (ii) alignment of model input and output with the management decision, (iii) appropriate spatial and temporal resolutions, (iv) uncertainty quantification, (v) sufficient predictive performance, and (vi) transparent communication. We discuss challenges and synthesize suggestions for addressing these points. © 2019 The Author(s)

Intermittent rivers and ephemeral streams (IRES) may represent over half the global stream network, but their contribution to respiration and carbon dioxide (CO2) emissions is largely undetermined. In particular, little is known about the variability and drivers of respiration in IRES sediments upon rewetting, which could result in large pulses of CO2. We present a global study examining sediments from 200 dry IRES reaches spanning multiple biomes. Results from standardized assays show that mean respiration increased 32-fold to 66-fold upon sediment rewetting. Structural equation modeling indicates that this response was driven by sediment texture and organic matter quantity and quality, which, in turn, were influenced by climate, land use, and riparian plant cover. Our estimates suggest that respiration pulses resulting from rewetting of IRES sediments could contribute significantly to annual CO2 emissions from the global stream network, with a single respiration pulse potentially increasing emission by 0.2 0.7%. As the spatial and temporal extent of IRES increases globally, our results highlight the importance of recognizing the influence of wetting-drying cycles on respiration and CO2 emissions in stream networks. (c)2019. American Geophysical Union. All Rights Reserved.

Aim: Systematic conservation planning is vital for allocating protected areas given the spatial distribution of conservation features, such as species. Due to incomplete species inventories, species distribution models (SDMs) are often used for predicting species habitat suitability and species probability of occurrence. Currently, SDMs mostly ignore spatial dependencies in species and predictor data. Here, we provide a comparative evaluation of how accounting for spatial dependencies, that is, autocorrelation, affects the delineation of optimized protected areas. Location: Southeast Australia, Southeast U.S. Continental Shelf, Danube River Basin. Methods: We employ Bayesian spatially explicit and non-spatial SDMs for terrestrial, marine and freshwater species, using realm-specific planning unit shapes (grid, hexagon and subcatchment, respectively). We then apply the software gurobi to optimize conservation plans based on species targets derived from spatial and non-spatial SDMs (10% 50% each to analyse sensitivity), and compare the delineation of the plans. Results: Across realms and irrespective of the planning unit shape, spatially explicit SDMs (a) produce on average more accurate predictions in terms of AUC, TSS, sensitivity and specificity, along with a higher species detection probability. All spatial optimizations meet the species conservation targets. Spatial conservation plans that use predictions from spatially explicit SDMs (b) are spatially substantially different compared to those that use non-spatial SDM predictions, but (c) encompass a similar amount of planning units. The overlap in the selection of planning units is smallest for conservation plans based on the lowest targets and vice versa. Main conclusions: Species distribution models are core tools in conservation planning. Not surprisingly, accounting for the spatial characteristics in SDMs has drastic impacts on the delineation of optimized conservation plans. We therefore encourage practitione

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requiremen

Floating matter (FM) is a pivotal, albeit neglected, element along river corridors contributing to their ecological integrity. FM consists of particulate matter of natural (e.g. wood, branches, leaves, seeds) and anthropogenic (e.g. plastic, human waste) origin as well as of organisms that, due to its properties, is able to float on the water surface. In this paper, we provide a comprehensive overview of the FM cycle and the fundamental environmental functions FM provides along rivers. Indeed, FM serves as an important geomorphological agent, a dispersal vector for animals and plant propagules, a habitat, a resource, and a biogeochemical component. Furthermore, we collected data on the amount of FM accumulating at dams and in reservoirs, and related it to key characteristics of the respective catchments. River fragmentation truncates the natural dynamics of FM through its extraction at damming structures, alteration in the flow regime, and low morphological complexity, which may decrease FM retention. Finally, we identify key knowledge gaps in relation to the role FM plays in supporting river integrity, and briefly discuss FM management strategies. (c) 2019, Springer Nature Switzerland AG.

Aim: Freshwater megafauna remain underrepresented in research and conservation, despite a disproportionately high risk of extinction due to multiple human threats. Therefore, our aims are threefold; (i) identify global patterns of freshwater megafauna richness and endemism, (ii) assess the conservation status of freshwater megafauna and (iii) demonstrate spatial and temporal patterns of human pressure throughout their distribution ranges. Location: Global. Methods: We identified 207 extant freshwater megafauna species, based on a 30 kg weight threshold, and mapped their distributions using HydroBASINS subcatchments (level 8). Information on conservation status and population trends for each species was extracted from the IUCN Red List website. We investigated human impacts on freshwater megafauna in space and time by examining spatial congruence between their distributions and human pressures, described by the Incident Biodiversity Threat Index and Temporal Human Pressure Index. Results: Freshwater megafauna occur in 76% of the world s main river basins (level 3 HydroBASINS), with species richness peaking in the Amazon, Congo, Orinoco, Mekong and Ganges-Brahmaputra basins. Freshwater megafauna are more threatened than their smaller counterparts within the specific taxonomic groups (i.e., fishes, mammals, reptiles and amphibians). Out of the 93 freshwater megafauna species with known population trends, 71% are in decline. Meanwhile, IUCN Red List assessments reported insufficient or outdated data for 43% of all freshwater megafauna species. Since the early 1990s, human pressure has increased throughout 63% of their distribution ranges, with particularly intense impacts occurring in the Mekong and Ganges-Brahmaputra basins. Main conclusions: Freshwater megafauna species are threatened globally, with intense and increasing human pressures occurring in many of their biodiversity hotspots. We call for research and conservation actions for freshwater megafauna, as they ar

The world´s largest network of protected areas Natura 2000 (N2000) has been implemented to protect Europe´s biodiversity. N2000 is built upon two cornerstones, the Birds Directive, which lists 691 bird species (plus one additional bird genus with no further classification) and the Habitats Directive, which lists next to a variety of species, 233 habitat types to be protected. There is evidence of the positive impact of the Directives on the EU´s biodiversity, although the overall improvement reported for species in favourable condition in the last assessment was low. However, most of the assessments are species focused, while habitats have received very little attention. Here we developed a generic workflow, which we exemplified for Germany, to assess the status of habitat coverage within the N2000 network combining information from publicly available data sources. Applying the workflow allows identification of gaps in habitat protection, followed by the prioritization of potential areas of high protection value using the conservation planning software Marxan. We found that, in Germany, N2000 covers all target habitats. However, common habitats were proportionally underrepresented relative to rare ones, which contrasts with studies focussing on the representation of species. Moreover, the German case study suggests that especially highly protected areas (i.e. covered by more than 90% with N2000 sites) build an excellent basis towards a cost-effective and efficient conservation network. Our workflow provides a generic approach to deal with the common problem of missing habitat distribution data outside of N2000 sites, information which is however crucial for managers to plan conservation actions appropriately across Europe. To avoid a biased representation of habitat types within N2000, our results underpin the importance of defining qualitative and quantitative conservation targets which will allow assesment of the trajectory of habitat protection in Europe as well

Aim: Freshwater megafauna remain underrepresented in research and conservation, despite a disproportionately high risk of extinction due to multiple human threats. Therefore, our aims are threefold; (i) identify global patterns of freshwater megafauna richness and endemism, (ii) assess the conservation status of freshwater megafauna and (iii) demonstrate spatial and temporal patterns of human pressure throughout their distribution ranges. Location: Global. Methods: We identified 207 extant freshwater megafauna species, based on a 30 kg weight threshold, and mapped their distributions using HydroBASINS subcatchments (level 8). Information on conservation status and population trends for each species was extracted from the IUCN Red List website. We investigated human impacts on freshwater megafauna in space and time by examining spatial congruence between their distributions and human pressures, described by the Incident Biodiversity Threat Index and Temporal Human Pressure Index. Results: Freshwater megafauna occur in 76% of the world s main river basins (level 3 HydroBASINS), with species richness peaking in the Amazon, Congo, Orinoco, Mekong and Ganges-Brahmaputra basins. Freshwater megafauna are more threatened than their smaller counterparts within the specific taxonomic groups (i.e., fishes, mammals, reptiles and amphibians). Out of the 93 freshwater megafauna species with known population trends, 71% are in decline. Meanwhile, IUCN Red List assessments reported insufficient or outdated data for 43% of all freshwater megafauna species. Since the early 1990s, human pressure has increased throughout 63% of their distribution ranges, with particularly intense impacts occurring in the Mekong and Ganges-Brahmaputra basins. Main conclusions: Freshwater megafauna species are threatened globally, with intense and increasing human pressures occurring in many of their biodiversity hotspots. We call for research and conservation actions for freshwater megafauna, as they ar

The world´s largest network of protected areas Natura 2000 (N2000) has been implemented to protect Europe´s biodiversity. N2000 is built upon two cornerstones, the Birds Directive, which lists 691 bird species (plus one additional bird genus with no further classification) and the Habitats Directive, which lists next to a variety of species, 233 habitat types to be protected. There is evidence of the positive impact of the Directives on the EU´s biodiversity, although the overall improvement reported for species in favourable condition in the last assessment was low. However, most of the assessments are species focused, while habitats have received very little attention. Here we developed a generic workflow, which we exemplified for Germany, to assess the status of habitat coverage within the N2000 network combining information from publicly available data sources. Applying the workflow allows identification of gaps in habitat protection, followed by the prioritization of potential areas of high protection value using the conservation planning software Marxan. We found that, in Germany, N2000 covers all target habitats. However, common habitats were proportionally underrepresented relative to rare ones, which contrasts with studies focussing on the representation of species. Moreover, the German case study suggests that especially highly protected areas (i.e. covered by more than 90% with N2000 sites) build an excellent basis towards a cost-effective and efficient conservation network. Our workflow provides a generic approach to deal with the common problem of missing habitat distribution data outside of N2000 sites, information which is however crucial for managers to plan conservation actions appropriately across Europe. To avoid a biased representation of habitat types within N2000, our results underpin the importance of defining qualitative and quantitative conservation targets which will allow assesment of the trajectory of habitat protection in Europe as well

Aim: Freshwater megafauna remain underrepresented in research and conservation, despite a disproportionately high risk of extinction due to multiple human threats. Therefore, our aims are threefold; (i) identify global patterns of freshwater megafauna richness and endemism, (ii) assess the conservation status of freshwater megafauna and (iii) demonstrate spatial and temporal patterns of human pressure throughout their distribution ranges. Location: Global. Methods: We identified 207 extant freshwater megafauna species, based on a 30 kg weight threshold, and mapped their distributions using HydroBASINS subcatchments (level 8). Information on conservation status and population trends for each species was extracted from the IUCN Red List website. We investigated human impacts on freshwater megafauna in space and time by examining spatial congruence between their distributions and human pressures, described by the Incident Biodiversity Threat Index and Temporal Human Pressure Index. Results: Freshwater megafauna occur in 76% of the world s main river basins (level 3 HydroBASINS), with species richness peaking in the Amazon, Congo, Orinoco, Mekong and Ganges-Brahmaputra basins. Freshwater megafauna are more threatened than their smaller counterparts within the specific taxonomic groups (i.e., fishes, mammals, reptiles and amphibians). Out of the 93 freshwater megafauna species with known population trends, 71% are in decline. Meanwhile, IUCN Red List assessments reported insufficient or outdated data for 43% of all freshwater megafauna species. Since the early 1990s, human pressure has increased throughout 63% of their distribution ranges, with particularly intense impacts occurring in the Mekong and Ganges-Brahmaputra basins. Main conclusions: Freshwater megafauna species are threatened globally, with intense and increasing human pressures occurring in many of their biodiversity hotspots. We call for research and conservation actions for freshwater megafauna, as they ar

The world´s largest network of protected areas Natura 2000 (N2000) has been implemented to protect Europe´s biodiversity. N2000 is built upon two cornerstones, the Birds Directive, which lists 691 bird species (plus one additional bird genus with no further classification) and the Habitats Directive, which lists next to a variety of species, 233 habitat types to be protected. There is evidence of the positive impact of the Directives on the EU´s biodiversity, although the overall improvement reported for species in favourable condition in the last assessment was low. However, most of the assessments are species focused, while habitats have received very little attention. Here we developed a generic workflow, which we exemplified for Germany, to assess the status of habitat coverage within the N2000 network combining information from publicly available data sources. Applying the workflow allows identification of gaps in habitat protection, followed by the prioritization of potential areas of high protection value using the conservation planning software Marxan. We found that, in Germany, N2000 covers all target habitats. However, common habitats were proportionally underrepresented relative to rare ones, which contrasts with studies focussing on the representation of species. Moreover, the German case study suggests that especially highly protected areas (i.e. covered by more than 90% with N2000 sites) build an excellent basis towards a cost-effective and efficient conservation network. Our workflow provides a generic approach to deal with the common problem of missing habitat distribution data outside of N2000 sites, information which is however crucial for managers to plan conservation actions appropriately across Europe. To avoid a biased representation of habitat types within N2000, our results underpin the importance of defining qualitative and quantitative conservation targets which will allow assesment of the trajectory of habitat protection in Europe as well