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.
Topographical relief comprises the vertical and horizontal variations of the Earth's terrain and drives processes in geomorphology, biogeography, climatology, hydrology and ecology. Its ...characterisation and assessment, through geomorphometry and feature extraction, is fundamental to numerous environmental modelling and simulation analyses. We, therefore, developed the Geomorpho90m global dataset comprising of different geomorphometric features derived from the MERIT-Digital Elevation Model (DEM) - the best global, high-resolution DEM available. The fully-standardised 26 geomorphometric variables consist of layers that describe the (i) rate of change across the elevation gradient, using first and second derivatives, (ii) ruggedness, and (iii) geomorphological forms. The Geomorpho90m variables are available at 3 (~90 m) and 7.5 arc-second (~250 m) resolutions under the WGS84 geodetic datum, and 100 m spatial resolution under the Equi7 projection. They are useful for modelling applications in fields such as geomorphology, geology, hydrology, ecology and biogeography.
Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully ...standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.
Global declines in biodiversity highlight the need to effectively monitor the density and distribution of threatened species. In recent years, molecular survey methods detecting DNA released by ...target‐species into their environment (eDNA) have been rapidly on the rise. Despite providing new, cost‐effective tools for conservation, eDNA‐based methods are prone to errors. Best field and laboratory practices can mitigate some, but the risks of errors cannot be eliminated and need to be accounted for. Here, we synthesize recent advances in data processing tools that increase the reliability of interpretations drawn from eDNA data. We review advances in occupancy models to consider spatial data‐structures and simultaneously assess rates of false positive and negative results. Further, we introduce process‐based models and the integration of metabarcoding data as complementing approaches to increase the reliability of target‐species assessments. These tools will be most effective when capitalizing on multi‐source data sets collating eDNA with classical survey and citizen‐science approaches, paving the way for more robust decision‐making processes in conservation planning.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Nitrogen (N) and Phosphorus (P) are essential nutritional elements for life processes in water bodies. However, in excessive quantities, they may represent a significant source of aquatic pollution. ...Eutrophication has become a widespread issue rising from a chemical nutrient imbalance and is largely attributed to anthropogenic activities. In view of this phenomenon, we present a new geo-dataset to estimate and map the concentrations of N and P in their various chemical forms at a spatial resolution of 30 arc-second (∼1 km) for the conterminous US. The models were built using Random Forest (RF), a machine learning algorithm that regressed the seasonally measured N and P concentrations collected at 62,495 stations across the US streams for the period of 1994-2018 onto a set of 47 in-house built environmental variables that are available at a near-global extent. The seasonal models were validated through internal and external validation procedures and the predictive powers measured by Pearson Coefficients reached approximately 0.66 on average.
Aim
Understanding variation in biodiversity typically requires consideration of factors operating at different spatial scales. Recently, ecologists and biogeographers have recognized the need of ...analysing ecological communities in the light of multiple facets including not only species‐level information but also functional and phylogenetic approaches to improve our understanding of the relative contribution of processes shaping biodiversity. Here, our aim was to disentangle the relative importance of environmental variables measured at multiple levels (i.e., local, catchment, climate, and spatial variables) influencing variation in macroinvertebrate beta diversity facets (i.e., species, traits, and phylogeny) and their components (i.e., replacement and abundance difference) in boreal streams.
Taxon
Aquatic macroinvertebrates
Location
Western Finland
Methods
A total of 105 streams were sampled in western Finland, encompassing a geographical extent over 500 km. We analysed variation in the different beta diversity facets and components using distance‐based redundancy analysis and associated variation partitioning procedures. We modelled spatial structures using distance‐based Moran eigenvector maps.
Results
We found that the relative influence of explanatory variables on each diversity facet and component revealed relatively similar patterns. Our main finding was that local environmental and spatial variables generally contributed most to the total explained variability in all facets and components of beta diversity, whereas catchment and climate variables explained less variation in the beta diversity facets at the spatial scale considered in this study.
Main conclusions
Different facets of beta diversity were mainly influenced by local environmental variables and spatial structuring, likely acting through deterministic and stochastic pathways respectively. Identifying the ecological variables and mechanisms that drive variation in beta diversity may be used to guide the conservation and restoration efforts for biodiversity under global change.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Summary
1. Freshwater ecosystems will be profoundly affected by global climate change, especially those in mountainous areas, which are known to be particularly vulnerable to warming temperatures. We ...modelled impacts of climate change on the distribution ranges of 38 species of benthic stream macroinvertebrates from nine macroinvertebrate orders covering all river zones from the headwaters to large river reaches.
2. Species altitudinal shifts as well as range changes up to the year 2080 were simulated using the A2a and B2a Intergovernmental Panel on Climate Change climate‐warming scenarios. Presence‐only species distribution models were constructed for a stream network in Germany’s lower mountain ranges by means of consensus projections of four algorithms, as implemented in the BIOMOD package in R (GLM, GAM, GBM and ANN).
3. Species were predicted to shift an average of 122 and 83 m up in altitude along the river continuum by the year 2080 under the A2a and B2a climate‐warming scenarios, respectively. No correlation between altitudinal shifts and mean annual air temperature of species’ occurrence could be detected.
4. Depending on the climate‐warming scenario, most or all (97% for A2a and 100% for B2a) of the macroinvertebrate species investigated were predicted to survive under climate change in the study area. Ranges were predicted to contract for species that currently occur in streams with low annual mean air temperatures but expand for species that inhabit rivers where air temperatures are higher.
5. Our models predict that novel climate conditions will reorganise species composition and community structure along the river continuum. Possible effects are discussed, including significant reductions in population size of headwater species, eventually leading to a loss of genetic diversity. A shift in river species composition is likely to enhance the establishment of non‐native macroinvertebrates in the lower reaches of the river continuum.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Plans are currently being drafted for the next decade of action on biodiversity—both the post‐2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) and Biodiversity ...Strategy of the European Union (EU). Freshwater biodiversity is disproportionately threatened and underprioritized relative to the marine and terrestrial biota, despite supporting a richness of species and ecosystems with their own intrinsic value and providing multiple essential ecosystem services. Future policies and strategies must have a greater focus on the unique ecology of freshwater life and its multiple threats, and now is a critical time to reflect on how this may be achieved. We identify priority topics including environmental flows, water quality, invasive species, integrated water resources management, strategic conservation planning, and emerging technologies for freshwater ecosystem monitoring. We synthesize these topics with decades of first‐hand experience and recent literature into 14 special recommendations for global freshwater biodiversity conservation based on the successes and setbacks of European policy, management, and research. Applying and following these recommendations will inform and enhance the ability of global and European post‐2020 biodiversity agreements to halt and reverse the rapid global decline of freshwater biodiversity.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Freshwater ecosystems harbor specialized and vulnerable biodiversity, and the prediction of potential impacts of freshwater biodiversity to environmental change requires knowledge of the geographic ...and environmental distribution of taxa. To date, however, such quantitative information about freshwater species distributions remains limited. Major impediments include heterogeneity in available species occurrence data, varying detectability of species in their aquatic environment, scarcity of contiguous freshwater-specific predictors, and methods that support addressing these issues in a single framework. Here we demonstrate the use of a hierarchical Bayesian modeling (HBM) framework that combines disparate species occurrence information with newly-developed 1 km freshwater-specific predictors, to account for imperfect species detection and make fine-grain (1 km) estimates of distributions in freshwater organisms. The approach integrates a Bernoulli suitability and a Binomial observability process into a hierarchical zero-inflated Binomial model. The suitability process includes point presence observations, records of site visits, 1 km environmental predictors and expert-derived species range maps integrated with a distance-decay function along the within-stream distance as covariates. The observability process uses repeated observations to estimate a probability of observation given that the species was present. The HBM accounts for the spatial autocorrelation in species habitat suitability projections using an intrinsic Gaussian conditional autoregressive model. We used this framework for three fish species native to different regions and habitats in North America. Model comparison shows that HBMs significantly outperformed non-spatial GLMs in terms of AUC and TSS scores, and that expert information when appropriately included in the model can provide an important refinement. Such ancillary species information and an integrative, hierarchical Bayesian modeling framework can therefore be used to advance fine-grain habitat suitability predictions and range size estimates in the freshwater realm. Our approach is extendable in terms of data availability and generality and can be used on other freshwater organisms and regions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Global climate change (GCC) is expected to lead to massive loss of global biodiversity in the alpine regions of mountain ranges. Studies on the potential effects of GCC on low mountain areas remain ...sparse, however, despite the high conservation value of these areas as biodiversity refugia. We chose a species distribution modeling approach to assess potential GCC impacts on the future distributions of montane freshwater invertebrates under two different greenhouse gas scenarios and three averaged general circulation models. For this, ensemble models consisting of six algorithms generalized linear model (GLM), generalized boosted model (GBM), generalized additive model (GAM), classification tree analysis (CTA), artificial neural networks (ANN), and multivariate adaptive regression splines (MARS) were applied to project areas of 23 cold-stenothermic aquatic insects from montane regions of Central Europe. We found an average loss of 70–80% of the potential distribution for the study species until 2080, depending on the underlying Intergovernmental Panel on Climate Change scenario. Species distribution ranges below 1000 m above sea level were found to decrease by up to ~96% according to the severest greenhouse gas emission scenario. While the Alps remain the single main refugium under the A2a greenhouse gas emission scenario, the more moderate climate scenario B2a shows fragmented potential persistence of montane insects in some low mountain ranges. The results show that montane freshwater assemblages in low mountain ranges are particularly threatened by ongoing GCC. As vertical dispersal is limited by elevational restriction, low mountain ranges may act as summit traps under GCC. We thus propose that GCC will lead to the extinction of several species and unique genetic lineages of postglacial relict species, resulting in a significant decline in Central European fauna.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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