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Abstract Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in, and deployment of AI-technologies in domains critical for sustainability, few have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We also identify possible systemic risks in these domains including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions, and d) trade-offs between efficiency and resilience. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors.

A thorough understanding of long-term temporal social-ecological dynamics at the national scale helps to explain the current condition of a country’s ecosystems and to support environmental policies to tackle future sustainability challenges. We aimed to develop a methodological approach to understand past long-term (1960-2010) social-ecological dynamics in Spain. First, we developed a methodical framework that allowed us to explore complex social-ecological dynamics among biodiversity, ecosystem services, human well-being, drivers of change, and institutional responses. Second, we compiled 21 long-term, national-scale indicators and analyzed their temporal relationships through a redundancy analysis. Third, we used a Bayesian change point analysis to detect evidence of past social-ecological thresholds and historical time periods. Our results revealed that Spain has passed through four socialecological thresholds that define five different time periods of nature and society relationships. Finally, we discussed how the proposed methodological approach helps to reinterpret national-level ecosystem indicators through a new conceptual lens to develop a more systems-based way of understanding long-term social-ecological patterns and dynamics This work was supported by the Biodiversity Foundation (http://www.fundacion-biodiversidad.es/) of the Spanish Ministry of Agriculture, Food and Environment. Partial financial support was also provided by the Ministry of Economy and Competitiveness of Spain (project CGL2014-53782-P: ECOGRADIENTES). The Spanish National Institute for Agriculture and Food Research and Technology (INIA) funded Marina García-Llorente as part of the European Social Fund. Blanca González García-Mon participated in this article as a “la Caixa” Banking Foundation scholar. The funders had no role in the study design, data collection and analysis, preparation of the report, or the decision to submit the study for publication

In agro-ecosystems, environmental monitoring is fundamental to detect and survey changes related to land use change and management practices. Butterflies and moths have often been suggested as suitable indicators for monitoring environmental effects on biodiversity in farmlands. Here, we estimated the required sample size and monitoring effort necessary to run a Lepidoptera survey in European farmland, assessing in particular if monitoring investment would differ between representative bio-geographical regions.We operated linear 1-km long transect routes in farmland of Romania, Spain and Sweden from 2013 to 2015, and recorded butterflies and burnet moths (Papilionoidea, Zygaenidae). The transects were walked back and forth four times a season, and replicated yearly. The lepidopteran diversity was high in farmlands of Romania and Spain, but comparatively low in Sweden. The coefficient of variation (CV) of recorded species number differed between countries being lowest in Sweden and highest in Spain. In general, the CV dropped above a transect length of 400–800 m, thus indicating an increase in statistical power. Assuming a non-parametric test for matched samples, power calculations were conducted with the raw count data and with log-transformed count data for comparison. When using log-transformed data, the required sample size to detect an effect was less than 10 transects per country or region (in order to detect a 10% loss of species or a decrease of 30% in total abundance). Specific subgroups of species, e.g. protected species or specific indicator groups, showed a higher variance, thus requiring a higher sample size to detect effects ranging from 12 to 16 transects (equivalent to 21–29 working days per country and year). When using original, untransformed count data a considerably larger sample size would be needed. Actual time to be invested in field work differed between countries due to contrasting regional constraints and conditions. Nevertheless, the final monitoring effort in working days was similar between countries as the factors involved balanced out each other, in particular due to the differing year-to-year variations.Our study demonstrated the feasibility of an environmental monitoring programme in arable land using farmland butterflies across Europe. We present a suitable approach and guidelines as well as the necessary effort to be invested in future Europe-wide monitoring programmes of butterflies in agro-ecosystems, based on predictions of statistical power. In agro-ecosystems, environmental monitoring is fundamental to detect and survey changes related to land use change and management practices. Butterflies and moths have often been suggested as suitable indicators for monitoring environmental effects on biodiversity in farmlands. Here, we estimated the required sample size and monitoring effort necessary to run a Lepidoptera survey in European farmland, assessing in particular if monitoring investment would differ between representative bio-geographical regions.We operated linear 1-km long transect routes in farmland of Romania, Spain and Sweden from 2013 to 2015, and recorded butterflies and burnet moths (Papilionoidea, Zygaenidae). The transects were walked back and forth four times a season, and replicated yearly. The lepidopteran diversity was high in farmlands of Romania and Spain, but comparatively low in Sweden. The coefficient of variation (CV) of recorded species number differed between countries being lowest in Sweden and highest in Spain. In general, the CV dropped above a transect length of 400–800 m, thus indicating an increase in statistical power. Assuming a non-parametric test for matched samples, power calculations were conducted with the raw count data and with log-transformed count data for comparison. When using log-transformed data, the required sample size to detect an effect was less than 10 transects per country or region (in order to detect a 10% loss of species or a decrease of 30% in total abundance). Specific subgroups of species, e.g. protected species or specific indicator groups, showed a higher variance, thus requiring a higher sample size to detect effects ranging from 12 to 16 transects (equivalent to 21–29 working days per country and year). When using original, untransformed count data a considerably larger sample size would be needed. Actual time to be invested in field work differed between countries due to contrasting regional constraints and conditions. Nevertheless, the final monitoring effort in working days was similar between countries as the factors involved balanced out each other, in particular due to the differing year-to-year variations.Our study demonstrated the feasibility of an environmental monitoring programme in arable land using farmland butterflies across Europe. We present a suitable approach and guidelines as well as the necessary effort to be invested in future Europe-wide monitoring programmes of butterflies in agro-ecosystems, based on predictions of statistical power.

Topsoil conditions in temperate forests are influenced by several soil-forming factors, such as canopy composition (e.g. through litter quality), land-use history, atmospheric deposition, and the parent material. Many studies have evaluated the effects of single factors on physicochemical topsoil conditions, but few have assessed the simultaneous effects of multiple drivers. Here, we evaluate the combined effects of litter quality, land-use history (past land cover as well as past forest management), and atmospheric deposition on several physicochemical topsoil conditions of European temperate deciduous forest soils: bulk density, proportion of exchangeable base cations, carbon/nitrogen-ratio (C/N), litter mass, bio-available and total phosphorus, pHKCl and soil organic matter. We collected mineral soil and litter layer samples, and measured site characteristics for 190 20 × 20 m European mixed forest plots across gradients of litter quality (derived from the canopy species composition) and atmospheric deposition, and for different categories of past land cover and past forest management. We accounted for the effects of parent material on topsoil conditions by clustering our plots into three soil type groups based on texture and carbonate concentration. We found that litter quality was a stronger driver of topsoil conditions compared to land-use history or atmospheric deposition, while the soil type also affected several topsoil conditions here. Plots with higher litter quality had soils with a higher proportion of exchangeable base cations, and total phosphorus, and lower C/N-ratios and litter mass. Furthermore, the observed litter quality effects on the topsoil were independent from the regional nitrogen deposition or the soil type, although the soil type likely (co)-determined canopy composition and thus litter quality to some extent in the investigated plots. Litter quality effects on topsoil phosphorus concentrations did interact with past land cover, highlighting the need to consider land-use history when evaluating canopy effects on soil conditions. We conclude that forest managers can use the canopy composition as an important tool for influencing topsoil conditions, although soil type remains an important factor to consider.

Question: When evaluating forests in terms of their biodiversity, distinctiveness and naturalness, the affinity of the constituent species to forests is a crucial parameter. Here we ask to what extent are vascular plant species associated with forests, and does species’ affinity to forests vary between European regions?. Location: Temperate and boreal forest biome of Northwestern and Central Europe. Methods: We compiled EuForPlant, a new extensive list of forest vascular plant species in 24 regions spread across 13 European countries using vegetation databases and expert knowledge. Species were region-specifically classified into four categories reflecting the degree of their affinity to forest habitats: 1.1, species of forest interiors; 1.2, species of forest edges and forest openings; 2.1, species that can be found in forest as well as open vegetation; and 2.2, species that can be found partly in forest, but mainly in open vegetation. An additional “O” category was distinguished, covering species typical for non-forest vegetation. Results: EuForPlant comprises 1,726 species, including 1,437 herb-layer species, 159 shrubs, 107 trees, 19 lianas and 4 epiphytic parasites. Across regions, generalist forest species (with 450 and 777 species classified as 2.1 and 2.2, respectively) significantly outnumbered specialist forest species (with 250 and 137 species classified as 1.1 and 1.2, respectively). Even though the degree of shifting between the categories of forest affinity among regions was relatively low (on average, 17.5%), about one-third of the forest species (especially 1.2 and 2.2) swapped categories in at least one of the study regions. Conclusions: The proposed list can be used widely in vegetation science and global change ecology related to forest biodiversity and community dynamics. Shifting of forest affinity among regions emphasizes the importance of a continental-scale forest plant species list with regional specificity. QuestionWhen evaluating forests in terms of their biodiversity, distinctiveness and naturalness, the affinity of the constituent species to forests is a crucial parameter. Here we ask to what extent are vascular plant species associated with forests, and does species’ affinity to forests vary between European regions?LocationTemperate and boreal forest biome of Northwestern and Central Europe.MethodsWe compiled EuForPlant, a new extensive list of forest vascular plant species in 24 regions spread across 13 European countries using vegetation databases and expert knowledge. Species were region-specifically classified into four categories reflecting the degree of their affinity to forest habitats: 1.1, species of forest interiors; 1.2, species of forest edges and forest openings; 2.1, species that can be found in forest as well as open vegetation; and 2.2, species that can be found partly in forest, but mainly in open vegetation. An additional “O” category was distinguished, covering species typical for non-forest vegetation.ResultsEuForPlant comprises 1,726 species, including 1,437 herb-layer species, 159 shrubs, 107 trees, 19 lianas and 4 epiphytic parasites. Across regions, generalist forest species (with 450 and 777 species classified as 2.1 and 2.2, respectively) significantly outnumbered specialist forest species (with 250 and 137 species classified as 1.1 and 1.2, respectively). Even though the degree of shifting between the categories of forest affinity among regions was relatively low (on average, 17.5%), about one-third of the forest species (especially 1.2 and 2.2) swapped categories in at least one of the study regions.ConclusionsThe proposed list can be used widely in vegetation science and global change ecology related to forest biodiversity and community dynamics. Shifting of forest affinity among regions emphasizes the importance of a continental-scale forest plant species list with regional specificity.

Questions: Light availability at the forest floor affects many forest ecosystem processes, and is often quantified indirectly through easy-to-measure stand characteristics. We investigated how three such characteristics, basal area, canopy cover and canopy closure, were related to each other in structurally complex mixed forests. We also asked how well they can predict the light-demand signature of the forest understorey (estimated as the mean Ellenberg indicator value for light [“EIVLIGHT”] and the proportion of “forest specialists” [“%FS”] within the plots). Furthermore, we asked whether accounting for the shade-casting ability of individual canopy species could improve predictions of EIVLIGHT and %FS. Location: A total of 192 study plots from nineteen temperate forest regions across Europe. Methods: In each plot, we measured stand basal area (all stems >7.5 cm diameter), canopy closure (with a densiometer) and visually estimated the percentage cover of all plant species in the herb (<1 m), shrub (1–7 m) and tree layer (>7 m). We used linear mixed-effect models to assess the relationships between basal area, canopy cover and canopy closure. We performed model comparisons, based on R2 and the Akaike Information Criterion (AIC), to assess which stand characteristics can predict EIVLIGHT and %FS best, and to assess whether canopy shade-casting ability can significantly improve model fit. Results: Canopy closure and cover were weakly related to each other, but showed no relation with basal area. For both EIVLIGHT and %FS, canopy cover was the best predictor. Including the share of high-shade-casting species in both the basal-area and cover models improved the model fit for EIVLIGHT, but not for %FS. Conclusions: The typically expected relationships between basal area, canopy cover and canopy closure were weak or even absent in structurally complex mixed forests. In these forests, easy-to-measure structural canopy characteristics were poor predictors of the understorey light-demand signature, but accounting for compositional characteristics could improve predictions.

Global sustainability targets demand transformative changes. Nature-based solutions (NbS) are gaining traction in science and policy, but their potential for transformative change remains unexplored. We provide a framework to evaluate how NbS contribute to transformative change and apply it to 93 NbS from mountain social-ecological systems (SES). The framework serves to assess what elements may catalyze transformative change, how transformative change occurs, and what its outcomes are. Our results show that NbS are as much “people based” as “nature based.” Most NbS are based on four elements with transformation potential: nature's values, knowledge types, community engagement, and nature management practices. Our results confirm the potential of NbS for transformative change, observed through changes in non-sustainable trajectories of SES. We illustrate the components of our framework through a novel classification of NbS. The framework provides key components for assessing the effectiveness of NbS and allows tracking long-term transformative change processes. Nature-based solutions (NbS) havegained considerable traction in scienceand policy, but their potential to delivertransformative change remainsunexplored. We provide a framework toassess NbS under a transformativechange lens and operationalize it through93 NbS from mountain regions globally.We found evidence of NbS’ potential fortransformative change towardsustainable trajectories, mostly through acombination of various nature’s valuesand knowledge types, communityengagement processes, and ecosystemmanagement practices.