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Which ecosystem services are addressed? Most relevant renewable food resources, i.e., provisioning ecosystem services from agriculture (crops, meat, dairy products) and aqua culture.

Large scale land acquisitions (LSLA), and Reducing Emissions from Deforestation and forest Degradation (REDD+) are both land based phenomena which when occurring in the same area, can compete with each other for land. A quantitative analysis of country characteristics revealed that land available for agriculture, accessibility, and political stability are key explanatory factors for a country being targeted for LSLA. Surprisingly LSLA occur in countries with lower accessibility. Countries with good land availability, poor accessibility and political stability may become future targets if they do not already have LSLA. Countries which high levels of agriculture-driven deforestation and LSLA, should develop interventions which reduce forest loss driven either directly or indirectly by LSLA as part of their REDD+ strategies. Both host country and investor-side policies have been identified which could be used more widely to reduce conflicts between LSLA and REDD+. Findings from this research highlight the need for and can inform the development of national and international policies on land acquisitions including green acquisitions such as REDD+. Land management must be considered with all its objectives—including food security, biodiversity conservation, and climate change mitigation—in a coherent strategy which engages relevant stakeholders. This is not currently occurring and might be a key ingredient to achieve the targets under the Sustainable Development Goals 2 and 15 and 16 (related to food security and sustainable agriculture and the protection of forests) among others.

We analysed the spatial distribution patterns of plant species’ arbuscular mycorrhizal status across an intermediate geographical scale (i.e. the country of Germany) and related these distributions to environmental drivers. Three levels of arbuscular mycorrhizal status of plant species could be defined: (1) obligate arbuscular mycorrhizal species that are always colonised by mycorrhizal fungi, (2) facultative arbuscular mycorrhizal species that are colonised under some conditions but not colonised under others and (3) non-mycorrhizal species that are never found to be colonised by mycorrhizal fungi. We aimed to investigate whether plant species assemblages at the studied grid cell scale are composed of different proportions of species regarding their arbuscular mycorrhizal status, and whether the variation of these proportions can be linked to the geographical variation of ecological and environmental factors. We fitted a vector generalised additive model (VGAM) for log-ratios of proportions of plant species’ arbuscular mycorrhizal status per grid cell (2859 grid cells, each c. 130 km2). The spatially explicit plant arbuscular mycorrhizal status distribution model was based on environmental predictors related to climate, geology and land use. The spatial distribution of plant arbuscular mycorrhizal status can be explained as a function of nine environmental predictors (D2 = 0.54). Proportion of obligate arbuscular mycorrhizal plant species per grid cell increased with increasing temperature range, mean annual temperature, urban area and area of lime as geological parent material and decreased with increasing area of mixed forest and coniferous forest. Annual temperature range was by far the most important predictor. These results extend the comparative context of former studies that established relationships between mycorrhizal status and other plant characteristics at species level, including those describing species ecological requiremen

Growing demand of resources increases pressure on ecosystem services (ES) and biodiversity. Monetary valuation of ES is frequently seen as a decision-support tool by providing explicit values for unconsidered, non-market goods and services. Here we present global value transfer functions by using a meta-analytic framework for the synthesis of 194 case studies capturing 839 monetary values of ES. For 12 ES the variance of monetary values could be explained with a subset of 93 study- and site-specific variables by utilizing boosted regression trees. This provides the first global quantification of uncertainties and transferability of monetary valuations. Models explain from 18% (water provision) to 44% (food provision) of variance and provide statistically reliable extrapolations for 70% (water provision) to 91% (food provision) of the terrestrial earth surface. Although the application of different valuation methods is a source of uncertainty, we found evidence that assuming homogeneity of ecosystems is a major error in value transfer function models. Food provision is positively correlated with better life domains and variables indicating positive conditions for human well-being. Water provision and recreation service show that weak ownerships affect valuation of other common goods negatively (e.g. non-privately owned forests). Furthermore, we found support for the shifting baseline hypothesis in valuing climate regulation. Ecological conditions and societal vulnerability determine valuation of extreme event prevention. Valuation of habitat services is negatively correlated with indicators characterizing less favorable areas. Our analysis represents a stepping stone to establish a standardized integration of and reporting on uncertainties for reliable and valid benefit transfer as an important component for decision support.

BACKGROUND: A controversy exists regarding which monitoring technique is superior in cases in which general anesthesia (GA) is necessary for carotid endarterectomy (CEA). Multimodal evoked potential (mEP) monitoring was investigated under GA during CEA and compared with a historical control group undergoing neurological evaluations awake under loco-regional anesthesia (LA).METHODS: We retrospectively studied 651 patients undergoing elective CEA. In groupHISTORY (N.=349; 1997-1999) LA was provided using superficial or deep/superficial cervical plexus blocks. In groupmEP, (N.=302; 2009-2013) GA was performed by administering remifentanil/propofol infusion. The multimodal EPs included the median-nerve-somatosensory and motor evoked potentials. The primary outcome was the rate of technical failure. The arterio-arterial shunt rate and immediate postoperative motor outcomes were also compared.RESULTS: GroupmEP showed a significantly lower rate of technical failure (OR 0.17; CI 0.03-0.6; P=0.002). Because the groups differed systematically, logistic regression analysis was used to compare shunt rates and motor outcomes. Since shunt rates were 8.3% (groupmEP) versus 8.2% (groupHISTORY), but logistic regression model showed significant differences (OR 3.77; CI 1.67-8.95; P=0.001) correct comparison was impossible. Immediate postoperative deficits were 4.3% (groupmEP) and 4.9% (groupHISTORY); logistic regression analysis: transient OR 0.77, CI 0.28 to 0.22, P=0.61 and permanent OR 0.37, CI 0.02-7.74, P=0.49.CONCLUSION: Monitoring mEPs was associated with less technical failure than awake evaluation and showed similar motor outcomes. Because the groups differed systematically, the interpretation of shunt rates was impossible. Monitoring mEP should be considered to detect intraoperative ischemia in cases in which patients undergo CEA under GA.

The factors that promote invasive behavior in introduced plant species occur across many scales of biological and ecological organization. Factors that act at relatively small scales, for example the evolution of biological traits associated with invasiveness, scale up to shape species distributions amongst different climates and habitats, as well as other characteristics linked to invasion, such as attractiveness for cultivation (and by extension propagule pressure). To identify drivers of invasion it is therefore necessary to disentangle the contribution of multiple factors that are interdependent. To this end, we formulated a conceptual model describing the process of invasion of central European species into North America based on a sequence of 'drivers'. We then used confirmatory path analysis to test whether the conceptual model is supported by a statistical model inferred from a comprehensive database containing 466 species. The path analysis revealed that invasion of central-European plants in North America, in terms of the number of North American regions invaded, most strongly depends on minimum residence time in the invaded range and the number of habitats occupied by species in their native range. In addition to the confirmatory path analysis, we identified the effects of various biological traits on several important drivers of the conceptualized invasion process. The data supported a model, which included indirect effects of biological traits on invasion via their effect on the number of native range habitats occupied and cultivation in the native range. For example, persistent seed banks and longer flowering periods are positively correlated with number of native habitats, while a stress-tolerant life strategy is negatively correlated with native-range cultivation. However, the importance of the biological traits is nearly an order of magnitude less than that of the larger-scale drivers and highly dependent on the invasion stage (traits were associate

For several data bases in species distribution modelling (SDM), presences are known but absences are uncertain and can be non-detections. The environment influences both the non-detections and the species occurrences (preferential sampling), affecting model predictions.The objective is to estimate model-based probability of occurrence when absences are uncertain and sampling is preferential. Our Bayesian image restoration (BIR) model has an environmental, spatial and non-detection component. The latter is based on the number of ‘control species’ (selected by expert knowledge to have wide geographic range and occupy several habitats) observed. Control species are assumed present in all grid cells so an observed absence of the control species is a non-detection.The observed absence of a focal species is likely a non-detection when the environment is conducive, the focal species was observed in the neighbourhood, and the number of control species is small.Simulating an artificial species (true prevalence 0·31) and preferential sampling (observed prevalence 0·18), the BIR modelled prevalence was 0·32 (0·30–0·34). The estimation was robust to failure of assumptions with a mis-specified environmental model. The restored map was close to the true map, and the true realized niche of the species was inferred (with uncertainty). The link between the non-detection and control species is crucial, and a sensitivity analysis is recommended.BIR restored the simulated atlas map more accurately than a covariate adjustment method. When applied to the vascular plant Asarum europaeum L., BIR changed the interpretation. The uncertainty maps assisted decision-making. A BIR implementation new to the SDM field is presented.BIR using control species is most fruitfully applied at coarse scale and intermediate extent, with limited environmental extremes and sufficient expert knowledge (e.g. many Central European countries).BIR is a framework, and we studied one implementation. Any proxy (road

Macroecology has prospered in recent years due in part to the wide array of climatic data, such as those provided by the WorldClim and CliMond data sets, which has become available for research. However, important environmental variables have still been missing, including spatial data sets on UV-B radiation, an increasingly recognized driver of ecological processes.We developed a set of global UV-B surfaces (glUV) suitable to match common spatial scales in macroecology. Our data set is based on remotely sensed records from NASA's Ozone Monitoring Instrument (Aura-OMI). Following a similar approach as for the WorldClim and CliMond data sets, we processed daily UV-B measurements acquired over a period of eight years into monthly mean UV-B data and six ecologically meaningful UV-B variables with a 15-arc minute resolution. These bioclimatic variables represent Annual Mean UV-B, UV-B Seasonality, Mean UV-B of Highest Month, Mean UV-B of Lowest Month, Sum of Monthly Mean UV-B during Highest Quarter and Sum of Monthly Mean UV-B during Lowest Quarter. We correlated our data sets with selected variables of existing bioclimatic surfaces for land and with Terra–MODIS Sea Surface Temperature for ocean regions to test for relations to known gradients and patterns.UV-B surfaces showed a distinct seasonal variance at a global scale, while the intensity of UV-B radiation decreased towards higher latitudes and was modified by topographic and climatic heterogeneity. UV-B surfaces were correlated with global mean temperature and annual mean radiation data, but exhibited variable spatial associations across the globe. UV-B surfaces were otherwise widely independent of existing bioclimatic surfaces.Our data set provides new climatological information relevant for macroecological analyses. As UV-B is a known driver of numerous biological patterns and processes, our data set offers the potential to generate a better understanding of these dynamics in macroecology, biogeography, global ch

Many separate studies have estimated the year of peak, or maximum, rate of using an individual resource such as oil. However, no study has estimated the year of peak rate for multiple resources and investigated the relationships among them. We exploit time series on the appropriation of 27 global renewable and nonrenewable resources. We found 21 resources experienced a peak-rate year, and for 20 resources the peak-rate years occurred between 1960-2010, a narrow time window in the long human history. Whereas 4 of 7 nonrenewable resources show no peak-rate year, conversion to cropland and 18 of the 20 renewable resources have passed their peak rate of appropriation. To test the hypothesis that peak-rate years are synchronized, i.e., occur at approximately the same time, we analyzed 20 statistically independent time series of resources, of which 16 presented a peak-rate year centered on 2006 (1989-2008). We discuss potential causal mechanisms including change in demand, innovation and adaptation, interdependent use of resources, physical limitation, and simultaneous scarcity. The synchrony of peak-rate years of multiple resources poses a greater adaptation challenge for society than previously recognized, suggesting the need for a paradigm shift in resource use toward a sustainable path in the Anthropocene.

Remotely sensed land surface temperatures help exploring the surface urban heat island. Measures to mitigate the urban heat island include increasing green urban areas and altering the form of cities. Research is needed to explore the impacts of urban form on the surface urban heat island. Research strategy: Data on land surface temperatures for summer 2001 and land cover are combined with meteorological, demographic, and topographic data for European urban regions, delineated as larger urban zones. To ensure a comprehensive view, three ways of quantifying surface urban heat island are calculated and stratified for morning and evening, and climate zones. Linear models reveal the relative influence of the four factors: (1) composition (e.g., share of different land covers in the urban region), (2) configuration (e.g., spatial arrangement), (3) location (e.g., distance to coast or elevation), and (4) population. Findings: The explanatory power (i.e., adj. R-sq) of the models varies strongly among the different ways to quantify the surface urban heat island and time of day. Rather specific combinations of explanatory variables were found to be relevant in explaining the variation in the different ways of quantifying surface urban heat islands. Compact urban form increases the surface urban heat island measured in one way, but was not a significant predictor for other ways of quantification. Increasing the share of built-up area and forest both increase the surface urban heat island. More built-up areas increased the mean temperature in the region, whereas more forest unsurprisingly decreased the overall temperature. The three ways of quantifying the surface urban heat island were correlated at r<0.5, and their variation was explained by different variables implying that they carry different information about the surface urban heat island effect. Takeaway for practice: Considerable attention needs to be paid to the aims of spat

Plant diversity is globally threatened by anthropogenic land use including management and modification of the natural environment. At regional and local scales, numerous studies world-wide have examined land use and its effects on plant diversity, but evidence for declining species diversity is mixed. This is because, first, land use comes in many variations, hampering comparisons of studies. Second, land use directly affects the environment, but indirect effects extend beyond the boundaries of the land in use. Third, land-use effects greatly depend on the environmental, historical and socio-economic context.To evaluate the generality and variation of studies’ findings about land-use effects, we undertook a quantitative synthesis using meta-analytic techniques.Using 572 effect sizes from 375 studies distributed globally relating to 11 classes of land use, we found that direct and indirect effects of land use on plant diversity (measured as species richness) are variable and can lead to both local decreases and increases. Further, we found evidence (best AIC model) that land-use-specific covariables mostly determine effect-size variation and that in general land-use effects differ between biomes.Synthesis and applications. This extensive synthesis provides the most comprehensive and quantitative overview to date about the effects of the most widespread and relevant land-use options on plant diversity and their covariables. We found important covariables of specific land-use classes but little evidence that land-use effects can be generally explained by their environmental and socio-economic context. We also found a strong regional bias in the number of studies (i.e. more studies from Europe and North America) and highlight the need for an overarching and consistent land-use classification scheme. Thereby, our study provides a new vantage point for future research directions.