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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017) 44 pages, 9 tables, 9 figures.-- Corinne Le Quéré ... et al.-- This work is distributed under the Creative Commons Attribution 4.0 License Peer reviewed

Urban areas are increasing globally, providing opportunities for biodiversity researchers to study the process in which species become established in novel, highly disturbed habitats. This ecological process can be understood through analyses of morphological and genetic variation, which can shed light on patterns of neutral and adaptive evolution. Previous studies have shown that urban populations often diverge genetically from non-urban source populations. This could occur due to neutral genetic drift, but an alternative is that selection could lead to allele frequency changes in urban populations. The development of genome scan methods provides an opportunity to investigate these outcomes from samples of genetic variation taken along an urbanization gradient. Here we examine morphological variation in wing size and diversity at neutral amplified fragment length polymorphisms in the butterfly Pieris rapae L. (Lepidoptera, Pieridae) sampled from the center to the periphery of Marseille. We utilize established and novel environmental correlation approaches to scan genetic variation for evidence of selection. We find significant morphological differences in urban populations, as well as weak genetic structure and decreased genetic diversity in urban versus non-urban sites. However, environmental correlation tests provide little support for selection in our dataset. Our comparison of different methods and allele frequency clines suggests that loci identified as significant are false positives. Although there is some indication that selection may be acting on wing size in urban butterflies, genetic analyses suggest P. rapae are undergoing neutral drift. International audience

In the context of climate change and increasing urbanization, Small Island Developing States are increasingly vulnerable to natural disasters. In response to urbanization in at risk areas, the concept of territorial resilience has potential as an approach to urban flood issues. The objective of this research is to develop a spatial decision support tool based on a collaborative assessment method of territorial resilience. The proposed methodology consists of: the adaptation to the French Polynesian context, three existing resilience assessment methods applied to a case study in the Punaruu Valley’s (Punaauia, French Polynesia) and the use of geovisualization techniques: use of GIS for data processing and analysis, visualization, mapping and model processing. This methodology integrates the technical, urban and social components of the territory, while highlighting the various levers available to improve territorial resilience and facilitate its understanding through collaborative work efforts and the use of a visual tool. The results demonstrate the reproducibility of these methods for assessing resilience in French Polynesia. They underline the potential of a collaborative approach to highlight critical infrastructures and generate possible decision support to improve the territory’s ability to function despite a disruption and the ability to rebuild following this disruption.

Using the method of fuzzy cognitive mapping, this study explores stakeholder attitudes toward offshore wind energy. The survey was conducted with local communities of the Bay of Saint-Brieuc, where an offshore wind farm is under development. It was used to record the stakeholder perceptions of social, ecological, and economic impacts and the expression of expected compensation for negative impacts. Distribution and interaction among the data were analyzed through multiple correspondence analysis. Our study illustrates a gap between positive impacts associated with sustainable development perceived at the national level and more negative impacts perceived by local communities. The expression of expected compensation is dependent on the perceived impacts. This study highlights the place attachment of local stakeholders and thus suggests developing offshore wind farms with respect to territorial integrity and its heritage dimension in order to improve social acceptability. International audience

There is increasing interest in measuring ecological stability to understand how communities and ecosystems respond to broad-scale global changes. One of the most common approaches is to quantify the variation through time in community or ecosystem aggregate attributes (e.g. total biomass), referred to as aggregate variability. It is now widely recognized that aggregate variability represents only one aspect of communities and ecosystems, and compositional variability, the changes in the relative frequency of species in an assemblage, is equally important. Recent contributions have also begun to explore ecological stability at regional spatial scales, where interconnected local communities form metacommunities, a key concept in managing complex landscapes. However, the conceptual frameworks and measures of ecological stability in space have only focused on aggregate variability, leaving a conceptual gap. Here, we address this gap with a novel framework for quantifying the aggregate and compositional variability of communities and ecosystems through space and time. We demonstrate that the compositional variability of a metacommunity depends on the degree of spatial synchrony in compositional trajectories among local communities. We then provide a conceptual framework in which compositional variability of 1) the metacommunity through time and 2) among local communities combine into four archetype scenarios: spatial stasis (low/low), spatial synchrony (high/low), spatial asynchrony (high/high) and spatial compensation (low/high). We illustrate this framework based on numerical examples and a case study of a macroalgal metacommunity in which low spatial synchrony reduced variability in aggregate biomass at the metacommunity scale, while masking high spatial synchrony in compositional trajectories among local communities. Finally, we discuss the role of dispersal, environmental heterogeneity, species interactions and suggest future avenues. We believe this framework will be helpful for considering both aspects of variability simultaneously, which is important to better understand ecological stability in natural and complex landscapes in response to environmental changes. \ₑprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/oik.08517 International audience