RESUMEN
Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.
Asunto(s)
Secuestro de Carbono , Carbono , Conservación de los Recursos Naturales , Bosques , Biodiversidad , Carbono/análisis , Carbono/metabolismo , Conservación de los Recursos Naturales/estadística & datos numéricos , Conservación de los Recursos Naturales/tendencias , Actividades Humanas , Restauración y Remediación Ambiental/tendencias , Desarrollo Sostenible/tendencias , Calentamiento Global/prevención & controlRESUMEN
Succession is a fundamental concept in ecology because it indicates how species populations, communities, and ecosystems change over time on new substrate or after a disturbance. A mechanistic understanding of succession is needed to predict how ecosystems will respond to land-use change and to design effective ecosystem restoration strategies. Yet, despite a century of conceptual advances a comprehensive successional theory is lacking. Here we provide an overview of 19 successional theories ('models') and their key points, group them based on conceptual similarity, explain conceptual development in successional ideas and provide suggestions how to move forward. Four groups of models can be recognised. The first group (patch & plants) focuses on plants at the patch level and consists of three subgroups that originated in the early 20th century. One subgroup focuses on the processes (dispersal, establishment, and performance) that operate sequentially during succession. Another subgroup emphasises individualistic species responses during succession, and how this is driven by species traits. A last subgroup focuses on how vegetation structure and underlying demographic processes change during succession. A second group of models (ecosystems) provides a more holistic view of succession by considering the ecosystem, its biota, interactions, diversity, and ecosystem structure and processes. The third group (landscape) considers a larger spatial scale and includes the effect of the surrounding landscape matrix on succession as the distance to neighbouring vegetation patches determines the potential for seed dispersal, and the quality of the neighbouring patches determines the abundance and composition of seed sources and biotic dispersal vectors. A fourth group (socio-ecological systems) includes the human component by focusing on socio-ecological systems where management practices have long-lasting legacies on successional pathways and where regrowing vegetations deliver a range of ecosystem services to local and global stakeholders. The four groups of models differ in spatial scale (patch, landscape) or organisational level (plant species, ecosystem, socio-ecological system), increase in scale and scope, and reflect the increasingly broader perspective on succession over time. They coincide approximately with four periods that reflect the prevailing view of succession of that time, although all views still coexist. The four successional views are: succession of plants (from 1910 onwards) where succession was seen through the lens of species replacement; succession of communities and ecosystems (from 1965 onwards) when there was a more holistic view of succession; succession in landscapes (from 2000 onwards) when it was realised that the structure and composition of landscapes strongly impact successional pathways, and increased remote-sensing technology allowed for a better quantification of the landscape context; and succession with people (from 2015 onwards) when it was realised that people and societal drivers have strong effects on successional pathways, that ecosystem processes and services are important for human well-being, and that restoration is most successful when it is done by and for local people. Our review suggests that the hierarchical successional framework of Pickett is the best starting point to move forward as this framework already includes several factors, and because it is flexible, enabling application to different systems. The framework focuses mainly on species replacement and could be improved by focusing on succession occurring at different hierarchical scales (population, community, ecosystem, socio-ecological system), and by integrating it with more recent developments and other successional models: by considering different spatial scales (landscape, region), temporal scales (ecosystem processes occurring over centuries, and evolution), and by taking the effects of the surrounding landscape (landscape integrity and composition, the disperser community) and societal factors (previous and current land-use intensity) into account. Such a new, comprehensive framework could be tested using a combination of empirical research, experiments, process-based modelling and novel tools. Applying the framework to seres across broadscale environmental and disturbance gradients allows a better insight into what successional processes matter and under what conditions.
Asunto(s)
Ecología , Ecosistema , Humanos , BiotaRESUMEN
Combating climate change requires unified action across all sectors of society. However, this collective action is precluded by the 'consensus gap' between scientific knowledge and public opinion. Here, we test the extent to which the iconic cities around the world are likely to shift in response to climate change. By analyzing city pairs for 520 major cities of the world, we test if their climate in 2050 will resemble more closely to their own current climate conditions or to the current conditions of other cities in different bioclimatic regions. Even under an optimistic climate scenario (RCP 4.5), we found that 77% of future cities are very likely to experience a climate that is closer to that of another existing city than to its own current climate. In addition, 22% of cities will experience climate conditions that are not currently experienced by any existing major cities. As a general trend, we found that all the cities tend to shift towards the sub-tropics, with cities from the Northern hemisphere shifting to warmer conditions, on average ~1000 km south (velocity ~20 km.year-1), and cities from the tropics shifting to drier conditions. We notably predict that Madrid's climate in 2050 will resemble Marrakech's climate today, Stockholm will resemble Budapest, London to Barcelona, Moscow to Sofia, Seattle to San Francisco, Tokyo to Changsha. Our approach illustrates how complex climate data can be packaged to provide tangible information. The global assessment of city analogues can facilitate the understanding of climate change at a global level but also help land managers and city planners to visualize the climate futures of their respective cities, which can facilitate effective decision-making in response to on-going climate change.
Asunto(s)
Cambio Climático , Ciudades , Clima , Toma de Decisiones , Humanos , Modelos Teóricos , Análisis de Componente Principal , Factores de TiempoRESUMEN
[This corrects the article DOI: 10.1371/journal.pone.0217592.].