• Energy Research

AbstractSustainability is a key challenge for humanity in the context of complex and unprecedented global changes. Future Earth, an international research initiative aiming to advance global sustainability science, has recently launched knowledge–action networks (KANs) as mechanisms for delivering its research strategy. The research initiative is currently developing a KAN on “natural assets” to facilitate and enable action-oriented research and synthesis towards natural assets sustainability. ‘Natural assets’ has been adopted by Future Earth as an umbrella term aiming to translate and bridge across different knowledge systems and different perspectives on peoples’ relationships with nature. In this paper, we clarify the framing of Future Earth around natural assets emphasizing the recognition on pluralism and identifying the challenges of translating different visions about the role of natural assets, including via policy formulation, for local to global sustainability challenges. This understanding will be useful to develop inter-and transdisciplinary solutions for human–environmental problems by (i) embracing richer collaborative decision processes and building bridges across different perspectives; (ii) giving emphasis on the interactions between biophysical and socioeconomic drivers affecting the future trends of investments and disinvestments in natural assets; and (iii) focusing on social equity, power relationships for effective application of the natural assets approach. This understanding also intends to inform the scope of the natural asset KAN’s research agenda to mobilize the translation of research into co-designed action for sustainability.

Ecosystem services research needs to become more transdisciplinary.•ecoSERVICES will advance co-designed, transdisciplinary ecosystem service research. Ecosystem services have become a mainstream concept for the expression of values assigned by people to various functions of ecosystems. Even though the introduction of the concept has initiated a vast amount of research, progress in using this knowledge for sustainable resource use remains insufficient. We see a need to broaden the scope of research to answer three key questions that we believe will improve incorporation of ecosystem service research into decision-making for the sustainable use of natural resources to improve human well-being: (i) how are ecosystem services co-produced by social-ecological systems, (ii) who benefits from the provision of ecosystem services, and (iii) what are the best practices for the governance of ecosystem services? Here, we present these key questions, the rationale behind them, and their related scientific challenges in a globally coordinated research programme aimed towards improving sustainable ecosystem management. These questions will frame the activities of ecoSERVICES, formerly a DIVERSITAS project and now a project of Future Earth, in its role as a platform to foster global coordination of multidisciplinary sustainability science through the lens of ecosystem services.

BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans. Emerging models are beginning to incorporate six key biological mechanisms that can improve predictions of biological responses to climate change. Models that include biological mechanisms have been used to project (clockwise from top) the evolution of disease-harboring mosquitoes, future environments and land use, physiological responses of invasive species such as cane toads, demographic responses of penguins to future climates, climate-dependent dispersal behavior in butterflies, and mismatched interactions between butterflies and their host plants. Despite these modeling advances, we seldom have the detailed data needed to build these models, necessitating new efforts to collect the relevant data to parameterize more biologically realistic predictive models.

Multiple, coordinated goals and holistic actions are critical

AbstractIn 2010, the parties of the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 with the mission of halting biodiversity loss and enhance the benefits it provides to people. The 20 Aichi Biodiversity Targets (Aichi Targets), which are included in the Strategic Plan, are organized under five Strategic Goals, and provide coherent guidance on how to achieve it. Halfway through the Strategic Plan, it is time to prioritize actions in order to achieve the best possible outcomes for the Aichi Targets in 2020. Actions to achieve one target may influence other targets (downstream interactions); in turn a target may be influenced by actions taken to attain other targets (upstream interactions). We explore the interactions among targets and the time-lags between implemented measures and desired outcomes to develop a framework that can reduce the overall burden associated with the implementation of the Strategic Plan. We identified the targets addressing the underlying drivers of biodiversity loss and the targets aimed at enhancing the implementation of the Strategic Plan as having the highest level of downstream interactions. Targets aimed at improving the status of biodiversity and safeguarding ecosystems followed by targets aimed at reducing the direct pressures on biodiversity and enhancing the benefits to all from biodiversity and ecosystem services, were identified as having the highest levels of upstream interactions. Perhaps one of the most challenging aspects of the Strategic Plan is the need to balance actions for its long-term sustainability with the need for urgent actions to halt biodiversity loss.