Challenging the Scientific Foundations for an IUCN Red List of Ecosystems

The International Union for Conservation of Nature (IUCN) is currently discussing the development of a Red List of Ecosystems (RLE) that would mirror the categories and criteria used to assess the conservation status of species. The suggested scientific foundations for the RLE are being considered by IUCN for adoption as the backbone of the RLE. We identify conceptual and operational weaknesses in the draft RLE approach, the categories, and criteria.While species are relatively well-described units, there is no consistent means to classify ecosystems for assessing conservation status. The proposed RLE is framed mostly around certain features of ecosystems such as broad vegetation or habitat types, and do not consider major global change drivers such as climate change. We discuss technical difficulties with the proposed concept of ecosystem collapse and suggest it is not analogous to species extinction. We highlight the lack of scientific basis for the criteria and thresholds proposed by the RLE, and question the need to adopt the structure of the Red List of Species for an RLE. We suggest that the proposed RLE is open to ambiguous interpretations and uncertain outcomes, and that its practicality and benefit for conservation should be carefully evaluated before final approval

The Natural Capital Indicator Framework (NCIF): A framework of indicators for national natural capital reporting

It is now widely recognised that components of the environment play the role of economic assets, termed natural capital, that are a foundation of social and economic development. National governments monitor the state and trends of natural capital through a range of activities including natural capital accounting, national ecosystem assessments, ecosystem service valuation, and economic and environmental analyses. Indicators play an integral role in these activities as they facilitate the reporting of complex natural capital information. One factor that hinders the success of these activities and their comparability across countries is the absence of a coherent framework of indicators concerning natural capital (and its benefits) that can aid decision-making. Here we present an integrated Natural Capital Indicator Framework (NCIF) alongside example indicators, which provides an illustrative structure for countries to select and organise indicators to assess their use of and dependence on natural capital. The NCIF sits within a wider context of indicators related to natural, human, social and manufactured capital, and associated flows of benefits. The framework provides decision-makers with a structured approach to selecting natural capital indicators with which to make decisions about economic development that take into account national natural capital and associated flows of benefits.Comment: 26 pages, 3 figures, 1 table, 1 graphical abstrac

Density-Dependent Demographic Variation Determines Extinction Rate of Experimental Populations

Understanding population extinctions is a chief goal of ecological theory. While stochastic theories of population growth are commonly used to forecast extinction, models used for prediction have not been adequately tested with experimental data. In a previously published experiment, variation in available food was experimentally manipulated in 281 laboratory populations of Daphnia magna to test hypothesized effects of environmental variation on population persistence. Here, half of those data were used to select and fit a stochastic model of population growth to predict extinctions of populations in the other half. When density-dependent demographic stochasticity was detected and incorporated in simple stochastic models, rates of population extinction were accurately predicted or only slightly biased. However, when density-dependent demographic stochasticity was not accounted for, as is usual when forecasting extinction of threatened and endangered species, predicted extinction rates were severely biased. Thus, an experimental demonstration shows that reliable estimates of extinction risk may be obtained for populations in variable environments if high-quality data are available for model selection and if density-dependent demographic stochasticity is accounted for. These results suggest that further consideration of density-dependent demographic stochasticity is required if predicted extinction rates are to be relied upon for conservation planning

Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory

The authors analyze developmental, genetic, and demographic mechanisms by which populations tolerate changing environments and discuss empirical methods for determining the critical rate of sustained environmental change that causes population extinction

Synthetic biology and the conservation of biodiversity

AbstractSynthetic biology is a broad and fast-moving field of innovation involving the design and construction of new biological parts, and the redesign of existing, natural biological systems to address real world problems. It has many potential applications that may change human relations to the natural world. Synthetic biology is virtually unknown to the conservation community. Based on a meeting in 2013 that brought together these two communities we consider first the differences between the two fields, and second the kinds of opportunities and risks that arise.This is the accepted manuscript of a paper published in Oryx (Redford KH, Adams W, Carlson R, Mace GM, Ceccarelli B, Oryx 2014, 48 (3), 330-336, doi:10.1017/S0030605314000040)

Towards a risk register for natural capital

1. Natural capital is essential for goods and services on which people depend. Yet pressures on the environment mean that natural capital assets are continuing to decline and degrade, putting such benefits at risk. Systematic monitoring of natural assets is a major challenge that could be both unaffordable and unmanageable without a way to focus efforts. Here we introduce a simple approach, based on the commonly used management tool of a risk register, to highlight natural assets whose condition places benefits at risk. 2. We undertake a preliminary assessment using a risk register for natural capital assets in the UK based solely on existing information. The status and trends of natural capital assets are assessed using asset–benefit relationships for ten kinds of benefits (food, fibre (timber), energy, aesthetics, freshwater (quality), recreation, clean air, wildlife, hazard protection and equable climate) across eight broad habitat types in the UK based on three dimensions of natural capital within each of the habitat types (quality, quantity and spatial configuration). We estimate the status and trends of benefits relative to societal targets using existing regulatory limits and policy commitments, and allocate scores of high, medium or low risk to asset–benefit relationships that are both subject to management and of concern. 3. The risk register approach reveals substantial gaps in knowledge about asset–benefit relationships which limit the scope and rigour of the assessment (especially for marine and urban habitats). Nevertheless, we find strong indications that certain assets (in freshwater, mountain, moors and heathland habitats) are at high risk in relation to their ability to sustain certain benefits (especially freshwater, wildlife and climate regulation). 4. Synthesis and applications. With directed data gathering, especially to monitor trends, improve metrics related to asset–benefit relationships, and improve understanding of nonlinearities and thresholds, the natural capital risk register could provide a useful tool. If updated regularly, it could direct monitoring efforts, focus research and protect and manage those natural assets where benefits are at highest risk

The Limits to Sustainability Science: Ecological Constraints or Endless Innovation?

Ecological principles must govern sustainability, yet sustainability science is largely concerned with social-environmental interactions and barely considers physical limits on resource use. Whether it is possible to overcome such limits can be contested, but the issues raised by a macroecological perspective should be a fundamental part of the United Nations Conference on Sustainable Development (Rio+20)

Historical drivers of extinction risk: using past evidence to direct future monitoring

Global commitments to halt biodiversity decline mean that it is essential to monitor species' extinction risk. However, the work required to assess extinction risk is intensive. We demonstrate an alternative approach to monitoring extinction risk, based on the response of species to external conditions. Using retrospective International Union for Conservation of Nature Red List assessments, we classify transitions in the extinction risk of 497 mammalian carnivores and ungulates between 1975 and 2013. Species that moved to lower Red List categories, or remained Least Concern, were classified as ‘lower risk'; species that stayed in a threatened category, or moved to a higher category of risk, were classified as ‘higher risk'. Twenty-four predictor variables were used to predict transitions, including intrinsic traits (species biology) and external conditions (human pressure, distribution state and conservation interventions). The model correctly classified up to 90% of all transitions and revealed complex interactions between variables, such as protected areas (PAs) versus human impact. The most important predictors were: past extinction risk, PA extent, geographical range size, body size, taxonomic family and human impact. Our results suggest that monitoring a targeted set of metrics would efficiently identify species facing a higher risk, and could guide the allocation of resources between monitoring species' extinction risk and monitoring external conditions