Global Hotspots of Conflict Risk between Food Security and Biodiversity Conservation

This work contributes to the Belmont Forum/FACCE-JPI DEVIL project (grant number NE/M021327/1), and AM is supported by a BBSRC EastBio Studentship (http://www.eastscotbiodtp.ac.uk/). The Conservation Biology Institute are acknowledged for provision of data as well as BirdLife International, IUCN, NatureServe, and USGS for their contribution of the species range map data used in producing data available from the Biodiversity Mapping website (http://biodiversitymapping.org).Peer reviewedPublisher PD

A habitat suitability model for predicting coral community and reef distributions in the Galapagos

The coral communities and coral reefs of the Galapagos Marine Reserve support tens of thousands of species, including many rare and endemic species. Reef-building corals are sensitive to elevated temperatures, which have been linked to coral bleaching (loss of symbiotic zooxanthellae) and therefore their distribution around the islands has been strongly affected by extreme climatic events over the last 30 years. Following the 1982–3 El Niño-Southern Oscillation event, coral cover was reduced by 95 %, with further mortality in the 1997–8 event. Although there has been significant recovery of the communities in recent years, there is concern that by 2100 the global climate system and sea surface temperatures will warm by between 1.4° and 5.8°C, which could result in 100% mortality of Galapagos corals. This paper reports a temperature and depth bioclimatic envelope (or niche) model of potential coral distribution, developed using an historical analysis of monthly sea surface temperatures, derived from the NOAA AVHRR over the period 1985–2001, and a near-shore bathymetry data set derived from Shuttle Radar Topography Mission digital topographic data integrated with ship-based depth sounding surveys and digitised hydrographic maps. The model was validated against known coral community and coral reef localities. Application of the model can support the identification of potential new areas where conditions for coral growth are favourable and enable predictions of the effects of future climate change

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression

Impacts of land use, population, and climate change on global food security

Funding Information: This work contributes to the Belmont Forum/FACCE‐JPI DEVIL project (NE/M021327/1). AM is supported by a Biotechnology and Biological Sciences Research Council (BBSRC) EastBio Studentship ( http://www.eastscotbiodtp.ac.uk/ ) (grant number BB/M010996/1) and the Global Challenges Research Fund Trade, Development and the Environment Hub project (ES/S008160/1). Elke Stehfest and Jonathan Doelman are acknowledged for provision of land use data and we thank the two anonymous reviewers for their constructive and helpful suggestions which have strengthened this manuscript.Peer reviewedPublisher PD

It's not the 'what', but the 'how':Exploring the role of debt in natural resource (un)sustainability

<div><p>A debt-based economy cannot survive without economic growth. However, if private debt consistently grows faster than GDP, the consequences are financial crises and the current unprecedented level of global debt. This policy dilemma is aggravated by the lack of analyses factoring the impact of debt-growth cycles on the environment. What is really the relationship between debt and natural resource sustainability, and what is the role of debt in decoupling economic growth from natural resource availability? Here we present a conceptual Agent-Based Model (ABM) that integrates an environmental system into an ABM representation of Steve Keen’s debt-based economic models. Our model explores the extent to which debt-driven processes, within debt-based economies, enhance the decoupling between economic growth and the availability of natural resources. Interestingly, environmental and economic collapse in our model are not caused by debt growth, or the debt-based nature of the economic system itself (i.e. the ‘<i>what</i>’), but rather, these are due to the inappropriate use of debt by private actors (i.e. the ‘<i>how</i>’). Firms inappropriately use bank credits for speculative goals–rather than production-oriented ones–and for exponentially increasing rates of technological development. This context creates temporal mismatches between natural resource growth and firms’ resource extraction rates, as well as between economic growth and the capacity of the government to effectively implement natural resource conservation policies. This paper discusses the extent to which economic growth and the availability of natural resources can be re-coupled through a more sustainable use of debt, for instance by shifting mainstream banking forces to partially support environmental conservation as well as economic growth.</p></div

Evidence-based selection of environmental factors and datasets for measuring multiple environmental deprivation in epidemiological research

This Environment and Human Health project aims to develop a health-based summary measure of multiple physical environmental deprivation for the UK, akin to the measures of multiple socioeconomic deprivation that are widely used in epidemiology. Here we describe the first stage of the project, in which we aimed to identify health-relevant dimensions of physical environmental deprivation and acquire suitable environmental datasets to represent population exposure to these dimensions at the small-area level. We present the results of this process: an evidence-based list of environmental dimensions with population health relevance for the UK, and the spatial datasets we obtained and processed to represent these dimensions. This stage laid the foundations for the rest of the project, which will be reported elsewhere

Projecting the effect of crop yield increases, dietary change and different price scenarios on land use under two different state security regimes

Peer reviewedPublisher PD

Safe and just operating spaces for regional social-ecological systems

Humanity faces a major global challenge in achieving wellbeing for all, while simultaneously ensuring that the biophysical processes and ecosystem services that underpin wellbeing are exploited within scientifically informed boundaries of sustainability. We propose a framework for defining the safe and just operating space for humanity that integrates social wellbeing into the original planetary boundaries concept (Rockström et al., 2009a,b) for application at regional scales. We argue that such a framework can: (1) increase the policy impact of the boundaries concept as most governance takes place at the regional rather than planetary scale; (2) contribute to the understanding and dissemination of complexity thinking throughout governance and policy-making; (3) act as a powerful metaphor and communication tool for regional equity and sustainability. We demonstrate the approach in two rural Chinese localities where we define the safe and just operating space that lies between an environmental ceiling and a social foundation from analysis of time series drawn from monitored and palaeoecological data, and from social survey statistics respectively. Agricultural intensification has led to poverty reduction, though not eradicated it, but at the expense of environmental degradation. Currently, the environmental ceiling is exceeded for degraded water quality at both localities even though the least well-met social standards are for available piped water and sanitation. The conjunction of these social needs and environmental constraints around the issue of water access and quality illustrates the broader value of the safe and just operating space approach for sustainable development

A continental-scale validation of ecosystem service models

Faced with environmental degradation, governments worldwide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by the existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the demand side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being