Landscapes generate a wide range of valuable ecosystem services, yet land use decisions often ignore the value of these services. Using the example of the UK, we show the significance of land use change not only for agricultural production but also for emissions and sequestration of greenhouse gases, open-access recreational visits, urban green space and wild species diversity. We use spatially explicit models in conjunction with valuation methods to estimate comparable economic values for these services, taking account of climate change impacts. We show that, while decisions which focus solely upon agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning incorporating all potential services and their values, and that this approach also conserves wild species diversity.One Sentence Summary: Valuation of ecosystem services within land-use planning creates significant gains relative to current, market-dominated, decision making. Main Text:The Millennium Ecosystem Assessment (1) provided important evidence of the ongoing global degradation of ecosystem services and highlighted the need to incorporate their value into the economic analyses which underpin real-world decision-making. Previous studies have shown that the overall values of unconverted natural habitats can exceed the private benefits following conversion (2, 3), that knowledge of landscape heterogeneity and ecological processes can support cost effective land planning (4-7), that trade-offs in land-use decisions affect values from ecosystem services and biodiversity at local level (8, 9), and that current land use is vulnerable to the impacts of global change (10, 11). In the UK National Ecosystem Assessment (NEA) (12), a comprehensive assessment of the UK's ecosystems was linked to a systematic, environmental and economic analysis of the benefits they generate. Here we show how taking account of multiple objectives in a changing environment (including, but not restricted to, climate change) fundamentally alters decisions regarding optimal land use. The NEA analyses are based upon highly detailed, spatially-referenced environmental data covering all of Great Britain. These data supported the design and parameterization of models of both the drivers and consequences of land use decisions, incorporating the complexity of the natural environment and its variation across space and time (13). Model outputs provide inputs to economic analyses which assess the value of both marketed and non-marketed goods (Table 1).The NEA specifically addressed the consequences of land use change driven by either just agricultural or a wider set of values, all within the context of ongoing climate change. To assess this, raw data on land use and its determinants were drawn from multiple sources to compile a 40 year dataset, spatially disaggregated at a resolution of 2km grid squares (400ha) or finer across all of Great Britain, forming more than ½ million sets of spatially referenced, time specific...

Deforestation is a main driver of climate change and biodiversity loss. An incentive mechanism to reduce emissions from deforestation and forest degradation (REDD) is being negotiated under the United Nations Framework Convention on Climate Change. Here we use the best available global data sets on terrestrial biodiversity and carbon storage to map and investigate potential synergies between carbon and biodiversity-oriented conservation. A strong association (r S = 0.82) between carbon stocks and species richness suggests that such synergies would be high, but unevenly distributed. Many areas of high value for biodiversity could be protected by carbon-based conservation, while others could benefit from complementary funding arising from their carbon content. Some high-biodiversity regions, however, would not benefit from carbon-focused conservation, and could become under increased pressure if REDD is implemented. Our results suggest that additional gains for biodiversity conservation are possible, without compromising the effectiveness for climate change mitigation, if REDD takes biodiversity distribution into account.

No abstract

No abstract

1. Concern about climate change and energy security is stimulating land-use change, which in turn precipitates social, economic and environmental responses. It is predicted that within 20 years in the UK, bioenergy crops could occupy significant areas of rural land. Among these, dedicated biomass crops, such as Miscanthus ( Miscanthus spp.) grass and short rotation willow ( Salix spp.) coppice, differ significantly from arable crops in their growth characteristics and management. It is important that the potential impacts of these differences are assessed before large-scale, long-term planting occurs. 2. We used a Sustainability Appraisal Framework (SAF) approach to landscape planning in the UK to identify stakeholder aspirations (objectives) and associated criteria (indicators) for the planting of dedicated biomass crops. 3. The use of environmental and physical constraints mapping allowed the SAF to focus only on environmentally-acceptable locations, thereby avoiding unsustainable trade-offs. The mapping identified 3·1 million ha of land in England as suitable for planting, suggesting the UK government target of 1·1 million ha by 2020 is feasible. 4. Evaluation of the SAF identified that while biodiversity was of concern to stakeholders, some current indicators of biodiversity are not appropriate. Butterfly abundance proved the most appropriate indicator, and it was found that total abundance was greater in field margins of both willow and Miscanthus biomass crops than in arable field margins. 5. Synthesis and applications. The potential conflicts of assuring food security, water availability, energy security and biodiversity conservation are recognized as a key challenge by governments worldwide. Methods with which decision-makers can compare the performance of different land-use scenarios against sustainability objectives will be crucial for achieving optimized and sustainable use of land-based resources to meet all four challenges. Using biomass crops planting as an example, this work illustrates the potential of a Sustainability Appraisal Framework, subject to identification and agreement of appropriate indicators, in securing a holistic understanding of the wide-ranging implications of large-scale, long-term changes to rural land-use in the wider context of sustainable land-use planning per se .

The need for climate change mitigation and to meet increasing energy demands has led to a rise in the land area under bioenergy crops in many countries. There are concerns that such large-scale land conversion will conflict with food production and impact on the environment. Perennial biomass crops could be grown on more marginal agricultural land. However, for sustainable solutions, biomass yields will need to be sufficient and the wider implications of land-use changes considered. Here, focusing on Miscanthus in England as an example, we combined an empirical model with GIS to produce a yield map and estimated regional energy generation potentials after masking out areas covered by environmental and socio-economic factors which could preclude the planting of energy crops. Agricultural land quality and the distributions of currently grown food crops were then taken into account. Results showed that: (i) regional contrasts occur in the importance of different factors affecting biomass planting; (ii) areas with the highest biomass yields co-locate with food producing areas on high grade land, and; (iii) when such high grade land and unsuitable areas are excluded, a policy-related scenario for increased planting on 350,000 ha utilised 4-28% (depending on the region) of lower grade land and would not necessarily greatly impact on UK food security. We conclude that the GIS-based yield and suitability mapping described here can help identify important issues in bioenergy generation potentials and land use implications at regional or finer spatial scales that would be missed in analyses at the national level.

No abstract

No abstract