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Agri-environment schemes (AES) are key mechanisms to deliver conservation policy, and include management to provide resources for target taxa. Mobile species may move to areas where resources are increased, without this necessarily having an effect across the wider countryside or on populations over time. Most assessments of AES efficacy have been at small spatial scales, over short timescales, and shown varying results. We developed a survey design based on orthogonal gradients of AES management at local and landscape scales, which will enable the response of several taxa to be monitored. An evidence review of management effects on butterflies, birds and pollinating insects provided data to score AES options. Predicted gradients were calculated using AES uptake, weighted by the evidence scores. Predicted AES gradients for each taxon correlated strongly, and with the average gradient across taxa, supporting the co-location of surveys across different taxa. Nine 1 × 1 km survey squares were selected in each of four regional blocks with broadly homogenous background habitat characteristics. Squares in each block covered orthogonal contrasts across the range of AES gradients at local and landscape scales. This allows the effects of AES on species at each scale, and the interaction between scales, to be tested. AES options and broad habitats were mapped in field surveys, to verify predicted gradients which were based on AES option uptake data. The verified AES gradient had a strong positive relationship with the predicted gradient. AES gradients were broadly independent of background habitat within each block, likely allowing AES effects to be distinguished from potential effects of other habitat variables. Surveys of several mobile taxa are ongoing. This design will allow mobile taxa responses to AES to be tested in the surrounding countryside, as well as on land under AES management, and potentially in terms of population change over time. The design developed here pr

Agri-environment schemes (AES) are key mechanisms to deliver conservation policy, and include management to provide resources for target taxa. Mobile species may move to areas where resources are increased, without this necessarily having an effect across the wider countryside or on populations over time. Most assessments of AES efficacy have been at small spatial scales, over short timescales, and shown varying results. We developed a survey design based on orthogonal gradients of AES management at local and landscape scales, which will enable the response of several taxa to be monitored. An evidence review of management effects on butterflies, birds and pollinating insects provided data to score AES options. Predicted gradients were calculated using AES uptake, weighted by the evidence scores. Predicted AES gradients for each taxon correlated strongly, and with the average gradient across taxa, supporting the co-location of surveys across different taxa. Nine 1 × 1 km survey squares were selected in each of four regional blocks with broadly homogenous background habitat characteristics. Squares in each block covered orthogonal contrasts across the range of AES gradients at local and landscape scales. This allows the effects of AES on species at each scale, and the interaction between scales, to be tested. AES options and broad habitats were mapped in field surveys, to verify predicted gradients which were based on AES option uptake data. The verified AES gradient had a strong positive relationship with the predicted gradient. AES gradients were broadly independent of background habitat within each block, likely allowing AES effects to be distinguished from potential effects of other habitat variables. Surveys of several mobile taxa are ongoing. This design will allow mobile taxa responses to AES to be tested in the surrounding countryside, as well as on land under AES management, and potentially in terms of population change over time. The design developed here pr

This paper describes the relationship between the landscape and the socio-economic and political characteristics of a highly biodiverse Andean region of Colombia, which is now recovering from the socio-ecological impact of protracted armed conflict. We quantify the current spatial relationship between nature and society, and we include legacy effects from the most recent period of armed conflict and its consequences of forced displacement and land use disruption. The procedure followed provides a quantitative model where a minimum number of socio-economic and political variables explain the variation in land cover. The results represent the relationship between land use intensity and the main socio-economic and political indicators, highlighting a close interaction between landscape configuration, socio-economic structure of local populations, coercive conservation and armed conflict. A simulated post-conflict landscape shows a clear transition gradient towards agrarian expansion and intensification, also in systemswhere naturalness is a relevant feature. The peace process in Colombia offers opportunities for new schemes of land planning and management, including natural resource governance and policy reforms to improve welfare and resilience of local communities. The results allow to define options for future planning given the possible consequences of socio-political legacy effects yet to fully play out across Colombia.

This paper describes the relationship between the landscape and the socio-economic and political characteristics of a highly biodiverse Andean region of Colombia, which is now recovering from the socio-ecological impact of protracted armed conflict. We quantify the current spatial relationship between nature and society, and we include legacy effects from the most recent period of armed conflict and its consequences of forced displacement and land use disruption. The procedure followed provides a quantitative model where a minimum number of socio-economic and political variables explain the variation in land cover. The results represent the relationship between land use intensity and the main socio-economic and political indicators, highlighting a close interaction between landscape configuration, socio-economic structure of local populations, coercive conservation and armed conflict. A simulated post-conflict landscape shows a clear transition gradient towards agrarian expansion and intensification, also in systemswhere naturalness is a relevant feature. The peace process in Colombia offers opportunities for new schemes of land planning and management, including natural resource governance and policy reforms to improve welfare and resilience of local communities. The results allow to define options for future planning given the possible consequences of socio-political legacy effects yet to fully play out across Colombia.

Clear, accessible, objective metrics of species status are critical to communicate the state of biodiversity and to measure progress towards biodiversity targets. However, the population data underpinning current species status metrics is often highly skewed towards particular taxonomic groups such as birds, butterflies and mammals, primarily due to the restricted availability of high quality population data. A synoptic overview of the state of biodiversity requires sampling from a broader range of taxonomic groups. Incorporating data from a wide range of monitoring and analysis methods and considering more than one measure of species status are possible ways to achieve this. Here, we utilise measures of species’ population change and extinction risk to develop three species status metrics, a Categorical Change metric, a Species Index and a Red List metric, and populate them with a wide range of data sources from the UK, covering thousands of species from across taxonomy. The species status metrics reiterate the commonly reported decline in freshwater and terrestrial species’ status in the UK in recent decades and give little evidence that this rate of decline has slowed. The utility of species status metrics is further improved if we can extrapolate beyond the species sampled to infer the status of the community. For the freshwater and terrestrial species status metrics presented here we can do this with some confidence. Nevertheless, despite the range and number of species contributing to the species metrics, significant taxonomic bias remained and we report weighting options that could help control for this. The three metrics developed were used in the State of Nature 2016 report and indications are they reached a large number of audience members. We suggest options to improve the design and communication of these and similar metrics in the future.

In order to effectively manage natural resources at national scales national decision makers require data on the natural capital which supports the delivery of ecosystem services (ES). Key data sources used for the provision of national natural capital metrics include Satellite Remote Sensing (SRS), which provides information on land cover at an increasing range of resolutions, and field survey, which can provide very high resolution data on ecosystem components, but is constrained in its potential coverage by resource requirements. Here we combine spatially representative field data from a historic national survey of Great Britain (Countryside Survey (CS)) with concurrent low resolution SRS data land cover map within modelling frameworks to produce national natural capital metrics. We present three examples of natural capital metrics; top soil carbon, headwater stream quality and nectar species plant richness which show how highly resolved, but spatially representative field data can be used to significantly enhance the potential of low resolution SRS land cover data for providing national spatial data on natural capital metrics which have been linked to ecosystem services (ES). We discuss the role of such metrics in evaluations of ecosystem service provision and areas of further development to improve their utility for stakeholders.

Clear, accessible, objective metrics of species status are critical to communicate the state of biodiversity and to measure progress towards biodiversity targets. However, the population data underpinning current species status metrics is often highly skewed towards particular taxonomic groups such as birds, butterflies and mammals, primarily due to the restricted availability of high quality population data. A synoptic overview of the state of biodiversity requires sampling from a broader range of taxonomic groups. Incorporating data from a wide range of monitoring and analysis methods and considering more than one measure of species status are possible ways to achieve this. Here, we utilise measures of species’ population change and extinction risk to develop three species status metrics, a Categorical Change metric, a Species Index and a Red List metric, and populate them with a wide range of data sources from the UK, covering thousands of species from across taxonomy. The species status metrics reiterate the commonly reported decline in freshwater and terrestrial species’ status in the UK in recent decades and give little evidence that this rate of decline has slowed. The utility of species status metrics is further improved if we can extrapolate beyond the species sampled to infer the status of the community. For the freshwater and terrestrial species status metrics presented here we can do this with some confidence. Nevertheless, despite the range and number of species contributing to the species metrics, significant taxonomic bias remained and we report weighting options that could help control for this. The three metrics developed were used in the State of Nature 2016 report and indications are they reached a large number of audience members. We suggest options to improve the design and communication of these and similar metrics in the future.

In order to effectively manage natural resources at national scales national decision makers require data on the natural capital which supports the delivery of ecosystem services (ES). Key data sources used for the provision of national natural capital metrics include Satellite Remote Sensing (SRS), which provides information on land cover at an increasing range of resolutions, and field survey, which can provide very high resolution data on ecosystem components, but is constrained in its potential coverage by resource requirements. Here we combine spatially representative field data from a historic national survey of Great Britain (Countryside Survey (CS)) with concurrent low resolution SRS data land cover map within modelling frameworks to produce national natural capital metrics. We present three examples of natural capital metrics; top soil carbon, headwater stream quality and nectar species plant richness which show how highly resolved, but spatially representative field data can be used to significantly enhance the potential of low resolution SRS land cover data for providing national spatial data on natural capital metrics which have been linked to ecosystem services (ES). We discuss the role of such metrics in evaluations of ecosystem service provision and areas of further development to improve their utility for stakeholders.

Ways of reducing the drivers of global biodiversity loss and degradation of ecosystem services are needed more than ever before. Policy options must be based on the best evidence of the role of multiple driving forces. Increasingly, a significant part of the evidence base comes from attributing signals of biological change detected in large-scale analytical surveys to a range of possible causal factors. We highlight a number of subtle difficulties that can beset the challenge of detecting such correlative relationships. These are as follows: (1) The Modifiable Area Unit Problem. (2) Incomplete explanatory variable data. (3) Lack of control over the replication and crossing of driving variables. In most cases these problems can be avoided by more careful specification of the scientific question and application of relatively new analytical techniques. Ignoring them can lead to mis-specification of hypothesised driver–state–impact relationships and flawed conclusions as to the most important causes of change.

Ways of reducing the drivers of global biodiversity loss and degradation of ecosystem services are needed more than ever before. Policy options must be based on the best evidence of the role of multiple driving forces. Increasingly, a significant part of the evidence base comes from attributing signals of biological change detected in large-scale analytical surveys to a range of possible causal factors. We highlight a number of subtle difficulties that can beset the challenge of detecting such correlative relationships. These are as follows: (1) The Modifiable Area Unit Problem. (2) Incomplete explanatory variable data. (3) Lack of control over the replication and crossing of driving variables. In most cases these problems can be avoided by more careful specification of the scientific question and application of relatively new analytical techniques. Ignoring them can lead to mis-specification of hypothesised driver–state–impact relationships and flawed conclusions as to the most important causes of change.