A visualization platform to analyze contextual links between natural capital and ecosystem services

To prevent further loss of our vital ecosystem services we must understand the linkages to their supporting natural capital attributes. Systematic literature reviews synthesise evidence of natural capital attribute to ecosystem service (NC-ES) linkages. However, such reviews rarely account for the context dependency of evidence that is derived from individual studies undertaken for a particular purpose, at a specific spatial scale or geographic location. To address this deficiency, we developed the LiNCAGES (Linking Natural Capital Attribute Groups to Ecosystem Services) platform for investigating the context dependency of literature-based evidence for NC-ES linkages. We demonstrate the application of the LiNCAGES platform using the OpenNESS systematic literature review of NC-ES linkages. A hypothetical use case scenario of a small-scale European forest manager is described. We find evidence for many NC-ES linkages, and trade-offs and synergies between services, is severely diminished or non-existent under certain contexts, such as larger spatial scales and European study location. The LiNCAGES platform provides a flexible tool that researchers can use to support collation, exploration and synthesis of literature-based evidence on NC-ES linkages. This is vital for providing credible and salient evidence to stakeholders on important NC-ES linkages that occur under their context, to guide effective management strategies

Environment and Rural Affairs Monitoring & Modelling Programme - ERAMMP Report-30: Analysis of National Monitoring Data in Wales for the State of Natural Resources Report 2020

The Glastir Monitoring and Evaluation Programme (GMEP, https://gmep.wales/) was at the forefront of the ecosystem approach to monitoring the impact of Pillar II schemes across the European Union - as recognised by the European Commission’s Monitoring and Evaluation Help Desk. GMEP also recruited a large sample of counterfactual “wider Wales” sites, thus enabling additional all Wales reporting. GMEP and other assimilated data represents a significant source of robust, timely and spatially relevant evidence which can contribute to SoNaRR. To facilitate use of GMEP data in SoNaRR, we present new analyses of national monitoring data which has been co-developed with SoNaRR technical leads at Natural Resources Wales (NRW)

Identifying effective approaches for monitoring national natural capital for policy use

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

Exploring relationships between land use intensity, habitat heterogeneity and biodiversity to identify and monitor areas of High Nature Value farming

Understanding how species richness is distributed across landscapes and which variables may be used as predictors is important for spatially targeting management interventions. This study uses finely resolved data over a large geographical area to explore relationships between land-use intensity, habitat heterogeneity and species richness of multiple taxa. It aims to identify surrogate landscape metrics, valid for a range of taxa, which can be used to map and monitor High Nature Value farmland (HNV). Results show that variation in species richness is distributed along two axes: land-use intensity and habitat heterogeneity. At low intensity land-use, species rich groups include wetland plants, plant habitat indicators, upland birds and rare invertebrates, whilst richness of other species groups (farmland birds, butterflies, bees) was associated with higher land-use intensity. Habitat heterogeneity (broadleaved woodland connectivity, hedgerows, habitat diversity) was positively related to species richness of many taxa, both generalists (plants, butterflies, bees) and specialists (rare birds, woodland birds, plants, butterflies). The results were used to create maps of HNV farmland. The proportion of semi-natural vegetation is a useful metric for identifying HNV type 1. HNV type 2 (defined as a mosaic of low-intensity habitats and structural elements) is more difficult to predict from surrogate variables, due to complex relationships between biodiversity and habitat heterogeneity and inadequacies of current remotely sensed data. This approach, using fine-scaled field survey data collected at regular intervals, in conjunction with remotely sensed data offers potential for extrapolating modelled results nationally, and importantly, can be used to assess change over time