Modelling and testing forest ecosystems condition account

We developed an application model based on the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework, endorsed by the United Nations Statistical Commission in 2021. This model enables mapping condition accounts for forest ecosystems using automated computation. We applied the model nationally in Spain between 2000 and 2015 to test its effectiveness. Our model follows five methodological steps to generate forest condition accounts: (i) definition and spatial delimitation of forest ecosystem types; (ii) selection of variables using the ecosystem condition typology encompassing physical, chemical, compositional, structural, functional, and landscape characteristics; (iii) establishment of reference levels, including lower (collapse) and upper (high ecosystem integrity) thresholds; (iv) aggregation of variables into condition index; and (v) calculation of a single condition index by rescaling the aggregated indicators between 0 and 1. The results obtained from the model provide valuable insights into the status and trends of individual condition indicators, as well as aggregated condition index values for forest ecosystems, in a spatially explicit manner. Overall, the condition of the forest ecosystems in Spain showed a slight increase, from 0.56 in 2000 to 0.58 in 2015. However, distinct trends were observed for each ecosystem type. For example, mixed Alpine and Macaronesia forests exhibited a significant improvement, while the continental Mediterranean coniferous forests did not show any change. This innovative approach to monitoring forest condition accounts has important potential applications in policy and decision-making processes. It can contribute to effective evidence-based nature conservation, ecosystem service management, and identifying restoration areas.

Does local Natural Capital Accounting deliver useful policy and management information? A case study of Dartmoor and Exmoor National Parks

Natural capital accounting provides a systematic framework through which to quantify the benefits of natural assets. National-scale applications have demonstrated the feasibility of developing such accounts and their value as a tool to support environmental policy and management decisions. Building on that success, there have been increasing calls for sub-national organisations (for example, protected area authorities and water companies) to develop their own natural capital accounts. As we document in this paper, recent efforts by local organisations in the UK to produce such accounts have tended to rely on a set of 'standard practice' methods, many borrowed directly from national natural capital accounting exercises. In this paper, we review those methods and apply them in producing natural capital accounts for two UK National Parks. Working with the National Park Authorities, we critically assess the usefulness of those accounts to inform local land management. On account of data gaps and significant sensitivity to methodological assumptions, our research shows that these local accounts are considered of limited practical use for land management decision making at a local scale. Through specific illustrative examples, we show that natural capital accounts for local decision-making can be improved through: the inclusion of fit-for-purpose data and valuation methods, the consideration of uncertainties, and the incorporation of ecological information and spatial aspects. We also highlight the need for the development of both standardised guidelines and readily-available tools to quantify and value ecosystem services.

Assessing the Accuracy and Potential for Improvement of the National Land Cover Database’s Tree Canopy Cover Dataset in Urban Areas of the Conterminous United States

The National Land Cover Database (NLCD) provides time-series data characterizing the land surface for the United States, including land cover and tree canopy cover (NLCD-TC). NLCD-TC was first published for 2001, followed by versions for 2011 (released in 2016) and 2011 and 2016 (released in 2019). As the only nationwide tree canopy layer, there is value in assessing NLCD-TC accuracy, given the need for cross-city comparisons of urban forest characteristics. Accuracy assessments have only been conducted for the 2001 data and suggest substantial inaccuracies for that dataset in cities. For the most recent NLCD-TC version, we used various datasets that characterize the built environment, weather, and climate to assess their accuracy in different contexts within 27 cities. Overall, NLCD underestimates tree canopy in urban areas by 9.9% when compared to estimates derived from those high-resolution datasets. Underestimation is greater in higher-density urban areas (13.9%) than in suburban areas (11.0%) and undeveloped areas (6.4%). To evaluate how NLCD-TC error in cities could be reduced, we developed a decision tree model that uses various remotely sensed and built-environment datasets such as building footprints, urban morphology types, NDVI (Normalized Difference Vegetation Index), and surface temperature as explanatory variables. This predictive model removes bias and improves the accuracy of NLCD-TC by about 3%. Finally, we show the potential applications of improved urban tree cover data through the examples of ecosystem accounting in Seattle, WA, and Denver, CO. The outputs of rainfall interception and urban heat mitigation models were highly sensitive to the choice of tree cover input data. Corrected data brought results closer to those from high-resolution model runs in all cases, with some variation by city, model, and ecosystem type. This suggests paths forward for improving the quality of urban environmental models that require tree canopy data as a key model input.

Testing ecosystem accounting in the United States: A case study for the Southeast

Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S. We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a ten-state region in the Southeast. The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015. Results illustrate how information from ecosystem accounts can contribute to policy and decision-making. Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area's environmental-economic trends. The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries. Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.

The Elusive Quest for Valuation of Coastal and Marine Ecosystem Services

Coastal and marine ecosystem (CME) services provide benefits to people through direct goods and services that may be harvested or enjoyed in situ and indirect services that regulate and support biological and geophysical processes now and in the future. In the past two decades, there has been an increase in the number of studies and journal articles designed to measure the economic value of the world’s CME services, although there is significantly less published research than for terrestrial ecosystems. This article provides a review of the literature on valuation of CME services along with a discussion of the theoretical and practical challenges that must be overcome to utilize valuation results in CME policy and planning at local, regional, and global scales. The review reveals that significant gaps exist in research and understanding of the broad range of CME services and their economic values. It also raises questions about the validity of aggregating ecosystem services as independent components to determine the value of a biome when there is little understanding of the relationships and feedbacks between ecosystems and the services they produce. Finally, the review indicates that economic valuation of CME services has had a negligible impact on the policy process in four main regions around the world. An alternative direction for CME services research would focus on valuing the world’s CME services in a wealth accounting framework.