A common typology for ecosystem characteristics and ecosystem condition variables

Panel-based assessment of ecosystem condition as a platform for adaptive and knowledge driven management

Ecosystems are subjected to increasing exposure to multiple anthropogenic drivers. This has led to the development of national and international accounting systems describing the condition of ecosystems, often based on few, highly aggregated indicators. Such accounting systems would benefit from a stronger theoretical and empirical underpinning of ecosystem dynamics. Operational tools for ecosystem management require understanding of natural ecosystem dynamics, consideration of uncertainty at all levels, means for quantifying driver-response relationships behind observed and anticipated future trajectories of change, and an efficient and transparent synthesis to inform knowledge-driven decision processes. There is hence a gap between highly aggregated indicator-based accounting tools and the need for explicit understanding and assessment of the links between multiple drivers and ecosystem condition as a foundation for informed and adaptive ecosystem management. We describe here an approach termed PAEC (Panel-based Assessment of Ecosystem Condition) for combining quantitative and qualitative elements of evidence and uncertainties into an integrated assessment of ecosystem condition at spatial scales relevant to management and monitoring. The PAEC protocol is founded on explicit predictions, termed phenomena, of how components of ecosystem structure and functions are changing as a result of acting drivers. The protocol tests these predictions with observations and combines these tests to assess the change in the condition of the ecosystem as a whole. PAEC includes explicit, quantitative or qualitative, assessments of uncertainty at different levels and integrates these in the final assessment. As proofs-of-concept we summarize the application of the PAEC protocol to a marine and a terrestrial ecosystem in Norway.

Synergies and complementarities between ecosystem accounting and the Red List of Ecosystems

Safeguarding biodiversity and human well-being depends on sustaining ecosystems. Two global standards for quantifying ecosystem change, the International Union for Conservation of Nature Red List of Ecosystems (RLE) and the United Nations System of Environmental-Economic Accounting Ecosystem Accounting (EA), underpin headline indicators for the Kunming-Montreal Global Biodiversity Framework. We analyse similarities and differences between the standards to understand their complementary roles in environmental policy and decision-making. The standards share key concepts, definitions of ecosystems and spatial data needs, meaning that similar data can be used in both. Their complementarities stem from their differing purposes and thus how data are analysed and interpreted. Although both record changes in ecosystem extent and condition, the RLE analyses the magnitude of change in terms of risk of ecosystem collapse and biodiversity loss, whereas EA links ecosystem change with the ecosystem's contributions to people and the economy. We recommend that the RLE and EA should not be treated as unrelated nor undertaken in isolation. Developing them in concert can exploit their complementarities while ensuring consistency in foundational data, in particular ecosystem classifications, maps and condition variables. Finding pathways for co-investment in foundational data, and for knowledge-sharing between people and organizations who undertake RLE assessments and accounting, will improve both processes and outcomes for biodiversity, ecosystems and people.

A decision methodology for site-level ecosystem accounting

The United Nations System of Environmental-Economic Accounting Ecosystem Accounting (SEEA EA) framework is the international standard for ecosystem accounting. To date, application of SEEA EA has been predominantly at large scales, usually at landscape and national levels. However, many environmental management decisions are taken locally, in site-specific contexts. While the use of SEEA EA continues to develop at all scales, there is currently no widely endorsed methodology for employing SEEA EA at local scales, such as the site level. We present a methodology for developing site-level ecosystem accounts, describing the important decisions at each step of the process. We also provide two case studies that demonstrate the context-dependent nature of the decision-making process of ecosystem accounting at small scales. The two major challenges for site-level accounting are stakeholder engagement and data availability. As the use of SEEA EA continues to increase in policy and decision-making processes worldwide, there is a need for local-scale case studies that adapt this methodology across a broad range of contexts. Our case studies provide some of the first published examples of the application of SEEA EA at the site level and are intended to promote consistent implementation of ecosystem accounting across scales.

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.

Accounting for forest condition in Europe based on an international statistical standard

Covering 35% of Europe's land area, forest ecosystems play a crucial role in safeguarding biodiversity and mitigating climate change. Yet, forest degradation continues to undermine key ecosystem services that forests deliver to society. Here we provide a spatially explicit assessment of the condition of forest ecosystems in Europe following a United Nations global statistical standard on ecosystem accounting, adopted in March 2021. We measure forest condition on a scale from 0 to 1, where 0 represents a degraded ecosystem and 1 represents a reference condition based on primary or protected forests. We show that the condition across 44 forest types averaged 0.566 in 2000 and increased to 0.585 in 2018. Forest productivity and connectivity are comparable to levels observed in undisturbed or least disturbed forests. One third of the forest area was subject to declining condition, signalled by a reduction in soil organic carbon, tree cover density and species richness of threatened birds. Our findings suggest that forest ecosystems will need further restoration, improvements in management and an extended period of recovery to approach natural conditions.

Trends and gaps in biodiversity and ecosystem services research: A text mining approach

Understanding the relationship between biodiversity conservation and ecosystem services concepts is essential for evidence-based policy development. We used text mining augmented by topic modelling to analyse abstracts of 15 310 peer-reviewed papers (from 2000 to 2020). We identified nine major topics; "Research & Policy", "Urban and Spatial Planning", "Economics & Conservation", "Diversity & Plants", "Species & Climate change", "Agriculture", "Conservation and Distribution", "Carbon & Soil & Forestry", "Hydro-& Microbiology". The topic "Research & Policy" performed highly, considering number of publications and citation rate, while in the case of other topics, the "best" performances varied, depending on the indicator applied. Topics with human, policy or economic dimensions had higher performances than the ones with 'pure' biodiversity and science. Agriculture dominated over forestry and fishery sectors, while some elements of biodiversity and ecosystem services were under-represented. Text mining is a powerful tool to identify relations between research supply and policy demand.

Inclusion of condition in natural capital assessments is critical to the implementation of marine nature-based solutions

Current approaches to measure ecosystem services (ES) within natural capital (NC) and nature-based solutions (NbS) assessments are generally coarse, often using a single figure for ecosystem services (e.g., nutrient remediation or blue carbon sequestration) applied to the local or national habitat stock, which fails to take account of local ecosystem conditions and regional variability. As such, there is a need for improved understanding of the link between habitat condition and ES provision, using comparable indicators in order to take more informed management decisions. Here the UK, Solent Marine Sites (SEMS) is used as a case study system to demonstrate how Water Framework Directive (WFD) 'ecological status' and other indicators of ecosystem condition (state or quality) can be coupled with habitat extent information to deliver a more precise locally-tailored NC approach for active coastal and marine habitat restoration. Habitat extent and condition data are collected for seven NbS relevant coastal habitats (littoral sediment, mat-forming green macroalgae, subtidal sediment, saltmarsh, seagrass, reedbeds and native oyster beds). The workflow includes: 1) biophysical assessment of regulatory ES; 2) monetary valuation; and 3) compilation of future scenarios of habitat restoration and creation. The results indicate that incorporating classifications by condition indices into local NC extent accounts improved ES benefits by 11-67%. This suggests that omitting condition from NC assessments could lead to undervaluation of ES benefits. Future scenarios of restoration in the SEMS also show that the additional regulatory benefits of reaching 'Good' ecological status are £376 million annually, but could be as much as £1.218 billion if 'High'status and all habitat creation targets were met. This evidence of the potential value of restoration and importance of including condition indices in assessments is highly relevant to consider when investing in water ecosystems conservation and restoration as called for by the UN Decade on Ecosystem Restoration (2021-2030), and more generally in global nutrient neutrality and blue carbon policy strategies.

Disentangling the ecosystem service 'flood regulation': Mechanisms and relevant ecosystem condition characteristics

Riverine floods cause increasingly severe damages to human settlements and infrastructure. Ecosystems have a natural capacity to decrease both severity and frequency of floods. Natural flood regulation processes along freshwaters can be attributed to two different mechanisms: flood prevention that takes place in the whole catchment and flood mitigation once the water has accumulated in the stream. These flood regulating mechanisms are not consistently recognized in major ecosystem service (ES) classifications. For a balanced landscape management, it is important to assess the ES flood regulation so that it can account for the different processes at the relevant sites. We reviewed literature, classified them according to these mechanisms, and analysed the influencing ecosystem characteristics. For prevention, vegetation biomass and forest extent were predominant, while for mitigation, the available space for water was decisive. We add some aspects on assessing flood regulation as ES, and suggest also to include flood hazard into calculations.

Ecosystem condition underpins the generation of ecosystem services: an accounting perspective

There is a linkage between the condition of ecosystems and the services they provide. In the accounting framework set by the United Nations System of integrated Environmental Economic Accounting – Ecosystem Accounts (SEEA EA), two different sets of accounts assess and monitor ecosystem condition and ecosystem services, respectively. The former are reported as indicators in an asset account format, while the latter are reported as supply and use tables. Without a concrete linkage, the two sets of accounts run in parallel: only an ex-post correlation analysis could confirm (or not) a common path. On the other hand, a clear linkage could create a sequence that justifies and supports the statement that any change in ecosystem condition will affect services and, in turn, the benefits provided to economy and society. Concrete applications undertaken under the project “Integrated system for Natural Capital Accounts” demonstrate at which stage a direct connection can occur between ecosystem condition and ecosystem services accounting. The paper starts with a theoretical background meant to set the basic concepts underlying the transition from condition to services. Next, the accounting framework for condition accounts is briefly presented: the specific ecosystem services case studies concern flood control and crop pollination. In the discussion, a simple proposal is drafted to facilitate a possible procedure for those practitioners interested in having condition and ES accounts operationally linked.

Assessing ecosystem condition at the national level in Hungary - indicators, approaches, challenges

The availability of robust and reliable spatial information on ecosystem condition is of increasing importance in informing conservation policy. Recent policy requirements have sparked a renewed interest in conceptual questions related to ecosystem condition and practical aspects like indicator selection, resulting in the emergence of conceptual frameworks, such as the System of Environmental-Economic Accounting - Ecosystem Accounting (SEEA-EA) and its Ecosystem Condition Typology (ECT). However, while such frameworks are essential to ensure that condition assessments are comprehensive and comparable, large-scale practical implementation often poses challenges that need to be tackled within stringent time and cost frames.

We present methods and experiences of the national-level mapping and assessment of ecosystem condition in Hungary. The assessments covered the whole country, including all major ecosystem types present. The methodology constitutes four approaches of quantifying and mapping condition, based on different interpretations of naturalness and hemeroby, complemented by two more using properties that ‘overarch’ ecosystem types, such as soil and landscape attributes. In order to highlight their strengths and drawbacks, as well as to help reconcile aspects of conceptual relevance with practical limitations, we retrospectively evaluated the six mapping approaches (and the resulting indicators) against the indicator selection criteria suggested in the SEEA-EA. The results show that the various approaches have different strengths and weaknesses and, thus, their joint application has a higher potential to address the specific challenges related to large-scale ecosystem condition mapping.

Developing peatland ecosystem accounts to guide targets for restoration

The United Nations System of Environmental and Economic Accounting - Ecosystem Accounting (SEEA EA) is a geospatial approach, whereby existing data on ecosystem stocks and flows are collated to show changes over time. The framework has been proposed as a means to track and monitor ecosystem restoration targets across the EU. Condition is a key consideration in the conservation assessment of habitats protected under the EU Habitats Directive and ecosystem condition accounts are also integral to the SEEA EA. While SEEA EA accounts have been developed at EU level for an array for ecosystem types, condition accounts remain the least developed. Collating available datasets under the SEEA EA framework, we developed extent and rudimentary condition accounts for peatland ecosystems at catchment scale in Ireland. Information relating to peatland ecosystem sub-types or habitat types was collated for peatland habitats listed under Annex I of the EU Habitats Directive, as well as degraded peatlands not included in EU nature conservation networks. While data relating to peatland condition were limited, understanding changes in ecosystem extent and incorporating knowledge of habitat types and degradation served as a proxy for ecosystem condition in the absence of more comprehensive data. This highlighted the importance of the ecosystem extent account, which underpins all other accounts in the SEEA EA framework. Reflecting findings at EU level, drainage, disturbance and land conversion were identified as the main pressures affecting peatland condition. We highlighted a number of options to gather data to build more robust, time-series extent and condition accounts for peatlands at varying accounting scales. Overall, despite the absence of comprehensive data, bringing information under the SEEA EA framework is considered a good starting point, with the integration of expert ecological opinion considered essential to ensure development of reliable accounts, particularly when working at ecosystem sub-type (habitat type) and catchment scale.

Applying the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework at catchment scale to develop ecosystem extent and condition accounts

Ecosystem accounting is a tool to integrate nature into decision-making in a more structured way. Applying the use of nationally available datasets at catchment scale and following the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework, we present results from a catchment case study in Ireland, highlighting findings specifically in relation to the development of ecosystem extent and condition accounts. In the absence of a national ecosystem map, CORINE landcover mapping formed the basic data for extent and type of ecosystems, distinguishing woodlands and forest, peatland and heathland, grasslands and cropland and urban areas, with limited coverage of linear freshwater rivers, hedgerows and coastal ecosystems. Additional remote sensing data provided higher resolution at catchment scale, while limited site-level survey data were available. Condition data gathered for reporting under the EU Water Framework Directive were available at sub-basin level for surface waterbodies. Data were available at national level for habitats reported for the EU under the Habitats Directive (59 habitats reported), covering ~ 25% of the study area. Data for ecosystem types outside of these reporting frameworks were in the form of ancillary data only, providing information on pressures, threats and intensity of use. Our findings in Ireland reflect work across the European region, highlighting the role of data gathering and stakeholder engagement. We outline some of the data gaps to provide information for future research and alignment of data for the purpose of NCA, both at catchment and national scale.