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Climate change has pervasive impacts on Earth’s ecosystems, but the diversity and complexity of ecosystems makes estimating the severity of impacts and the resulting risk of collapse difficult. In this perspective, we conceptualise the challenge of understanding how climate change alters ecosystems, and how to reliably measure those changes in ecosystem risk assessments, focussing on the IUCN Red List of Ecosystems. We propose solutions to resolve these challenges – using diverse teams, conceptual models, diverse using data sources including projections, learning from analogous ecosystems, and evaluating uncertainties – and we identify research gaps to bridge these challenges. Together, these solutions will improve our capacity to produce reliable assessments of collapse risk under climate change to inform timely and effective ecosystem conservation.
The human impact on nature has now reached a level at which the well-being of future human society is at risk. Therefore, transformative change in society is needed. Environmental assessments contribute to shaping environmental policy, potentially leveraging transformative change. Red Lists are a key information source on the state of biodiversity. Our aim was to study the Red List authors’ perceptions of how Red Lists contribute to leveraging sustainability changes. We interviewed 15 of the authors of the forest and peatland sections of the Finnish Red List of Ecosystems 2018. We used the framework of sustainability leverage points to locate sustainability changes that Red Lists have leveraged in the social part of the Finnish social-ecological system. Our results show how the assessors perceived the influence of the Red Lists at most of the leverage points, including the deepest ones, and how these influences simultaneously co-exist in several leverage points. The most prominent sustainability changes were linked with legislation and information flows, whereas current paradigms, system goals and legislation appeared to prevent Red Lists from leveraging sustainability changes in Finland. We conclude that the production and dissemination processes of Red List knowledge can make an important contribution to sustainability changes.
As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of ‘living in harmony with nature’1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management³. Ecosystems vary in their biota⁴, service provision⁵ and relative exposure to risks⁶, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth’s ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.
The European Space Agency’s Sentinel satellites have laid the foundation for global land use land cover (LULC) mapping with unprecedented detail at 10 m resolution. We present a cross-comparison and accuracy assessment of Google’s Dynamic World (DW), ESA’s World Cover (WC) and Esri’s Land Cover (Esri) products for the first time in order to inform the adoption and application of these maps going forward. For the year 2020, the three global LULC maps show strong spatial correspondence (i.e., near-equal area estimates) for water, built area, trees and crop LULC classes. However, relative to one another, WC is biased towards over-estimating grass cover, Esri towards shrub and scrub cover and DW towards snow and ice. Using global ground truth data with a minimum mapping unit of 250 m2, we found that Esri had the highest overall accuracy (75%) compared to DW (72%) and WC (65%). Across all global maps, water was the most accurately mapped class (92%), followed by built area (83%), tree cover (81%) and crops (78%), particularly in biomes characterized by temperate and boreal forests. The classes with the lowest accuracies, particularly in the tundra biome, included shrub and scrub (47%), grass (34%), bare ground (57%) and flooded vegetation (53%). When using European ground truth data from LUCAS (Land Use/Cover Area Frame Survey) with a minimum mapping unit of
National forest inventories (NFI) in Finland provide empirical evidence for a marked increase in tree growth, total forest area, and total timber volume over the past century. Meanwhile, the assessments of threatened forest species and habitats indicate continuous degradation of biodiversity in Finnish forests. To shed light on this seeming paradox, we summarized the temporal patterns of forest characteristics (indicators) that have major influence on biodiversity, comparing the structure of current Finnish forests with natural and historical references. Using a variety of data sources, we estimated the proportion of area of old-growth forest and of deciduous-dominated forests, the density of large trees, and the amount of dead wood in Finnish forests under natural reference conditions, in the 1750s, 1920s (NFI1), and 2010s (NFI12). Our results show that levels of the forest structures essential to maintain ecologically diverse forests are below those that likely
prevailed in Finland under natural reference conditions and in the 1750s. This scarcity is particularly pronounced for dead wood volumes and old forest area. The marked increase in the volume of living trees during the last century did not translate into improved biodiversity indicators and has not been effective for turning the tide of biodiversity loss in Finnish forests. We discuss actions that are necessary to safeguard forest biodiversity in Finland both in terms of protected areas and management in production forest.
https://journal.fi/msff/article/view/120306
Ecosystems worldwide are under increasing threat. We applied a standardized method for assessing the risk of ecosystem collapse, the International Union for Conservation of Nature (IUCN) Red List of Ecosystems, to coral reefs in the Western Indian Ocean (WIO), covering 11,919 km² of reef (~5% of the global total). Our approach combined indicators of change in historic ecosystem extent, ecosystem functioning (hard corals, fleshy algae, herbivores and piscivores) and projected sea temperature warming. We show that WIO coral reefs are vulnerable to collapse at the regional level, while in 11 nested ecoregions they range from critically endangered (islands, driven by future warming) to vulnerable (continental coast and northern Seychelles, driven principally by fishing pressure). Responses to avoid coral reef collapse must include ecosystem-based management of reefs and adjacent systems combined with mitigating and adapting to climate change. Our approach can be replicated across coral reefs globally to help countries and other actors meet conservation and sustainability targets set under multiple global conventions—including the Convention on Biological Diversity’s post-2020 global biodiversity framework and the United Nations’ Sustainable Development Goals.
Recent global initiatives in ecosystem restoration offer an unprecedented opportunity to improve biodiversity conservation and human health and well-being. Ecosystems form a core component of biodiversity. They provide humans with multiple benefits – a stable climate and breathable air; water, food and materials; and protection from disaster and disease. Ecosystem restoration, as defined by the UN Decade on Ecosystem Restoration, includes a range of management interventions that aim to reduce impacts on and assist in the recovery of ecosystems that have been damaged, degraded or destroyed. This Guide promotes the application of the science of ecosystem risk assessment, which involves measuring the risk of ecosystem collapse, in ecosystem restoration. It explores how the IUCN Red List of Ecosystems and ecosystem restoration can be jointly deployed to reduce risk of ecosystem collapse.
The UN System of Environmental-Economic Accounting Ecosystem Accounting (SEEA EA) aims at regular and standardised stocktaking of the extent of ecosystems, their condition, and the services they provide to society. Recording the condition of ecosystems is one of the most complex pieces in this exercise and needs to be supported by consistent guidelines. SEEA EA defines the condition of an ecosystem as its overall quality, measured in terms of quantitative metrics describing its abiotic and biotic characteristics. One of the key challenges lies in identifying the most appropriate metrics for each ecosystem type that capture these essential characteristics.
The objective of this paper is to create a well-defined framework for transparent and operative development of ecosystem condition indicators, which can be used in ecosystem accounting and ecosystem assessment studies. Starting from the SEEA EA documentation and a small targeted systematic review, we identified 12 key criteria, which we grouped according to their roles during the indicator development process. Five conceptual criteria (intrinsic relevance, instrumental relevance, sensitivity, directional meaning, and framework conformity) outline the priorities for identifying relevant characteristics of the ecosystems. Five practical criteria (validity, reliability, availability, simplicity, and compatibility) provide guidance on identifying concrete quantitative metrics for the selected characteristics. Finally, two ensemble criteria (comprehensiveness, and parsimony) ensure the completeness and complementarity of the final set of metrics.
To tackle the climate and biodiversity crises, the condition of ecosystems needs to be better recognized in national economic planning. The proposed framework supports the selection of a concise set of salient and credible ecosystem condition indicators through a transparent, repeatable and scientific process. This can make the compilation of ecosystem condition accounts more accessible and more standardised on a global level, which is a key prerequisite for the success of SEEA EA. Additionally, the framework presented in this paper may be useful in other contexts where ecological, environmental, or sustainability indicators need to be identified.
The environmental crises currently gripping the Earth have been codified in a new proposed geological epoch: the Anthropocene. This epoch, according to the Anthropocene Working Group, began in the mid-20th century and reflects the “great acceleration” that began with industrialization in Europe [J. Zalasiewicz et al., Anthropocene 19, 55–60 (2017)]. Ironically, European ideals of protecting a pristine “wilderness,” free from the damaging role of humans, is still often heralded as the antidote to this human-induced crisis [J. E. M. Watson et al., Nature , 563, 27–30 (2018)]. Despite decades of critical engagement by Indigenous and non-Indigenous observers, large international nongovernmental organizations, philanthropists, global institutions, and nation-states continue to uphold the notion of pristine landscapes as wilderness in conservation ideals and practices. In doing so, dominant global conservation policy and public perceptions still fail to recognize that Indigenous and local peoples have long valued, used, and shaped “high-value” biodiverse landscapes. Moreover, the exclusion of people from many of these places under the guise of wilderness protection has degraded their ecological condition and is hastening the demise of a number of highly valued systems. Rather than denying Indigenous and local peoples’ agency, access rights, and knowledge in conserving their territories, we draw upon a series of case studies to argue that wilderness is an inappropriate and dehumanizing construct, and that Indigenous and community conservation areas must be legally recognized and supported to enable socially just, empowering, and sustainable conservation across scale.
The Dasgupta Review is an independent, global review on the Economics of Biodiversity led by Professor Sir Partha Dasgupta (Frank Ramsey Professor Emeritus, University of Cambridge). The Review was commissioned in 2019 by HM Treasury and has been supported by an Advisory Panel drawn from public policy, science, economics, finance and business.
The Review calls for changes in how we think, act and measure economic success to protect and enhance our prosperity and the natural world. Grounded in a deep understanding of ecosystem processes and how they are affected by economic activity, the new framework presented by the Review sets out how we should account for Nature in economics and decision-making.
The final Review comprises the Full Report, an Abridged Version and the Headline Messages.
Human activity is accelerating biodiversity loss despite international commitments to prevent extinction and habitat degradation. To bend the curve, international goals must be translated into national targets and actions. Tools to do this are highly needed, but scarce. We present a first attempt to operationalize national Red Lists by using the quantitative criteria of risk assessment as quantifiable objectives in a Red to Green framework. The framework allows for a systematic setting of conservation goals, with quantifiable conservation objectives, and identifying conservation actions to achieve these objectives. We developed an index of conservation outcome, modified from the Red List Index, to quantify the potential conservation outcomes of implementing suggested conservation actions. We tested the framework and index on 123 Red Listed species and habitats prioritized for conservation by the Norwegian government. The policy-defined goal was to downlist them by one Red List category by 2035. We identified land use change as the greatest threat. For 70% of species and 20% of habitats, knowledge was insufficient to recommend conservation actions. Further, due to unmanageable threats, alternative, lower-ambitioned goals were suggested for 30% of the species. Our case show that reaching national goals is difficult, but possible if main constraints are resolved. Through a systematic assessment of knowledge and conservation actions, the framework forms a solid foundation for developing national action plans for biodiversity conservation, allowing for prioritization and implementation of conservation actions and reporting on progress. This is an important first step to reach national targets defined from international goals.
Sustainable nature management and ecosystem conservation depends critically on scientifically sound and stakeholder-relevant analytical frameworks for monitoring and assessing ecological condition. Several general frameworks are currently being developed internationally, including the Essential Biodiversity Variables (EBV), and the UN’s SEEA EEA Ecosystem Condition Typology (ECT). However, there has so far been few attempts to develop empirical implementations of these general frameworks, or to assess their applicability for environmental decision-making at national or regional scales. In this paper, we aim to fill this implementation gap by demonstrating a practical application of an empirically-based ecological condition assessment framework, the Index-Based Ecological Condition Assessment (IBECA). IBECA defines seven major classes of indicators of ecological condition, representing distinct ecosystem characteristics, and empirically synthesizes indicators for each of these characteristics from various monitoring data. We exemplify and explore the utility and robustness of IBECA using a case study from forest and alpine ecosystems in central Norway, and we investigate how IBECA aligns with the two international frameworks EBV and ECT. In particular, we analyze how the different approaches to categorize indicators into classes affect the assessment of ecological condition, both conceptually and using the case study indicators. We used eleven indicators for each of the two ecosystems and assessed the ecological condition according to IBECA for i) each individual indicator, ii) the seven ecosystem characteristics (indicator classes), and iii) a synthetic ecological condition value for the whole ecosystem. IBECA challenges key concepts of the international frameworks and illustrates practical challenges for national or regional level implementation. We identify three main strengths with the IBECA approach: i) it provides a transparent and management-relevant quantitative approach allowing assessment of spatio-temporal variation in ecological condition across indicators, characteristics and ecosystems, ii) the high degree of flexibility and transparency facilitates updating the ecological condition assessments, also back in time, as improved data and knowledge of indicators emerge, and iii) the quantitative and flexible procedure makes it a cost-effective approach suitable for fast management implementations. More generally, we stress the need for carefully choosing appropriate classification and aggregation approaches in ecological condition assessments, and for transparent and data-driven analytical approaches that can be adjusted as knowledge improves.
The UN System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) aims at regular and standardised stocktaking on the extent of ecosystems, their condition and the services they provide to society. Recording the condition of ecosystems is one of the most complex pieces in this exercise, needing to be supported by robust and consistent guidelines. SEEA EEA defines the condition of an ecosystem as its overall quality, measured in terms of quantitative metrics describing both abiotic and biotic characteristics. The main objective of this paper is to propose a simple universal classification (typology) for these ecosystem condition characteristics and metrics, based on long standing ecological concepts and traditions.
The proposed SEEA EEA Ecosystem Condition Typology (SEEA ECT) is a hierarchical classification consisting of six classes grouped into three main groups (abiotic, biotic and landscape-level ecosystem characteristics). In order to facilitate practical applications, SEEA ECT is cross-linked to the most relevant existing typologies for ecosystem characteristics currently used for other purposes. To ensure clarity and practicality, we identified potential overlaps between classes and also identified the most important groups of ‘ancillary data’ that should not be considered as ecosystem condition characteristics. We consider that this new typology for ecosystem condition will create a meaningful reporting structure for ecosystem condition accounts, thus facilitating its standardisation and broad application.
Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high‐profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.
Measuring the status and trends of biodiversity is critical for making informed decisions about the conservation, management or restoration of species, habitats and ecosystems. Defining the reference state against which status and change are measured is essential. Typically, reference states describe historical conditions, yet historical conditions are challenging to quantify, may be difficult to falsify, and may no longer be an attainable target in a contemporary ecosystem. We have constructed a conceptual framework to help inform thinking and discussion around the philosophical underpinnings of reference states and guide their application. We characterize currently recognized historical reference states and describe them as Pre-Human, Indigenous Cultural, Pre-Intensification and Hybrid-Historical. We extend the conceptual framework to include contemporary reference states as an alternative theoretical perspective. The contemporary reference state framework is a major conceptual shift that focuses on current ecological patterns and identifies areas with higher biodiversity values relative to other locations within the same ecosystem, regardless of the disturbance history. We acknowledge that past processes play an essential role in driving contemporary patterns of diversity. The specific context for which we design the contemporary conceptual frame is underpinned by an overarch-ing goal-to maximize biodiversity conservation and restoration outcomes in existing ecosystems. The contemporary reference state framework can account for the inherent differences in the diversity of biodiversity values (e.g. native species richness, habitat complexity) across spatial scales, communities and ecosystems. In contrast to historical reference states, contemporary references states are measurable and fal-sifiable. This 'road map of reference states' offers perspective needed to define and assess the status and trends in biodiversity and habitats. We demonstrate the contemporary reference state concept with an example from southeastern Australia. Our framework provides a tractable way for policy-makers and practitioners to navigate biodiversity assessments to maximize conservation and restoration outcomes in contemporary ecosystems.
Biodiversity underpins the supply of ecosystem services essential for well-being and economic development, yet
biodiversity loss continues at a substantial rate. Linking biodiversity indicators with national economic accounts
provides a means of mainstreaming biodiversity into economic planning and monitoring processes. Here we
examine the various strategies for biodiversity indicators to be linked into national economic accounts, specifically
the System of Environmental-Economic Accounts Experimental Ecosystem Accounting (SEEA EEA)
framework. We present what has been achieved in practice, using various case studies from across the world.
These case studies demonstrate the potential of economic accounting as an integrating, mainstreaming framework
that explicitly considers biodiversity. With the right indicators for the different components of biodiversity and scales of biological organisation, this can directly support more holistic economic planning approaches. This will be a significant step forward from relying on the traditional indicators of national economic accounts to guide national planning. It is also essential if society’s objectives for biodiversity and sustainable development are to be met.
The Myanmar National Ecosystem Assessment contributes to the GEF funded Strengthening Sustainability of Protected Area Management in Myanmar project. To support the Myanmar National Ecosystem Assessment, Myanmar’s terrestrial ecosystems were assessed under the International Union for the Conservation of Nature (IUCN) Red List of Ecosystems Categories and Criteria. This report summarises the methods and findings of the assessment, including detailed ecological descriptions of the 64 ecosystem types assessed.
A total of 64 ecosystem types were identified and evaluated under the IUCN Red List of Ecosystems categories and criteria. Twenty-nine (45.3%) ecosystems were assigned a threatened status, consisting of 8 (12.5%) Critically Endangered ecosystem types, 9 (14.1%) Endangered and 12 (18.8%) Vulnerable ecosystem types. One ecosystem type, Central Ayeyarwady Palm Savanna ecosystem types was confirmed as Collapsed. A further two ecosystem types, Ayeyarwady kanazo swamp forest and Southern Rakhine hills evergreen rainforest, were assessed with an upper plausible status outcome of Collapsed, although their final assessment was Critically Endangered.
Twenty-eight ecosystem types were assessed as Near Threatened or Least Concern. However, a post-assessment expert review by experts suggested that 11 of the 25 Least Concern ecosystems could qualify for a different assessment outcome if more data was available. These 11 ecosystems were reclassified to Data Deficient.
Thus, 17 of Myanmar’s ecosystem types were classified as Data Deficient. Data deficient ecosystem types were primarily ecosystems for which there were historical records, but with insufficient published information to assess the criteria (e.g. Rocky Tanintharyi karst). Alternatively, there were insufficient distribution records to incorporate into our mapping workflow to allow assessments of Criterion A and B (e.g. Grassy saltmarsh). Data deficient ecosystems also tended to occur in regions that were inaccessible to field researchers due to travel restrictions (e.g. Shan limestone grasslands). Urgent further work to confirm the distribution and assess the status of these data deficient ecosystems is recommended.
This IUCN Red List of Ecosystems assessment has shown a dire situation for Myanmar’s ecosystems. Of the area assessed, nearly two-thirds (64%, 426,628 km2) is mapped as a natural ecosystem type, but of this over half (57.8%, 24,750 km2) of remaining area contains a threatened ecosystem type (CR, EN or VU). This means over one third of Myanmar’s land area contains threatened ecosystems. There needs to be an increase in conservation efforts to reverse this situation and slow the trajectory towards collapse for ecosystems that are not currently threatened. Conservation planning will be key to identify what are the best conservation actions and where to apply them to reduce the risk of collapse for Myanmar’s natural ecosystems.
Ecosystem condition accounts are part of the System of Environmental-Economic Accounting – Experimental Ecosystem Accounting (SEEA EEA). An ecosystem condition account contains aggregated statistical information about the overall abiotic and biotic quality of an ecosystem at a policy relevant spatial scale. This article reviews 23 publicly-accessible reports undertaken or commissioned by government agencies, academic and non-government organisations that discuss or present an ecosystem condition account. This analysis revealed that ecosystem condition is usually reported for one or more ecosystem types, but there is little consistency in the terminology used to define ecosystem types. All case studies report variables or indicators that measure specific ecosystem characteristics in order to make inferences about the overall condition of ecosystems. All studies included biotic indicators and almost all studies included species-based indicators in the condition account. The thematic aggregation of indicators into a single composite index (or in a few composite sub-indices) is not a standard practice, but applied in about half of the studies. The definition and use of a reference condition or reference levels for specific indicators against which the reported condition can be evaluated is not a standard practice, but was applied in about half of the studies. Based on this analysis, we suggest the revision of the SEEA EEA to propose a globally-consistent typology of ecosystem types; to recommend a list of ecosystem condition indicators according to an agreed classification; to provide further guidance on aggregation methods and on the development of an ecosystem condition index that can be used to compare ecosystem condition across ecosystem types and across different accounting areas; to provide further guidance on how best to set reference levels and reference conditions against which the past, current and future ecosystem condition can be assessed; and to propose a standard set of statistical tables for reporting the condition account.
Gross domestic product (GDP) summarizes a vast amount of economic information in a single monetary metric that is widely used by decision makers around the world. However, GDP fails to capture fully the contributions of nature to economic activity and human well-being. To address this critical omission, we develop a measure of gross ecosystem product (GEP) that summarizes the value of ecosystem services in a single monetary metric. We illustrate the measurement of GEP through an application to the Chinese province of Qinghai, showing that the approach is tractable using available data. Known as the “water tower of Asia,” Qinghai is the source of the Mekong, Yangtze, and Yellow Rivers, and indeed, we find that water-related ecosystem services make up nearly two-thirds of the value of GEP for Qinghai. Importantly most of these benefits accrue downstream. In Qinghai, GEP was greater than GDP in 2000 and three-fourths as large as GDP in 2015 as its market economy grew. Large-scale investment in restoration resulted in improvements in the flows of ecosystem services measured in GEP (127.5%) over this period. Going forward, China is using GEP in decision making in multiple ways, as part of a transformation to inclusive, green growth. This includes investing in conservation of ecosystem assets to secure provision of ecosystem services through transregional compensation payments.
Global statistical standards are being developed
In 2014, the International Union for Conservation of Nature adopted the Red List of Ecosystems (RLE) criteria as the global standard for assessing risks to terrestrial, marine, and freshwater ecosystems. Five years on, it is timely to ask what impact this new initiative has had on ecosystem management and conservation. In this policy perspective, we use an impact evaluation framework to distinguish the outputs, outcomes, and impacts of the RLE since its inception. To date, 2,821 ecosystems in 100 countries have been assessed following the RLE protocol. Systematic assessments are complete or underway in 21 countries and two continental regions (the Americas and Europe). Countries with established ecosystem policy infrastructure have already used the RLE to inform legislation, land‐use planning, protected area management, monitoring and reporting, and ecosystem management. Impacts are still emerging due to varying pace and commitment to implementation across different countries. In the future, RLE indices based on systematic assessments have high potential to inform global biodiversity reporting. Expanding the coverage of RLE assessments, building capacity and political will to undertake them, and establishing stronger policy instruments to manage red‐listed ecosystems will be key to maximizing conservation impacts over the coming decades.
Threats to ecosystems are closely linked to human development, whereas lack, insufficiency, and inefficiency of public policies are important drivers of environmental decline. Previous studies have discussed the contribution of IUCN's Red List of Ecosystems (RLE) in conservation issues; however, its applications in different policy fields and instruments for achieving biodiversity conservation have not been explored in detail. Here, we introduce a framework to operationalize the RLE in public policy, facilitating work of governments, practitioners, and decision makers. Our analysis identified 20 policy instruments that could reduce risks to ecosystems highlighted by different Red List criteria. We discuss how RLE could inform the policy process by analyzing different instruments that could be designed, implemented, and modified to achieve risk reduction. We also present practical examples from around the world showing how ecosystem conservation could be improved by operationalizing the RLE in policy instruments. The RLE criteria can inform the policy process by helping to shape objectives and identifying policy instruments that directly address the causes and severity of risks illuminated in Red List assessments. We conclude that RLE could be expanded into a broader holistic spectrum of policy instruments, which could be a key to achieving the ecosystem conservation.
Assessing risks to marine ecosystems is critical due to their biological and economic importance, and because many have recently undergone regime shifts due to overfishing and environmental change. Yet defining collapsed ecosystem states, selecting informative indicators and reconstructing long-term marine ecosystem changes remains challenging. The IUCN Red List of Ecosystems constitutes the global standard for quantifying risks to ecosystems and we conducted the first Red List assessment of an offshore marine ecosystem, focusing on the southern Benguela in South Africa. We used an analogous but collapsed ecosystem – the northern Benguela – to help define collapse in the southern Benguela and derived collapse thresholds with structured expert elicitation (i.e. repeatable estimation by expert judgment). To capture complex ecosystem dynamics and reconstruct historical ecosystem states, we used environmental indicators as well as survey-, catch- and model-based indicators. We listed the ecosystem in 1960 and 2015 as Endangered, with assessment outcomes robust to alternative model parametrizations. While many indicators improved between 1960 and 2015, seabird populations have suffered large declines since 1900 and remain at risk, pointing towards ongoing management priorities. Catch-based indicators often over-estimated risks compared to survey- and model-based indicators, warning against listing ecosystems as threatened solely based on indicators of pressure. We show that risk assessments provide a framework for interpreting data from indicators, ecosystem models and experts to inform the management of marine ecosystems. This work highlights the feasibility of conducting Red List of Ecosystems assessments for marine ecosystems.
Ongoing ecosystem degradation and transformation are key threats to biodiversity. Measuring ecosystem change towards collapse relies on monitoring indicators that quantify key ecological processes. Yet little guidance is available on selecting and implementing indicators for ecosystem risk assessment. Here, we reviewed indicator use in ecological studies of decline towards collapse in marine pelagic and temperate forest ecosystems. We evaluated the use of indicator selection methods, indicator types (geographic distribution, abiotic, biotic), methods of assessing multiple indicators, and temporal quality of time series. We compared these ecological studies to risk assessments in the International Union for the Conservation of Nature Red List of Ecosystems (RLE), where indicators are used to estimate ecosystem collapse risk. We found that ecological studies and RLE assessments rarely reported how indicators were selected, particularly in terrestrial ecosystems. Few ecological studies and RLE assessments quantified ecosystem change with all three indicator types, and indicators types used varied between marine and terrestrial ecosystem. Several studies used indices or multivariate analyses to assess multiple indicators simultaneously, but RLE assessments did not, as RLE guidelines advise against them. Most studies and RLE assessments used time series spanning at least 30 years, increasing the chance of reliably detecting change. Limited use of indicator selection protocols and infrequent use of all three indicator types may hamper the ability to accurately detect changes. To improve the value of risk assessments for informing policy and management, we recommend using: (i) explicit protocols, including conceptual models, to identify and select indicators; (ii) a range of indicators spanning distributional, abiotic and biotic features; (iii) indices and multivariate analyses with extreme care until guidelines are developed; (iv) time series with sufficient data to increase ability to accurately diagnose directional change; (v) data from multiple sources to support assessments; and (vi) explicitly reporting steps in the assessment process. This article is protected by copyright. All rights reserved
Analyses of long-term ecosystem dynamics offer insights into the conditions that have led to stability vs. rapid change in the past and the importance of disturbance in regulating community composition. In this study, we (1) used lithology, pollen, and charcoal data from Mallín Casanova (47°S) to reconstruct the wetland, vegetation, and fire history of west-central Patagonia; and (2) compared the records with independent paleoenvironmental and archeological information to assess the effects of past climate and human activity on ecosystem dynamics. Pollen data indicate that Nothofagus-Pilgerodendron forests were established by 9,000 cal yr BP. Although the biodiversity of the understory increased between 8,480 and 5,630 cal yr BP, forests remained relatively unchanged from 9,000 to 2,000 cal yr BP. The charcoal record registers high fire-episode frequency in the early Holocene followed by low biomass burning between 6,500 and 2,000 cal yr BP. Covarying trends in charcoal, bog development, and Neoglacial advances suggest that climate was the primary driver of these changes. After 2,000 cal yr BP, the proxy data indicate (a) increased fire-episode frequency; (b) centennial-scale shifts in bog and forest composition; (c) the emergence of vegetation-fire linkages not recorded in previous times; and (d) paludification in the last 500 years possibly associated with forest loss. Our results therefore suggest that Nothofagus-Pilgerodendron dominance was maintained through much of the Holocene despite long-term changes in climate and fire. Unparalleled fluctuations in local ecosystems during the last two millennia were governed by disturbance-vegetation-hydrology feedbacks likely triggered by greater climate variability and deforestation.
The International Union for Conservation of Nature (IUCN) Red List of Ecosystems is a powerful tool for classifying threatened ecosystems, informing ecosystem management, and assessing the risk of ecosystem collapse (that is, the endpoint of ecosystem degradation). These risk assessments require explicit definitions of ecosystem collapse, which are currently challenging to implement. To bridge the gap between theory and practice, we systematically review evidence for ecosystem collapses reported in two contrasting biomes – marine pelagic ecosystems and terrestrial forests. Most studies define states of ecosystem collapse quantitatively, but few studies adequately describe initial ecosystem states or ecological transitions leading to collapse. On the basis of our review, we offer four recommendations for defining ecosystem collapse in risk assessments: (1) qualitatively defining initial and collapsed states, (2) describing collapse and recovery transitions, (3) identifying and selecting indicators of collapse, and (4) setting quantitative collapse thresholds.
Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.
Decisions about natural resource management are frequently complex and vexed, often leading to public policy compromises. Discord between environmental and economic metrics creates problems in assessing trade-offs between different current or potential resource uses. Ecosystem accounts, which quantify ecosystems and their benefits for human well-being consistent with national economic accounts, provide exciting opportunities to contribute significantly to the policy process. We advanced the application of ecosystem accounts in a regional case study by explicitly and spatially linking impacts of human and natural activities on ecosystem assets and services to their associated industries. This demonstrated contributions of ecosystems beyond the traditional national accounts. Our results revealed that native forests would provide greater benefits from their ecosystem services of carbon sequestration, water yield, habitat provisioning and recreational amenity if harvesting for timber production ceased, thus allowing forests to continue growing to older ages.Ecosystem accounts quantify trade-offs between the economy and the environment. Here, the authors apply this approach to a regional case study of native forest use to show how it can be used to inform policy about complex land management decisions.
Aim
Stochastic threats such as disease outbreak, pollution events, fire, tsunami and drought can cause rapid species extinction and ecosystem collapse. The ability of a species or ecosystem to persist after a stochastic threat is strongly related to the extent and spatial pattern of its geographical distribution. Consequently, protocols for assessing risks to biodiversity typically include geographic range size criteria for assessing risks from stochastic threats. However, owing in part to the rarity of such events in nature, the metrics for assessing risk categories have never been tested. In this study, we investigate the performance of alternative range size metrics, including the two most widely used, extent of occurrence ( EOO ) and area of occupancy ( AOO ), as predictors of ecosystem collapse in landscapes subject to stochastic threats.
Methods
We developed a spatially explicit stochastic simulation model to investigate the impacts of four threat types on a dataset of 1350 simulated geographic distributions of varying pattern and size. We empirically estimated collapse probability in response to each threat type and evaluated the ability of a set of spatial predictors to predict risk.
Results
The probability of ecosystem collapse increased rapidly as range size declined. While AOO and EOO were the most important predictors of collapse risk for the three spatially explicit threats included in our model (circle, swipe and cluster), core area, patch density and mean patch size were better predictors for edge effect threats.
Main conclusions
Our study is the first to quantitatively assess the range size metrics employed in biodiversity risk assessment protocols. We show that the current methods for measuring range size are the best spatial metrics for estimating risks from stochastic threats. Our simulation framework delivers an objective assessment of the performance of hitherto untested but widely used measures of geographic range size for risk assessment.
Ecosystem services (ES) approaches to biodiversity conservation are currently high on the ecological research and policy agendas. However, despite awealth of studies into biodiversity’s role in maintaining ES (B–ES relationships) across landscapes, we still lack generalities in the nature and strengths of these linkages. Reasons for this are manifold, but can largely be attributed to (i) a lack of adherence to definitions and thus a confusion between final ES and the ecosystem functions (EFs) underpinning them, (ii) a focus on uninformative biodiversity indices and singular hypotheses and (iii) top-down analyses across large spatial scales and overlooking of context-dependency. The biodiversity–ecosystem functioning (B–EF) field provides an alternate context for examining biodiversity’s mechanistic role in shaping ES, focusing on species’ characteristics that may drive EFs via multiple mechanisms across contexts. Despite acknowledgements of a need for B–ES research to look towards underlying B–EF linkages, the connections between these areas of research remains weak. With this review, we pull together recent B–EF findings to identify key areas for future developments in B–ES research. We highlight a means by which B–ES research may begin to identify howand when multiple underlying B–EF relationships may scale to final ES delivery and trade-offs. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
The Norwegian Red list for Ecosystems and Habitat types 2011 is an assessment of ecosystems and habitat types that are considered to be decreasing or to exist in very small numbers. The assessments are based on a set of criteria’s which assesses the ecosystems and habitat types risk of disappearing from Norway. The assessment work in this Red list has been made by a group of experts within nine different themes, and is based on the system for typification and description of ecological variation called “Nature types in Norway (NiN)”. The overall result from this assessment classifies 40 types as threatened and 31 as near threatened. This is the first official Red list for Ecosystems and Habitat types in Norway.
In response to growing demand for ecosystem-level risk assessment in biodiversity conservation, and rapid proliferation of locally tailored protocols, the IUCN recently endorsed new Red List criteria as a global standard for ecosystem risk assessment. Four qualities were sought in the design of the IUCN criteria: generality; precision; realism; and simplicity. Drawing from extensive global consultation, we explore trade-offs among these qualities when dealing with key challenges, including ecosystem classification, measuring ecosystem dynamics, degradation and collapse, and setting decision thresholds to delimit ordinal categories of threat. Experience from countries with national lists of threatened ecosystems demonstrates well-balanced trade-offs in current and potential applications of Red Lists of Ecosystems in legislation, policy, environmental management and education. The IUCN Red List of Ecosystems should be judged by whether it achieves conservation ends and improves natural resource management, whether its limitations are outweighed by its benefits, and whether it performs better than alternative methods. Future development of the Red List of Ecosystems will benefit from the history of the Red List of Threatened Species which was trialled and adjusted iteratively over 50 years from rudimentary beginnings. We anticipate the Red List of Ecosystems will promote policy focus on conservation outcomes in situ across whole landscapes and seascapes.This article is protected by copyright. All rights reserved
Natural capital is essential for goods and services on which people depend. Yet pressures on the environment mean that natural capital assets are continuing to decline and degrade, putting such benefits at risk. Systematic monitoring of natural assets is a major challenge that could be both unaffordable and unmanageable without a way to focus efforts. Here we introduce a simple approach, based on the commonly used management tool of a risk register, to highlight natural assets whose condition places benefits at risk.
We undertake a preliminary assessment using a risk register for natural capital assets in the UK based solely on existing information. The status and trends of natural capital assets are assessed using asset–benefit relationships for ten kinds of benefits (food, fibre (timber), energy, aesthetics, freshwater (quality), recreation, clean air, wildlife, hazard protection and equable climate) across eight broad habitat types in the UK based on three dimensions of natural capital within each of the habitat types (quality, quantity and spatial configuration). We estimate the status and trends of benefits relative to societal targets using existing regulatory limits and policy commitments, and allocate scores of high, medium or low risk to asset–benefit relationships that are both subject to management and of concern.
The risk register approach reveals substantial gaps in knowledge about asset–benefit relationships which limit the scope and rigour of the assessment (especially for marine and urban habitats). Nevertheless, we find strong indications that certain assets (in freshwater, mountain, moors and heathland habitats) are at high risk in relation to their ability to sustain certain benefits (especially freshwater, wildlife and climate regulation).
Synthesis and applications. With directed data gathering, especially to monitor trends, improve metrics related to asset–benefit relationships, and improve understanding of nonlinearities and thresholds, the natural capital risk register could provide a useful tool. If updated regularly, it could direct monitoring efforts, focus research and protect and manage those natural assets where benefits are at highest risk.
Tidal flats provide ecosystem services to billions of people worldwide, yet their changing status is largely unknown. In the Yellow Sea region of East Asia, tidal flats are the principal coastal ecosystem fringing more than 4000 km of the coastlines of China, North Korea and South Korea. However, widespread loss of areal extent, increasing frequency of algal blooms, hypoxic dead zones and jellyfish blooms, and declines of commercial fisheries and migratory bird populations suggest that this ecosystem is degraded and declining. Here, we apply the International Union for Conservation of Nature Red List of Ecosystems criteria to the Yellow Sea tidal flat ecosystem and determine that its status is endangered. Comparison of standardized remotely sensed habitat data and historic topographic map data indicated that in the last 50 years, a decline of more than 50% but less than 80% of tidal flat extent has occurred (criterion A1). Although restricted to a narrow band along the coastline, Yellow Sea tidal flats are sufficiently broadly distributed to be classified as least concern under criterion B. However, widespread pollution, algal blooms and declines of invertebrate and vertebrate fauna across the region result in a classification of endangered (C1, D1). Owing to the lack of long-term monitoring data and the unknown impacts of severe biotic and abiotic change, the ecosystem was scored as data deficient for Criterion E and several subcriteria. Our assessment demonstrates an urgent need to arrest the decline of the Yellow Sea tidal flat ecosystem, which could be achieved by (i) improved coastal planning and management at regional and national levels, (ii) expansion of the coastal protected area network, and (iii) improved managed of existing protected areas to reduce illegal land reclamation and coastal exploitation.
The Kunming-Montreal Global Biodiversity Framework (GBF) of the UN Convention on Biological Diversity set the agenda for global aspirations and action to reverse biodiversity loss. The GBF includes an explicit goal for maintaining and restoring biodiversity, encompassing ecosystems, species and genetic diversity (goal A), targets for ecosystem protection and restoration and headline indicators to track progress and guide action1. One of the headline indicators is the Red List of Ecosystems2, the global standard for ecosystem risk assessment. The Red List of Ecosystems provides a systematic framework for collating, analysing and synthesizing data on ecosystems, including their distribution, integrity and risk of collapse3. Here, we examine how it can contribute to implementing the GBF, as well as monitoring progress. We find that the Red List of Ecosystems provides common theory and practical data, while fostering collaboration, cross-sector cooperation and knowledge sharing, with important roles in 16 of the 23 targets. In particular, ecosystem maps, descriptions and risk categories are key to spatial planning for halting loss, restoration and protection (targets 1, 2 and 3). The Red List of Ecosystems is therefore well-placed to aid Parties to the GBF as they assess, plan and act to achieve the targets and goals. We outline future work to further strengthen this potential and improve biodiversity outcomes, including expanding spatial coverage of Red List of Ecosystems assessments and partnerships between practitioners, policy-makers and scientists.
In March 2021, the UN Statistical Commission adopted the System of Environmental-Economic Accounting Ecosystem Accounting. The SEEA EA provides detailed guidance measuring the extent and condition of ecosystems, and how to quantify ecosystem services. This paper presents the SEEA EA in terms of the various types of ecosystem accounts, its origins, purposes and applications. A first handbook was published in 2013 followed by a period of testing. A revision process was launched in 2018 involving a wide range of experts in ecology, environmental economics and statistics. They proposed new or updated classifications for ecosystems and ecosystem condition, a reference list of ecosystem services and improved the internal consistency of the different ecosystem accounts. These proposals were reviewed in two global consultation rounds yielding strong support for a standard approach to ecosystem accounting. Finally, the conceptual framework and the physical accounts (extent, condition and services) are adopted as an international statistical standard. The guidance on monetary accounts (ecosystem services, ecosystem assets, sequence of accounts) is considered as internationally recognised principles and recommendations. Countries are encouraged to develop ecosystem accounts for use in policy and decision-making processes in both public and private sector and contribute to its further methodological development.
To make sound decisions about the future of fisheries, managers need to have a good understanding of the amount of fish that have been caught over long periods. Unfortunately, current stock assessment processes are often flawed, as they are frequently based on data time series that do not represent the full range of change. The process of selecting a shortened (or truncated) time series may lead to misconceptions regarding the fishery's status and impact on management decisions. This study investigates shifting baseline effects in official stock assessments from the Ransom Myers Legacy Stock Assessment Database that used truncated catch time series. The findings suggest that truncated time series often fail to account for important features, such as historical biomass maxima, past recoveries, low abundance levels and biomass fluctuations, whose omission can bias reference points and perceptions of stock status. This study emphasises the importance of considering long-term data wherever possible to improve historical scientific baselines and inform sustainable fisheries management.
Despite substantial conservation efforts, the loss of ecosystems continues globally, along with related declines in species and nature’s contributions to people. An effective ecosystem goal, supported by clear milestones, targets and indicators, is urgently needed for the post-2020 global biodiversity framework and beyond to support biodiversity conservation, the UN Sustainable Development Goals and efforts to abate climate change. Here, we describe the scientific foundations for an ecosystem goal and milestones, founded on a theory of change, and review available indicators to measure progress. An ecosystem goal should include three core components: area, integrity and risk of collapse. Targets—the actions that are necessary for the goals to be met—should address the pathways to ecosystem loss and recovery, including safeguarding remnants of threatened ecosystems, restoring their area and integrity to reduce risk of collapse and retaining intact areas. Multiple indicators are needed to capture the different dimensions of ecosystem area, integrity and risk of collapse across all ecosystem types, and should be selected for their fitness for purpose and relevance to goal components. Science-based goals, supported by well-formulated action targets and fit-for-purpose indicators, will provide the best foundation for reversing biodiversity loss and sustaining human well-being.
Myanmar is highly biodiverse, with more than 16,000 plant, 314 mammal, 1131 bird, 293 reptile, and 139 amphibian species. Supporting this biodiversity is a variety of natural ecosystems—mostly undescribed—including tropical and subtropical forests, savannas, seasonally inundated wetlands, extensive shoreline and tidal systems, and alpine ecosystems. Although Myanmar contains some of the largest intact natural ecosystems in Southeast Asia, remaining ecosystems are under threat from accelerating land use intensification and over-exploitation. In this period of rapid change, a systematic risk assessment is urgently needed to estimate the extent and magnitude of human impacts and identify ecosystems most at risk to help guide strategic conservation action. Here we provide the first comprehensive conservation assessment of Myanmar's natural terrestrial ecosystems using the IUCN Red List of Ecosystems categories and criteria. We identified 64 ecosystem types for the assessment, and used models of ecosystem distributions and syntheses of existing data to estimate declines in distribution, range size, and functioning of each ecosystem. We found that more than a third (36.9%) of Myanmar's area has been converted to anthropogenic ecosystems over the last 2–3 centuries, leaving nearly half of Myanmar's ecosystems threatened (29 of 64 ecosystems). A quarter of Myanmar's ecosystems were identified as Data Deficient, reflecting a paucity of studies and an urgency for future research. Our results show that, with nearly two-thirds of Myanmar still covered in natural ecosystems, there is a crucial opportunity to develop a comprehensive protected area network that sufficiently represents Myanmar's terrestrial ecosystem diversity.
Drivers of biodiversity loss have generated an increased risk of ecosystem collapse in the Anthropocene. Coral ecosystems are among the most diverse ecosystems, but at the same time also part of the most vulnerable and threatened ecosystems worldwide. This is the case of Wider and Colombian Caribbean coral ecosystems, which has a reduction of 50%, with extreme cases of 85% of their cover over the past decades. The methodology of the Red List of Ecosystems was implemented, for the first time, on the Colombian Caribbean to provide the assessment of collapse risk for coral ecosystems. To do this, the spatial and functional components of the ecosystem were analyzed using two of the Red List criteria (B and D) at three spatial scales (national, ecoregional, and biotic). For the former component, restricted distribution metrics were applied, and monitoring data of 20-year period (SIMAC) were used for the latter. Also, as a novel issue in coral functional risk assessment, mac-roalgae cover was considered, along with the percentage of live coral cover. The results indicated differences in the level of collapse risk depending on the spatial scale, whereby the national scale hid the most important risk dynamics of ecoregions and biotic scale overestimated the spatial risk. However, all ecosystem units at the three scales were assess from vulnerable to critically endangered, which means high-risk categories. Functional spatio-temporal analysis showed a general high-risk stability for the two variables chosen (fleshy algae cover and live corals) since 1998. These were complementary and necessary to propose the hypothesis of phase shift in the Colombian oceanic region, the area with the highest functional risk in the Colombian Caribbean. Finally, practical management recommendations were made based on the final assessment proposed by the risk map of coral ecosystems.
The Red List of Habitats of the Czech Republic assesses the risk of collapse for 157 types of natural and semi-natural habitats defined in the second edition of the Habitat Catalogue of the Czech Republic. The assessment followed the guidelines for the IUCN Red List of Ecosystems as used in the European Red List of Habitats project, using the criteria of habitat reduction in quantity, restricted geographic distribution, and reduction in abiotic and biotic quality. Quantitative data for the assessment were partly taken from a detailed field habitat mapping at the national scale, and where no quantitative information was available, the values were estimated by summarizing independent judgements of 17 experts. In addition to the criteria involved in the Red List assessment , the experts also assessed various types of threatening factors and their importance for each habitat. Of 157 assessed habitats, 2 were Collapsed (CO), 14 Critically Endangered (CR), 32 Endangered (EN), 33 Vulnerable (VU), 30 Near Threatened (NT) and 46 Least Concern (LC). The largest proportion of CR + EN habitats was in the habitat group of springs and mires and in the group of wetlands. The threatening factors evaluated as the most important were successional changes after cessation of traditional management, eutrophication due to atmospheric nutrient deposition and pollution from agriculture, and increased drought in water-dependent habitats due to climate change or changes in local hydrological regime. The study shows that the IUCN criteria for Red List assessment of habitats, although developed for the global scale, are also applicable within small countries or regions.
Recent international efforts have focused on the development of metrics to supplement or adjust Gross Domestic Product (GDP) to better account for the broader environmental and social impacts of economic development. In this regard, the United Nations System of Environmental-Economic Accounting, through its Experimental Ecosystem Accounting (EEA) work, is developing a standardized approach to accounting for the value of ecosystem services generated by ecosystems and documenting the relationships between ecosystem services and economic activity. Limited examples exist of the application of the EEA approach to coastal and marine habitats. The purpose of the current paper is therefore to develop a pilot process for applying the EEA within a coastal area, using South Shore Long Island Bays as a case study. Indicators of ecosystem condition and ecosystem services are proposed, data are compiled for the study site, and population of EEA tables as proposed by the United Nations is undertaken. Results indicate significant data gaps for marine and coastal areas that may limit the immediate ability to compile these ecosystem accounts. However, based on identified data gaps and implementation challenges, the process undertaken at the pilot site also provides guidance for potential future research activities.
In this paper, we examine how progress on ecosystem service indicators could contribute to ecosystem accounting within the scope of environmental-economic accounting in Finland. We propose an integration framework and examine the integration of ecosystem service indicators into environmental-economic accounting with two case studies relevant for Finland: (1) water-related ecosystem services and (2) the ecosystem services of fish provisioning in marine ecosystems. In light of these case studies, we evaluate the relevance of existing Finnish ecosystem service indicators, the data availability for ecosystem accounting in Finland, and the applicability of the System of Environmental-Economic Accounting - Experimental Ecosystem Accounting (SEEA-EEA) framework to integrate Finnish ecosystem service indicators and other relevant data into environmental-economic accounts. The results indicate that the present ecosystem service indicators can assist in creating a basis for ecosystem accounting, but the indicators require further elaboration to be more compatible with the existing environmental-economic accounting system.
*The article is open access. The full version can be download from the link for free: https://www.sciencedirect.com/science/article/pii/S0304380017302491
Many decision-makers are looking to science to clarify how nature supports human well-being. Scientists' responses have typically focused on empirical models of the provision of ecosystem services (ES) and resulting decision-support tools. Although such tools have captured some of the complexities of ES, they can be difficult to adapt to new situations. Globally useful tools that predict the provision of multiple ES under different decision scenarios have proven challenging to develop. Questions from decision-makers and limitations of existing decision-support tools indicate three crucial research frontiers for incorporating cutting-edge ES science into decision-support tools: (1) understanding the complex dynamics of ES in space and time, (2) linking ES provision to human well-being, and (3) determining the potential for technology to substitute for or enhance ES. We explore these frontiers in-depth, explaining why each is important and how existing knowledge at their cutting edges can be incorporated to improve ES decision-making tools.
For over thirty years the Genuine Progress Indicator (GPI) has been used to evaluate economic performance, quantify benefits and costs of growth, and predict effects of policy changes on economic wellbeing. The popularity and use of the metric is increasing partially in response to new global demands for metrics that go beyond Gross Domestic Product (GDP). However, because the basic GPI accounting protocols have yet to be consistently updated to respond to theoretical critiques, new valuation methods, and new data sources a proliferation of studies at the global, national and sub-national level contain widely divergent methodologies. Because of this, GPI practitioners have called for a new, consistent framework to guide future GPI studies – GPI 2.0. This paper is an attempt to operationalize some of the concepts that have emerged from GPI 2.0 deliberations online and at recent workshops in the form of GPI 2.0 pilot accounts for the US, State of Maryland, and City of Baltimore. The goal is to demonstrate the feasibility of multi-scale GPI accounts that provide a more accurate measure of current economic welfare than GDP and that incorporate new methods and sources of information to replace many of the outdated aspects of the prevailing GPI approach.
This manual explains what GDP and GNI and their components are and what they mean. It shows how they are used and what they are used for. And it does this in an easily understood way. Opening with a chapter showing how national accounts concepts relate to macroeconomics, the books goes on to systematically deal with volume and prices, international comparability, production, final uses, household accounts, business accounts, government accounts, and financial accounts. It also has chapter on how national accounts data are gathered and the history of the national accounts system. Three special chapters examine national accounts in China, India, and the United States. Previously published only in French, this manual has been revised and expanded to have a truly global perspective.
The relationship between biodiversity and the rapidly expanding research and policy field of ecosystem services is confused and is damaging efforts to create coherent policy. Using the widely accepted Convention on Biological Diversity definition of biodiversity and work for the U.K. National Ecosystem Assessment we show that biodiversity has key roles at all levels of the ecosystem service hierarchy: as a regulator of underpinning ecosystem processes, as a final ecosystem service and as a good that is subject to valuation, whether economic or otherwise. Ecosystem science and practice has not yet absorbed the lessons of this complex relationship, which suggests an urgent need to develop the interdisciplinary science of ecosystem management bringing together ecologists, conservation biologists, resource economists and others.