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... For example, the Group on Earth Observations Biodiversity Observation Network's approach for global coordination has been to establish multiple biodiversity observation networks that operate at regional, national, and global scales but follow a standardized framework for monitoring biodiversity by using essential biodiversity variables that ensure information cross-scalability. 95,96 Likewise, multiscale scenario modeling of the integrated mangrove datasets, if developed with input from stakeholders who work across disciplines and spatial scales, would provide locally relevant recommendations for conservation action based on future predictions of ecosystem change. 95,97,98 This multiscale approach to scenario modeling has been embraced by the Intergovernmental Platform on Biodiversity and Ecosystem Services to help guide managers locally and globally. ...
... 95,96 Likewise, multiscale scenario modeling of the integrated mangrove datasets, if developed with input from stakeholders who work across disciplines and spatial scales, would provide locally relevant recommendations for conservation action based on future predictions of ecosystem change. 95,97,98 This multiscale approach to scenario modeling has been embraced by the Intergovernmental Platform on Biodiversity and Ecosystem Services to help guide managers locally and globally. 97,98 A Platform for Visualizing and Disseminating Global Datasets If the growing wealth of data being developed around mangrove forests is to have an influence beyond the academic literature, 99 it will be critical to develop a platform to provide decision makers with clear and easy-to-access information. ...
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Mangrove forests are found on sheltered coastlines in tropical, subtropical, and some warm temperate regions. These forests support unique biodiversity and provide a range of benefits to coastal communities, but as a result of large-scale conversion for aquaculture, agriculture, and urbanization, mangroves are considered increasingly threatened ecosystems. Scientific advances have led to accurate and comprehensive global datasets on mangrove extent, structure, and condition, and these can support evaluation of ecosystem services and stimulate greater conservation and rehabilitation efforts. To increase the utility and uptake of these products, in this Perspective we provide an overview of these recent and forthcoming global datasets and explore the challenges of translating these new analyses into policy action and on-the-ground conservation. We describe a new platform for visualizing and disseminating these datasets to the global science community, non-governmental organizations, government officials, and rehabilitation practitioners and highlight future directions and collaborations to increase the uptake and impact of large-scale mangrove research.
... Such support of international policy by the assessment, monitoring and prediction of the response of biodiversity and ecosystem functioning to environmental and socioeconomic change is the focus of the FutureEarth Global Research Project bioDISCOVERY. In their review, Krug et al. [13] describe the tasks of bioDISCOVERY as working towards a previously unprecedented capacity to observe the trends and status of biodiversity and ecosystems to predict at future interactions between people and nature. ...
... [17] address and identify the challenges of such global change and biodiversity research, discussed by Krug et al. [13], focussing on the different axes of the disciplines included in the URPP on 'Global Change and Biodiversity'. ...
... Such support of international policy by the assessment, monitoring and prediction of the response of biodiversity and ecosystem functioning to environmental and socioeconomic change is the focus of the FutureEarth Global Research Project bioDISCOVERY. In their review, Krug et al. [13] describe the tasks of bioDISCOVERY as working towards a previously unprecedented capacity to observe the trends and status of biodiversity and ecosystems to predict at future interactions between people and nature. ...
... [17] address and identify the challenges of such global change and biodiversity research, discussed by Krug et al. [13], focussing on the different axes of the disciplines included in the URPP on 'Global Change and Biodiversity'. ...
... Given the contemporary rapid changes in Alpine areas (Hock et al., 2019) and warming (Niedrist and Füreder, 2021) or pollution (e.g., secondary salinization; of Alpine rivers with the background of drastic declines of freshwater populations worldwide (WWF, 2018), monitoring of regional biodiversity is essential to understand future situations (Krug et al., 2017), but also for adapting and prioritizing conservation measures. This work provides not only a basis for the planned biodiversity monitoring in that northern Italian province (see https://biodiversity.eurac.edu), ...
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High biodiversity is a prerequisite for the integrity, stability, and functioning of global aquatic ecosystems, but it is currently subject to anthropogenic threats. Small freshwater bodies with high habitat diversity are essential to sustain regional biodiversity, but species inventory and biodiversity are largely overlooked, especially in mountainous regions. In the Italian Alps, obligate assessments of freshwater biota (e.g., for the European water framework directive, WFD) are usually done in larger rivers or lakes only, which is why many taxa from small freshwater habitats might have been overlooked so far. Here we summarize and discuss the efforts to record aquatic invertebrates within the framework of so-called "Biodiversity Days", organized since 2001 at 13 different sites located across the North Italian province of South Tyrol. These events with voluntary participation of scientists and naturalists from universities and environmental agencies led to the detection of 334 benthic invertebrate taxa in streams and lakes (mostly species or genus level), whereby higher taxa richness was found in streams. The overall hierarchy of species numbers within invertebrate orders or families corresponded to that of other Alpine regions (groups richest in taxa were Chironomidae and Trichoptera) and these Biodiversity Days contributed in biodiversity research of that region in detecting 167 additional taxa. Besides analyzing yearly gains in the regional taxa inventory, we predict that future surveys will lead to new discoveries of aquatic taxa for that province (i.e., current modeling estimates a regional inventory of more than 600 taxa). However, specific surveys in hitherto unconsidered habitats, such as morphologically modified or urban waters, might reveal even more taxa than currently estimated. Besides characterizing the invertebrate fauna of this region and providing a first reference list for future monitoring projects in the same region, this work demonstrates that such Biodiversity Days can contribute to biodiversity research.
... Previous ES frameworks have connected ES approaches with environmental policy decision support [83,85,86]. Some of these studies have applied ES supply-demand budget analysis to the preliminary stage of environmental management [42]. ...
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Transboundary environmental problems caused by urban expansion and economic growth cannot be solved by individual cities. Successful intercity environmental cooperation relies on the clear identification and definition of the rights and obligations of each city. An Ecosystem services (ES) approach not only budgets the ES supply and demand of a city, but also defines the spatial relationships between Services Provisioning Areas (SPA) and Services Benefiting Areas (SBA). However, to date, quantitative studies integrating ES budgets and spatial relations have been scarce. This study integrates ecosystem services supply–demand budgeting with flow direction analysis to identify intercity environmental cooperation in the highly urbanized Yangtze River Delta (YRD) region of China for water-related ecosystem services (flood protection, erosion regulation and water purification). The results demonstrated that there were significant spatial mismatches in the supply and demand of three water-related ES among 16 core cities in the YRD region: five to six cities in the southern part of the region had significant service surpluses, while ten to 11 cities in the north–central part had significant service deficits. We then went on to offer definitions for Ecosystem Services Surplus City, Ecosystem Services Deficit City and Ecosystem Services Balance City, as well as Service Provisioning City, Service Benefiting City and Service Connecting City in which to categorize cities in the YRD Region. Furthermore, we identified two intercity cooperation types and two non-cooperation types. This framework can be used to promote ecological integration in highly urbanized regions to advance sustainable development.
... The diagnostics and standards for evaluation of them as a suite of decision criteria could also provide efficiencies and improvements in a relatively simple, empirically based manner that would necessitate an identified range of actions. We certainly are not advocating for curtailment of fisheries-related research in any way, but we do think such an engineering approach could focus from a plethora of process-oriented studies into ones that lead to more refined solutions for LMR management (Krug et al., 2017;Link & Marshak, 2019;Lockerbie et al, 2016Lockerbie et al, , 2018. Often the factors and combinations thereof facing LMR populations can seem so overwhelming that it leads to inaction. ...
Article
The increasing need to account for the many factors that influence fish population dynamics, particularly those external to the population, has led to repeated calls for an ecosystem approach to fisheries management (EAFM). Yet systematically and clearly addressing these factors, and hence implementing EAFM, has suffered from a lack of clear operational guidance. Here, we propose 13 main factors (shift in location, migration route or timing, overfishing (three types), decrease in physiology, increase in predation, increase in competition, decrease in prey availability, increase in disease or parasites and a decline in habitat quality or habitat quantity) that can negatively influence fish populations via mechanisms readily observable in ~20 population features. Using these features as part of a diagnostic framework, we develop flow charts that link probable mechanism(s) underlying population change to the most judicious management actions. We then apply the framework for example case studies that have well‐known and documented population dynamics. To our knowledge, this is the first attempt to provide a clearly defined matrix of all the probable responses to the most common factors influencing fish populations, and to examine possible diagnostics simultaneously, comparatively and relatively in an attempt to elucidate the most probable mechanisms responsible. The framework we propose aims to operationalize EAFM, thereby not only better diagnosing factors influencing fish populations, but also suggesting the most appropriate management interventions, and ultimately leading to improved fisheries. We assert the framework proposed should result in both better use of limited analytical and observational resources and more tailored and effective management actions.
... It is now well-known that the pressures exerted by human activities on ecosystems can compromise the capacity of ecological cycles to regenerate and supply ecosystem services (ES) in ways that negatively affect human well-being (Costanza et al. 1997, MEA 2005, Guerry et al. 2015, Krug et al. 2017). Ecosystem services have been described as "the ecological characteristics, functions, or processes that directly or indirectly contribute to human well-being: that is, the benefits that people derive from functioning ecosystems" (Costanza et al. 2017). ...
Article
The assessment of ecosystem services (ES) is covered in a fragmented manner by environmental decision support tools that provide information about the potential environmental impacts of supply chains and their products, such as the well-known life cycle assessment (LCA) methodology. Within the flagship project of the Life Cycle Initiative (hosted by UN Environment), aiming at global guidance for life cycle impact assessment (LCIA) indicators, a dedicated subtask force was constituted to consolidate the evaluation of ES in LCA. As one of the outcomes of this subtask force, this paper describes the progress towards consensus building in the LCA domain concerning the assessment of anthropogenic impacts on ecosystems and their associated services for human well-being. To this end, the traditional LCIA structure, which represents the cause-effect chain from stressor to impacts and damages, is re-casted and expanded using the lens of the ES ‘cascade model’. This links changes in ecosystem structure and function to changes in human well-being, while LCIA links the effect of changes on ecosystems due to human impacts (e.g. land use change, eutrophication, freshwater depletion) to the increase or decrease in the quality and/or quantity of supplied ES. The proposed cascade modelling framework complements traditional LCIA with information about the externalities associated with the supply and demand of ES, for which the overall cost-benefit result might be either negative (i.e. detrimental impact on the ES provision) or positive (i.e. increase of ES provision). In so doing, the framework introduces into traditional LCIA the notion of “benefit” (in the form of ES supply flows and ecosystems’ capacity to generate services) which balances the quantified environmental intervention flows and related impacts (in the form of ES demands) that are typically considered in LCA. Recommendations are eventually provided to further address current gaps in the analysis of ES within the LCA methodology.
... It is therefore of the utmost importance that we have effective tools for detecting changes in biodiversity and ecosystem function in response to anthropogenic disturbance (Feest et al., 2010;Hill et al., 2016;Kremen, 2005;Pimm and Raven, 2000). Indicator groups have been widely used for this purpose (Cleary, 2004;Krug et al., 2017;Schulze et al., 2004), however choosing suitable indicator groups can be challenging (Broszeit et al., 2017;Fleishman and Murphy, 2009;Gao et al., 2015). Ideally they should be efficient to survey, show a predictable, sensitive response to environmental change, correlate well with overall biodiversity responses and play an important role in the ecosystem (Brown, 1997;Hilty and Merenlender, 2000). ...
Article
Biodiversity and ecosystem functions are threatened by human disturbance, and tropical forests are one the most vulnerable habitats. Monitoring the impacts of disturbance and the success of conservation projects is crucial, and to do this effectively it is important to identify suitable measures that are sensitive to ecosystem disturbance. Orchid bees (Euglossini) are a specialist group with mutualistic relationships with many plant species and can fly long distances, making them important pollinators of widely dispersed plant species. A loss of specialist pollinators such as these could have severe consequences for the plants that rely on their services. We therefore aimed to answer the following question: are orchid bees useful indicators of the impacts of human disturbance? If so, what measures of orchid bee diversity are most sensitive? And do orchid bees provide any indication of changes in pollination services along a disturbance gradient? Orchid bees were collected from 18 sites across a gradient of disturbance in a tropical forest region in southeast Peru. Alpha diversity across the gradient was compared using Hills numbers. Beta diversity was assessed using community composition, species contributions to beta diversity, beta diversity partitioning and novel measures of redundancy and representativeness. The potential pollination services available at each site were measured using artificial flowers and counts of pollinator visits. Alpha diversity of orchid bees showed low sensitivity to disturbance. Beta diversity measures were more informative, with disturbed sites found to be highly redundant in the ecosystem compared to the less disturbed sites. However, the most sensitive measure across the gradient was abundance – there was a significant decrease in the number of bees caught as disturbance increased, with likely consequences for pollination services. These results suggest that orchid bees may be useful indicators of the impacts of human disturbance, but alpha diversity is a poor metric for this purpose. In order to understand how human disturbance is affecting biodiversity, multiple diversity indices should be considered, and in the case of orchid bees, redundancy and abundance could be useful for detecting sensitive responses to forest disturbance.
... forest ecosystem change through effective global coordination [3] good observations, indicators and scenarios of biodiversity and ecosystem services change [4]. ...
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Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.
... forest ecosystem change through effective global coordination [3] good observations, indicators and scenarios of biodiversity and ecosystem services change [4]. ...
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Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.
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Forest ecosystems fulfill the entire ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. In the present study we focused to determine forest health pattern of Simlipal National Park (Odisha, India) based on Remote Sensing and GIS techniques. Multitemporal Landsat 8 operational Land Imager (OLI) data are derived from USGS Earth Explorer Community. Normalized difference vegetation index (NDVI), SARVI (Soil and Atmospherically Resistant Vegetation Index), Modified Chlorophyll Absorption Ratio (MCARI), and Moisture Stress Index (MSI) have been used to create different vegetation indices to estimate forest health. Finally, Weighted overlay analysis is performed on GIS platform to identify the forest health pattern in the national park. NDVI index showed the maximum accuracy for identifying vegetation classes. Results showed in the eastern and central part of the study area having excellent vegetation cover. Good to moderate vegetation cover areas are observed in the south and small pockets in north of the study area. The excellent vegetation coverage area also increases day by day. To exclude the agricultural lands and cloud cover from forest area images from the month of January are selected.
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Recent studies show that light detection and ranging (LiDAR) derived habitat variables significantly increase the performance and accuracy of species distribution models (SDMs). In particular, the structure of complex habitats such as forest can be accurately parametrized by an area-wide, LiDAR-based vegetation profile. However, evidence of specific applications of such models in real-world conservation management still remains sparse. Here, we developed a resource selection SDM for hazel grouse (Bonasa bonasia L.) in a Swiss nature park with the aim to map habitat suitability and to inform the park management about habitat improvement measures. We used remote sensing, particularly LiDAR to derive ecologically relevant forest vegetation characteristics at the local scale and used them as predictors in an ensemble SDM approach. The predicted habitat suitability was mainly affected by local, fine grained vegetation structure. Average vegetation height, shrub density and canopy height variation contributed most to the habitat quality for hazel grouse. This clearly shows how LiDAR provides the means to develop ecologically interpretable predictor variables of forest habitat structure and that these predictors can be used to reliably map local-scale habitat quality, indicated by high model performance scores (median AUC of 0.918). This improves spatial conservation planning, and at the same time, provides meaningful information to derive habitat improvement measures that can be implemented in the field by foresters. Hazel grouse occurrence in the park is restricted to a few highly suitable, disjunct habitat patches. Therefore, conservation management should increase the connectivity of suitable habitat with the aim to stimulate an increase and better exchange of individuals in the regional hazel grouse population. Habitat improvements can be achieved by forestry measures that regularly integrate early successional forest stages into production forests. They should contain stands with a shrub density of around 30% as well as heterogeneous stands in terms of vegetation height. © 2017 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London
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A recent paper by Mori [1] states the need for a unification of studies of ‘engineering’ and ‘ecological’ frameworks of resilience. Engineering resilience focuses on the capacity of a system to recover to equilibrium following some kind of perturbation, while ecological resilience (ER) explicitly recognizes multiple stable states and the capacity for systems to resist ‘regime shifts’ between alternative states. We find Mori's argument somewhat surprising given the number of recent biodiversity–ecosystem functioning (B-EF) studies that incorporate aspects of both resistance and recovery (e.g., see references in [2,3]).
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Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today’s terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.
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1.Global environmental change can influence ecosystem processes directly or through changes in the trait composition of natural communities. Traits are individual-level features of organisms, and theory predicts that diversity in traits should relate to ecosystem processes. Validated indices that account for both intra- and interspecific trait variation in multidimensional trait space are lacking. In this article we highlight how an individual-level perspective requires new concepts for trait diversity (TD) and we validate a set of measures suitable to study trait richness, evenness and divergence at the individual scale.2.First, we tested a selection of multivariate indices for trait richness, evenness and divergence from the literature (FRic, FEve, FDis and the Rao coefficient) using simulated and real individual-level data. We compared the observed changes in the tested indices with those predicted from their expected/required behaviour (that is, increase or decrease under specific manipulation of community trait structure) and found unsatisfactory results only for FRic and FEve, whereas FDis and the Rao coefficient showed the expected changes.3.Therefore, we propose two novel concepts and related indices for individual-level trait richness (TOP = Trait Onion Peeling) and evenness (TED = Trait Even Distribution). TOP represents the sum of all successive convex hull areas touching all individuals (points) within a multidimensional trait distribution. TED is a measure of how evenly distributed are individuals within the multidimensional trait space. It is calculated comparing the probability distributions of pairwise distances between individuals and between points of a perfectly even reference distribution. We tested TOP and TED on the same simulated and real data as above, and results indicated appropriate behaviour for TOP (trait richness) and TED (trait evenness).4.By validating TD indices in an individual-level context, the present study contributes to the expansion of functional ecology towards individual-level dynamics. Future comprehensive investigations of individual trait differences in natural communities may improve our understanding of the pathways by which environmental changes affect ecosystem functioning through biodiversity change.This article is protected by copyright. All rights reserved.
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model ensemble projections of climate change effects on global marine biodiversity. – ICES Species distribution models (SDMs) are important tools to explore the effects of future global changes in biodiversity. Previous studies show that variability is introduced into projected distributions through alternative datasets and modelling procedures. However, a multi-model approach to assess biogeographic shifts at the global scale is still rarely applied, particularly in the marine environment. Here, we apply three commonly used SDMs (AquaMaps, Maxent, and the Dynamic Bioclimate Envelope Model) to assess the global patterns of change in species richness, invasion, and extinction intensity in the world oceans. We make species-specific projections of distribution shift using each SDM, subsequently aggregating them to calculate indices of change across a set of 802 species of exploited marine fish and invertebrates. Results indicate an average poleward latitudinal shift across species and SDMs at a rate of 15.5 and 25.6 km decade 21 for a low and high emissions climate change scenario, respectively. Predicted distribution shifts resulted in hotspots of local invasion intensity in high latitude regions, while local extinctions were concentrated near the equator. Specifically, between 108N and 108S, we predicted that, on average, 6.5 species would become locally extinct per 0.58 latitude under the climate change emissions scenario Representative Concentration Pathway 8.5. Average invasions were predicted to be 2.0 species per 0.58 latitude in the Arctic Ocean and 1.5 species per 0.58 latitude in the Southern Ocean. These averaged global hotspots of invasion and local extinction intensity are robust to the different SDM used and coincide with high levels of agreement.
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An updated trophic model of the southern Benguela ecosystem in the period 2004-2008 was constructed, complementing trophic models for earlier periods. The model represents the trophic structure of the system after a southward shift of major resources. There was an increase in biomass of small pelagic fish and cephalopods between the 1980s and 2004-2008 periods, accompanied by declines in several higher trophic level groups. A 3 step process was followed: (1) a series of snapshots of the ecosystem was used to explore changes in the food web structure over time, (2) trophic indicators were extracted from these models to detect changes, and (3) model-derived ecological indicators which were deemed most meaningful for management within the ecosystem were selected for use in decision trees, providing a logical framework in which to access synthesised information on trends in ecosystem status as a result of fishing. Three decision trees were developed which examined the ecosystem at the community level (pelagic-caught fish and demersal-caught fish community decision trees) and at the system level (ecosystem decision tree). The decision trees classified one period of the southern Benguela ecosystem as 'Deteriorating' (the period after the onset of industrial fishing: 1960s vs. 1900s), and 3 periods as 'Not improving' (1980s vs. 1960s, 1990s vs. 1980s, and 2004-2008 vs. 1980s). The current management strategy has ensured that the offshore southern Benguela ecosystem has not deteriorated further since the 1960s in terms of ecosystem functioning and at the scale of the fish community. Although the decision trees are conservative with regard to trends, the logic they employ is sound and robust, providing fisheries managers with a coherent framework to access synthesised information and the reasoning behind conclusions reached.
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Ecosystem-based management of marine fisheries requires the use of simulation modelling to investigate the system-level impact of candidate fisheries management strategies. However, testing of fundamental assumptions such as system structure or process formulations is rarely done. In this study, we compare the output of three different ecosystem models (Atlantis, Ecopath with Ecosim, and OSMOSE) applied to the same ecosystem (the southern Benguela), to explore which ecosystem effects of fishing are most sensitive to model uncertainty. We subjected the models to two contrasting fishing pressure scenarios, applying high fishing pressure to either small pelagic fish or to adult hake. We compared the resulting model behaviour at a system level, and also at the level of model groups. We analysed the outputs in terms of various commonly used ecosystem indicators, and found some similarities in the overall behaviour of the models, despite major differences in model formulation and assumptions. Direction of change in system-level indicators was consistent for all models under the hake pressure scenario, although discrepancies emerged under the small-pelagic-fish scenario. Studying biomass response of individual model groups was key to understanding more integrated system-level metrics. All three models are based on existing knowledge of the system, and the convergence of model results increases confidence in the robustness of the model outputs. Points of divergence in the model results suggest important areas of future study. The use of feeding guilds to provide indicators for fish species at an aggregated level was explored, and proved to be an interesting alternative to aggregation by trophic level.
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Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development. © 2015 The Authors Ecology Letters published by John Wiley & Sons Ltd and CNRS.
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After a long incubation period, the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is now underway. Underpinning all its activities is the IPBES Conceptual Framework (CF), a simplified model of the interactions between nature and people. Drawing on the legacy of previous large-scale environmental assessments, the CF goes further in explicitly embracing different disciplines and knowledge systems (including indigenous and local knowledge) in the co-construction of assessments of the state of the world's biodiversity and the benefits it provides to humans. The CF can be thought of as a kind of " Rosetta Stone " that highlights commonalities between diverse value sets and seeks to facilitate crossdisciplinary and crosscultural understanding. We argue that the CF will contribute to the increasing trend towards interdisciplinarity in understanding and managing the environment. Rather than displacing disciplinary science, however, we believe that the CF will provide new contexts of discovery and policy applications for it.
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The first public product of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is its Conceptual Framework. This conceptual and analytical tool, presented here in detail, will underpin all IPBES functions and provide structure and comparability to the syntheses that IPBES will produce at different spatial scales, on different themes, and in different regions. Salient innovative aspects of the IPBES Conceptual Framework are its transparent and participatory construction process and its explicit consideration of diverse scientific disciplines, stakeholders, and knowledge systems, including indigenous and local knowledge. Because the focus on co-construction of integrative knowledge is shared by an increasing number of initiatives worldwide, this framework should be useful beyond IPBES, for the wider research and knowledge-policy communities working on the links between nature and people, such as natural, social and engineering scientists, policy-makers at different levels, and decisionmakers in different sectors of society.
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1.Laboratory microcosm experiments using protists as model organisms have a long tradition and are widely used to investigate general concepts in population biology, community ecology and evolutionary biology. Many variables of interest are measured in order to study processes and patterns at different spatiotemporal scales and across all levels of biological organization. This includes measurements of body size, mobility, or abundance, in order to understand population dynamics, dispersal behaviour, and ecosystem processes. Also, a variety of manipulations are employed, such as temperature changes or varying connectivity in spatial microcosm networks. 2.Past studies, however, have used varying methods for maintenance, measurement, and manipulation, which hinders across-study comparisons and meta-analyses, and the added value they bring. Furthermore, application of techniques such as flow-cytometry, image and video analyses, and in-situ environmental probes provide novel and improved opportunities to quantify variables of interest at unprecedented precision and temporal resolution. 3.Here, we take the first step towards a standardization of well-established and novel methods and techniques within the field of protist microcosm experiments. We provide a comprehensive overview of maintenance, measurement, and manipulation methods. An extensive supplement contains detailed protocols of all methods, and these protocols also exist in a community updateable online repository. 4.We envision that such a synthesis and standardization of methods will overcome shortcomings and challenges faced by past studies, and also promote activities such as meta-analyses and distributed experiments conducted simultaneously across many different laboratories at a global scale.
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In 2010, the parties of the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011-2020 with the mission of halting biodiversity loss and enhance the benefits it provides to people. The 20 Aichi Biodiversity Targets (Aichi Targets), which are included in the Strategic Plan, are organized under five Strategic Goals, and provide coherent guidance on how to achieve it. Halfway through the Strategic Plan, it is time to prioritize actions in order to achieve the best possible outcomes for the Aichi Targets in 2020. Actions to achieve one target may influence other targets (downstream interactions); in turn a target may be influenced by actions taken to attain other targets (upstream interactions). We explore the interactions among targets and the time-lags between implemented measures and desired outcomes to develop a framework that can reduce the overall burden associated with the implementation of the Strategic Plan. We identified the targets addressing the underlying drivers of biodiversity loss and the targets aimed at enhancing the implementation of the Strategic Plan as having the highest level of downstream interactions. Targets aimed at improving the status of biodiversity and safeguarding ecosystems followed by targets aimed at reducing the direct pressures on biodiversity and enhancing the benefits to all from biodiversity and ecosystem services, were identified as having the highest levels of upstream interactions. Perhaps one of the most challenging aspects of the Strategic Plan is the need to balance actions for its long-term sustainability with the need for urgent actions to halt biodiversity loss.
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Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere–atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.
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There is a growing demand for spatially explicit assessment of multiple ecosystem services (ES) and remote sensing (RS) can provide valuable data to meet this challenge. In this study, located in the Central French Alps, we used high spatial and spectral resolution RS images to assess multiple ES based on underpinning ecosystem properties (EP) of subalpine grasslands. We estimated five EP (green biomass, litter mass, crude protein content, species diversity and soil carbon content) from RS data using empirical RS methods and maps of ES were calculated as simple linear combinations of EP. Additionally, the RS-based results were compared with results of a plant trait-based statistical modelling approach that predicted EP and ES from land use, abiotic and plant trait data (modelling approach). The comparison between the RS and the modelling approaches showed that RS-based results provided better insight into the fine-grained spatial distribution of EP and thereby ES, whereas the modelling approach reflected the land use signal that underpinned trait-based models of EP. The spatial agreement between the two approaches at a 20-m resolution varied between 16 and 22% for individual EP, but for the total ecosystem service supply it was only 7%. Furthermore, the modelling approach identified the alpine grazed meadows land use class as areas with high values of multiple ES (hot spots) and mown-grazed permanent meadows as areas with low values and only few ES (cold spots). Whereas the RS-based hot spots were a small subset of those predicted by the modelling approach, cold spots were rather scattered, small patches with limited overlap with the modelling results. Despite limitations associated with timing of assessment campaigns and field data requirements, RS offers valuable data for spatially continuous mapping of EP and can thus supply RS-based proxies of ES. Although the RS approach was applied to a limited area and for one type of ecosystem, we believe that the broader availability of high fidelity airborne and satellite RS data will promote RS-based assessment of ES to larger areas and other ecosystems.
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Bundy, A., Shannon, L. J., Rochet, M-J., Neira, S., Shin, Y-J., Hill, L., and Aydin, K. 2010. The good(ish), the bad, and the ugly: a tripartite classification of ecosystem trends. – ICES Journal of Marine Science, 67: 745–768. Marine ecosystems have been exploited for a long time, growing increasingly vulnerable to collapse and irreversible change. How do we know when an ecosystem may be in danger? A measure of the status of individual stocks is only a partial gauge of its status, and does not include changes at the broader ecosystem level, to non-commercial species or to its structure or functioning. Six ecosystem indicators measuring trends over time were collated for 19 ecosystems, corresponding to four ecological attributes: resource potential, ecosystem structure and functioning, conservation of functional biodiversity, and ecosystem stability and resistance to perturbations. We explored the use of a decision-tree approach, a definition of initial ecosystem state (impacted or non-impacted), and the trends in the ecosystem indicators to classify the ecosystems into improving, stationary, and deteriorating. Ecosystem experts classified all ecosystems as impacted at the time of their initial state. Of these, 15 were diagnosed as “ugly”, because they had deteriorated from an already impacted state. Several also exhibited specific combinations of trends indicating “fishing down the foodweb”, reduction in size structure, reduction in diversity and stability, and changed productivity. The classification provides an initial evaluation for scientists, resource managers, stakeholders, and the general public of the concerning status of ecosystems globally.
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Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.
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Climate change will have far-reaching impacts on biodiversity, including increasing extinction rates. Current approaches to quantifying such impacts focus on measuring exposure to climatic change and largely ignore the biological differences between species that may significantly increase or reduce their vulnerability. To address this, we present a framework for assessing three dimensions of climate change vulnerability, namely sensitivity, exposure and adaptive capacity; this draws on species' biological traits and their modeled exposure to projected climatic changes. In the largest such assessment to date, we applied this approach to each of the world's birds, amphibians and corals (16,857 species). The resulting assessments identify the species with greatest relative vulnerability to climate change and the geographic areas in which they are concentrated, including the Amazon basin for amphibians and birds, and the central Indo-west Pacific (Coral Triangle) for corals. We found that high concentration areas for species with traits conferring highest sensitivity and lowest adaptive capacity differ from those of highly exposed species, and we identify areas where exposure-based assessments alone may over or under-estimate climate change impacts. We found that 608-851 bird (6-9%), 670-933 amphibian (11-15%), and 47-73 coral species (6-9%) are both highly climate change vulnerable and already threatened with extinction on the IUCN Red List. The remaining highly climate change vulnerable species represent new priorities for conservation. Fewer species are highly climate change vulnerable under lower IPCC SRES emissions scenarios, indicating that reducing greenhouse emissions will reduce climate change driven extinctions. Our study answers the growing call for a more biologically and ecologically inclusive approach to assessing climate change vulnerability. By facilitating independent assessment of the three dimensions of climate change vulnerability, our approach can be used to devise species and area-specific conservation interventions and indices. The priorities we identify will strengthen global strategies to mitigate climate change impacts.
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Shin, Y-J., and Shannon, L. J. 2010. Using indicators for evaluating, comparing and communicating the ecological status of exploited marine ecosystems. 1. The IndiSeas project. – ICES Journal of Marine Science, 67: 686–691. One of the challenges faced by the scientific community grappling with the ecosystem approach to fisheries is to propose a generic set of synthetic ecological indicators, which would accurately reflect the effects of fisheries on marine ecosystems, and could support sound communication and management practices. The IndiSeas Working Group was established in 2005 under the auspices of the Eur-Oceans Network of Excellence to develop methods to provide indicators-based assessments of the status of exploited marine ecosystems in a comparative framework. Here, we present the two main outputs of the first phase of the project: a suite of papers documenting a combination of indicator-based methods and results comparing the ecological status of the world's exploited marine ecosystems, and a website aiming to communicate these results beyond scientific audiences.
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With global science-policy conventions for biodiversity and ecosystem services in place, much effort goes into monitoring and reporting on the progress toward policy targets. As conservation actions happen locally, can such global monitoring and reporting efforts effectively guide conservation actions at subnational level? In this paper we explore three different perspectives: policy reporting for policy implementation; scientific knowledge for empowerment and actions; and from past trends to influencing the future. Using these three perspectives, we identify ways forward for both decision makers and scientists on how to engage, inform and empower a larger diversity of actors who make decisions on the future of biodiversity and ecosystem services at multiple scales.
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Marine biodiversity and ecosystem functioning have changed and are continuing to change in marine ecosystems across the world. These changes are driven by human interactions with the environment and ecosystems, as well as by natural environmental change, both locally (at the ecosystem level) and globally. This paper draws on published research, in particular that using ecosystem indicators to identify, assess and compare changes in biodiversity of exploited marine ecosystems across the globe. We use our results to reflect on the sustainability of our changing exploited marine ecosystems and consider ways forward to incorporate this information in decision making processes.
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As ecosystem assessments represent syntheses of knowledge on ecosystem status created to answer key policy questions, it is important to identify whether the dialogue between assessment practitioners and policy makers is delivering the goals which ecosystem assessment practitioners seek. A number of global and national ecosystem assessment processes are underway between now and 2020, and best practice in creating assessments which have stakeholder buy in and policy relevance is subject to continuing refinement. While there are few unequivocal examples of assessments driving policy change (due to political decision-making processes being affected by a multiplicity of considerations beyond the availability of evidence), building a strong case around which assessments have informed policy development will enhance future legitimacy of ecosystem assessments in political dialogue.
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Scenarios are important tools to facilitate the communication among scientists, practitioners, and decision-makers, and, thus to support policy and management decisions. The use of scenarios has an enormous potential to reduce ecosystem restoration costs and to optimize benefits, but this potential remains poorly explored. Here, we recommend and illustrate six best practices to guide the use of scenarios for planning native ecosystem restoration. We argue, first, for a participatory process to consider aspirations of multiple stakeholders along the whole scenario building process, from planning to implementation and review phases. Second, targeted restoration outcomes should be defined by key-actors (those who have direct interests in restoration) and directly involved stakeholders, within a clear socio-environmental context and under a well-defined problem statement, considering a broad range of nature and human benefits that can be derived from ecosystem restoration. Third, methodological choices, such as scenario types, spatial and temporal scales, drivers, restoration-related variables, and indicators, should be defined according to the multiple desired outcomes. Fourth, we encourage the consideration of the interactions among variables, within a spatially explicit, and temporally dynamic multi-criteria approach. Fifth, analysis and dissemination of scenario results should highlight the trade-offs and synergies among different restoration outcomes, identifying the scenarios that maximize benefits and minimize costs and resistance (i.e. the cost-effective and most feasible scenario) for multiple targets. Finally, promoting capacity building, through a wider consultation process including interaction with a broader group of stakeholders, is critical for the successful implementation and review of restoration interventions. Scenarios that support ecosystem restoration should follow an adaptive and iterative process, aiming to continuously improve restoration interventions and outcomes.
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Spatially well-informed decisions are essential to sustain and regulate processes and ecosystem services (ES), and to maintain the capacity of ecosystems to supply services. However, spatially explicit ES information is often lacking in decision-making, or exists only as ES maps based on categorical land cover data. Remote sensing (RS) opens new pathways to map ES, in particular biophysical ES supply. We developed an observation-based concept for spatially explicit and continuous ES mapping at landscape scale following the biophysical part of the ES cascade. We used Earth observations in combination with in situ data to map ecosystem properties, functions, and biophysical ES supply. We applied this concept in a case study to map two ES: carbon dioxide regulation and food supply. Based on Earth observations and in situ data, we determined the ecosystem property Sun-Induced chlorophyll Fluorescence (SIF) to indicate ecosystem state and applied scaling models to estimate gross primary production (GPP) as indicator for ecosystem functioning and consequently carbon dioxide regulation and food supply as ES.
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Tens of thousands of species are threatened with extinction as a result of human activities. Here we explore how the extinction risks of terrestrial mammals and birds might change in the next 50 years. Future population growth and economic development are forecasted to impose unprecedented levels of extinction risk on many more species worldwide, especially the large mammals of tropical Africa, Asia and South America. Yet these threats are not inevitable. Proactive international efforts to increase crop yields, minimize land clearing and habitat fragmentation, and protect natural lands could increase food security in developing nations and preserve much of Earth's remaining biodiversity. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
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New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species’ responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity.
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Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales. This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity – taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization – molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the species traits concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research. EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models.
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Indicators have been recognised as a useful tool aiding the implementation of an ecosystem approach to fisheries in marine ecosystems. Studies, such as the IndiSeas project (www.indiseas.org), use a suite of indicators as a method of assessing the state and trends of several of the world's marine ecosystems. While it is well known that both fishing and climatic variability influence marine fisheries in the southern Benguela ecosystem there are currently few studies in support of fisheries management that make use of environmental indicators in order to include climatic impacts on marine fish populations. Trends in ecological, fishing and environmental indicators can be utilised in a way that allows an overall ecosystem trend to be determined, and can therefore be used to aid decision support within southern Benguela fisheries. In this study trends in indicators were determined using linear regressions across three time periods, Period 1: 1978-1993, Period 2: 1994-2003 and Period 3: 2004-2010. These time periods were selected based on the timing of regime shifts within the southern Benguela, including changes in upwelling, wind stress and temperature. Each ecological indicator received a score based on the direction and significance of the observed trend with respect to fishing. To account for the impacts of fishing and environmental drivers on ecological indicators, scores were adjusted by predetermined factors, depending on the extent and direction of trends in these indicators. Weightings were applied to correlated ecological indicators to account for their redundancy, and lessen their impact on overall ecosystem score. Mean weighted scores were then used to establish an overall ecosystem score for each time period. Ecosystem classification was determined as follows: 1-1.49 = improving, 1.5-2.49 = possibly improving, 2.5-3.49 = no improvement or deterioration, 3.5-4.49 = possible deterioration, 4.5-5 = deteriorating. The ecosystem was observed to neither deteriorate nor improve across Period 1 or 2 (mean weighted scores: 2.75 and 2.56 respectively), however, during Period 3 a possible improvement was observed (mean weighted score: 1.99). This study shows that the sequential analysis of suites of ecological, fishing and environmental indicators can be used in order to determine ecosystem trends, accounting for both the impacts of fishing and the environment on ecosystem components.
Article
There is increasing reliance on ecological models to improve our understanding of how ecological systems work, to project likely outcomes under alternative global change scenarios and to help develop robust management strategies. Two common types of spatiotemporally explicit ecological models are those focussed on biodiversity composition and those focussed on ecosystem function. These modelling disciplines are largely practiced separately, with separate literature, despite growing evidence that natural systems are shaped by the interaction of composition and function. Here we call for the development of new modelling approaches that integrate composition and function, accounting for the important interactions between these two dimensions, particularly under rapid global change. We examine existing modelling approaches that have begun to combine elements of composition and function, identifying their potential contribution to fully integrated modelling approaches. The development and application of integrated models of composition and function face a number of important challenges, including biological data limitations, system knowledge and computational constraints. We suggest a range of promising avenues that could help researchers overcome these challenges, including the use of virtual species, macroecological relationships and hybrid correlative-mechanistic modelling. Explicitly accounting for the interactions between composition and function within integrated modelling approaches has the potential to improve our understanding of ecological systems, provide more accurate predictions of their future states and transform their management.This article is protected by copyright. All rights reserved.
Article
IndiSeas (“Indicators for the Seas”) is a collaborative international working group that was established in 2005 to evaluate the status of exploited marine ecosystems using a suite of indicators in a comparative framework. An initial shortlist of seven ecological indicators was selected to quantify the effects of fishing on the broader ecosystem using several criteria (i.e., ecological meaning, sensitivity to fishing, data availability, management objectives and public awareness). The suite comprised: (i) the inverse coefficient of variation of total biomass of surveyed species, (ii) mean fish length in the surveyed community, (iii) mean maximum life span of surveyed fish species, (iv) proportion of predatory fish in the surveyed community, (v) proportion of under and moderately exploited stocks, (vi) total biomass of surveyed species, and (vii) mean trophic level of the landed catch. In line with the Nagoya Strategic Plan of the Convention on Biological Diversity (2011–2020), we extended this suite to emphasize the broader biodiversity and conservation risks in exploited marine ecosystems. We selected a subset of indicators from a list of empirically based candidate biodiversity indicators initially established based on ecological significance to complement the original IndiSeas indicators. The additional selected indicators were: (viii) mean intrinsic vulnerability index of the fish landed catch, (ix) proportion of non-declining exploited species in the surveyed community, (x) catch-based marine trophic index, and (xi) mean trophic level of the surveyed community. Despite the lack of data in some ecosystems, we also selected (xii) mean trophic level of the modelled community, and (xiii) proportion of discards in the fishery as extra indicators. These additional indicators were examined, along with the initial set of IndiSeas ecological indicators, to evaluate whether adding new biodiversity indicators provided useful additional information to refine our understanding of the status evaluation of 29 exploited marine ecosystems. We used state and trend analyses, and we performed correlation, redundancy and multivariate tests. Existing developments in ecosystem-based fisheries management have largely focused on exploited species. Our study, using mostly fisheries independent survey-based indicators, highlights that biodiversity and conservation-based indicators are complementary to ecological indicators of fishing pressure. Thus, they should be used to provide additional information to evaluate the overall impact of fishing on exploited marine ecosystems.
Article
Accelerating rates of environmental change and the continued loss of global biodiversity threaten functions and services delivered by ecosystems. Much ecosystem monitoring and management is focused on the provision of ecosystem functions and services under current environmental conditions, yet this could lead to inappropriate management guidance and undervaluation of the importance of biodiversity. The maintenance of ecosystem functions and services under substantial predicted future environmental change (i.e., their 'resilience') is crucial. Here we identify a range of mechanisms underpinning the resilience of ecosystem functions across three ecological scales. Although potentially less important in the short term, biodiversity, encompassing variation from within species to across landscapes, may be crucial for the longer-term resilience of ecosystem functions and the services that they underpin.
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In 2010, the international community, under the auspices of the Convention on Biological Diversity, agreed on 20 biodiversity-related “Aichi Targets” to be achieved within a decade. We provide a comprehensive mid-term assessment of progress toward these global targets using 55 indicator data sets. We projected indicator trends to 2020 using an adaptive statistical framework that incorporated the specific properties of individual time series. On current trajectories, results suggest that despite accelerating policy and management responses to the biodiversity crisis, the impacts of these efforts are unlikely to be reflected in improved trends in the state of biodiversity by 2020. We highlight areas of societal endeavor requiring additional efforts to achieve the Aichi Targets, and provide a baseline against which to assess future progress.
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Human impacts on the biosphere are a matter of urgent and growing concern, with ecologists increasingly being asked to project biodiversity futures. The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is likely to comprehensively assess such projections, yet despite being widely used and potentially critical tools for analysing socio-environmental futures, integrated assessment models (IAMs) have received little attention from ecological modellers. We aim to raise awareness and understanding of IAMs among ecologists by describing the structure and composition of IAMs, assessing their utility for biodiversity projections and identifying limitations that hamper greater interaction between scientists using IAMs and those using ecological models. We also hope to inspire more accessible and applicable models by suggesting development needs for IAMs.