A B S T R A C TWe are increasingly confronted with severe social and economic impacts of environmental degradation all over the world. From a valuation perspective, environmental problems and conflicts originate from trade-offs http://dx.Ecosystem Services (xxxx) xxxx-xxxx 2212-0416/ Ecosystem services Intrinsic value Benefits of nature Quality of life Participation Social and environmental justice Decision supportbetween values. The urgency and importance to integrate nature's diverse values in decisions and actions stand out more than ever.Valuation, in its broad sense of 'assigning importance', is inherently part of most decisions on natural resource and land use. Scholars from different traditions -while moving from heuristic interdisciplinary debate to applied transdisciplinary science-now acknowledge the need for combining multiple disciplines and methods to represent the diverse set of values of nature. This growing group of scientists and practitioners share the ambition to explore how combinations of ecological, socio-cultural and economic valuation tools can support real-life resource and land use decision-making.The current sustainability challenges and the ineffectiveness of single-value approaches to offer relief demonstrate that continuing along a single path is no option. We advocate for the adherence of a plural valuation culture and its establishment as a common practice, by contesting and complementing ineffective and discriminatory single-value approaches. In policy and decision contexts with a willingness to improve sustainability, integrated valuation approaches can be blended in existing processes, whereas in contexts of power asymmetries or environmental conflicts, integrated valuation can promote the inclusion of diverse values through action research and support the struggle for social and environmental justice.The special issue and this editorial synthesis paper bring together lessons from pioneer case studies and research papers, synthesizing main challenges and setting out priorities for the years to come for the field of integrated valuation.
The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.
ABSTRACT. The governance of ecosystem services (ES) has been predominantly thought of in terms of market or state-based instruments. Comparatively, collective action mechanisms have rarely been considered. This paper addresses this gap by proposing a conceptual framework that brings together ES, social interdependencies, and collective action thinking. We use an ES conceptual lens to highlight social interdependencies among people so as to reflect on existing or potential collective actions among them. This framework can also contribute to increasing people's awareness of their mutual interdependencies and thereby fostering, framing, or enriching collective action, in ways that take into account the diversity and complexity of ecological processes underlying human activities. Our approach can contribute in particular to agroecological transitions that require landscape level innovations and coordination mechanisms among land users and managers. The framework distinguishes three types of social interdependencies: (i) between ES beneficiaries and ES providers, (ii) among beneficiaries, and (iii) among providers. These social interdependencies are in turn analyzed according to four main dimensions that are critical for collective action: (i) cognitive framing of interdependencies, (ii) levels of organization, (iii) formal and informal institutions, and (iv) power relations. Finally, we propose a strategy to turn this framework into action in contexts of participatory action research, a strategy grounded on a number of methodological principles and tools that convey complexity and increase people's awareness of interdependencies in agrarian social-ecological systems.
Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns.
Biological invasions and land-use changes are two major causes of the global modifications of biodiversity. Habitat suitability models are the tools of choice to predict potential distributions of invasive species. Although land-use is a key driver of alien species invasions, it is often assumed that land-use is constant in time. Here we combine historical and present day information, to evaluate whether land-use changes could explain the dynamic of invasion of the American bullfrog Rana catesbeiana ( 5 Lithobathes catesbeianus) in Northern Italy, from the 1950s to present-day. We used MAXENT to build habitat suitability models, on the basis of past (1960s, 1980s) and present-day data on land-uses and species distribution. For example, we used models built using the 1960s data to predict distribution in the 1980s, and so on. Furthermore, we used land-use scenarios to project suitability in the future. Habitat suitability models predicted well the spread of bullfrogs in the subsequent temporal step. Models considering land-use changes predicted invasion dynamics better than models assuming constant land-use over the last 50 years. Scenarios of future land-use suggest that suitability will remain similar in the next years. Habitat suitability models can help to understand and predict the dynamics of invasions; however, land-use is not constant in time: land-use modifications can strongly affect invasions; furthermore, both land management and the suitability of a given land-use class may vary in time. An integration of land-use changes in studies of biological invasions can help to improve management strategies.
River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.