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1.
PLoS One ; 18(2): e0281348, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36827966

RESUMEN

This article describes the adaptation of a non-spatial model of pastureland dynamics, including vegetation life cycle, livestock management and nitrogen cycle, for use in a spatially explicit and modular modelling platform (k.LAB) dedicated to make data and models more interoperable. The aim is to showcase to the social-ecological modelling community the delivery of an existing, monolithic model, into a more modular, transparent and accessible approach to potential end users, regional managers, farmers and other stakeholders. This also allows better usability and adaptability of the model beyond its originally intended geographical scope (the Cantabrian Region in the North of Spain). The original code base (written in R in 1,491 lines of code divided into 13 files) combines several algorithms drawn from the literature in an opaque fashion due to lack of modularity, non-semantic variable naming and implicit assumptions. The spatiotemporal rewrite is structured around a set of 10 namespaces called PaL (Pasture and Livestock), which includes 198 interoperable and independent models. The end user chooses the spatial and temporal context of the analysis through an intuitive web-based user interface called k.Explorer. Each model can be called individually or in conjunction with the others, by querying any PaL-related concepts in a search bar. A scientific dataflow and a provenance diagram are produced in conjunction with the model results for full transparency. We argue that this work demonstrates key steps needed to create more Findable, Accessible, Interoperable and Reusable (FAIR) models beyond the selected example. This is particularly essential in environments as complex as agricultural systems, where multidisciplinary knowledge needs to be integrated across diverse spatial and temporal scales in order to understand complex and changing problems.


Asunto(s)
Algoritmos , Ganado , Animales , España , Modelos Teóricos
2.
Ecosyst Serv ; 432020 Jun 01.
Artículo en Inglés | MEDLINE | ID: mdl-33365228

RESUMEN

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

3.
Sci Total Environ ; 650(Pt 2): 2325-2336, 2019 Feb 10.
Artículo en Inglés | MEDLINE | ID: mdl-30292124

RESUMEN

Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five "Tier 1" ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed.


Asunto(s)
Conservación de los Recursos Naturales , Ecosistema , Modelos Biológicos , Análisis Espacial
4.
Sci Total Environ ; 654: 763-777, 2019 Mar 01.
Artículo en Inglés | MEDLINE | ID: mdl-30448667

RESUMEN

Large river-floodplain systems are hotspots of biodiversity and ecosystem services but are also used for multiple human activities, making them one of the most threatened ecosystems worldwide. There is wide evidence that reconnecting river channels with their floodplains is an effective measure to increase their multi-functionality, i.e., ecological integrity, habitats for multiple species and the multiple functions and services of river-floodplain systems, although, the selection of promising sites for restoration projects can be a demanding task. In the case of the Danube River in Europe, planning and implementation of restoration projects is substantially hampered by the complexity and heterogeneity of the environmental problems, lack of data and strong differences in socio-economic conditions as well as inconsistencies in legislation related to river management. We take a quantitative approach based on best-available data to assess biodiversity using selected species and three ecosystem services (flood regulation, crop pollination, and recreation), focused on the navigable main stem of the Danube River and its floodplains. We spatially prioritize river-floodplain segments for conservation and restoration based on (1) multi-functionality related to biodiversity and ecosystem services, (2) availability of remaining semi-natural areas and (3) reversibility as it relates to multiple human activities (e.g. flood protection, hydropower and navigation). Our approach can thus serve as a strategic planning tool for the Danube and provide a method for similar analyses in other large river-floodplain systems.

5.
Sci Total Environ ; 656: 797-807, 2019 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-30530149

RESUMEN

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requirements for effectively managing a balance between biodiversity and ESS supply and demand in freshwater ecosystems.


Asunto(s)
Organismos Acuáticos , Biodiversidad , Conservación de los Recursos Naturales/métodos , Ecosistema , Capital Social , Medio Social , Teorema de Bayes , Europa (Continente)
6.
Sci Total Environ ; 652: 1113-1128, 2019 Feb 20.
Artículo en Inglés | MEDLINE | ID: mdl-30586798

RESUMEN

The Baixo Vouga Lagunar (BVL) is part of Ria de Aveiro coastal lagoon in Portugal, which is classified as a Special Protection Area under the European Habitats and Birds Directives. This part of the system, corresponding to the confluence of the Vouga River with the lagoon, is very important culturally and socioeconomically for the local communities, taking place several human activities, especially agriculture. To prevent salt water intrusion from the Ria de Aveiro into agriculture fields, a floodbank was initiated in the 90's. In frame of ongoing changes in Ria de Aveiro hydrodynamics, the existing floodbank will be now extended, introducing further changes in the ecological dynamics of the BVL and its adjacent area. As a consequence, the water level in the floodbank downstream side is expected to rise, increasing the submersion period in tidal wetlands, and leading to coastal squeeze. The aim of this study is to apply an ecosystem based-management approach to mitigate the impacts on biodiversity resulting from the management plan. To do so, we have modelled the implications of the changes in several hydrological and environmental variables on four saltmarsh species and habitats distribution, as well as on their associated ecosystem services, both upstream and downstream of the floodbank. The ecosystem services of interest were prioritized by stakeholders' elicitation, which were then used as an input to a spatial multi-criteria analysis aimed to find the best management actions to compensate for the unintended loss of biodiversity and ecosystem services in the BVL. According to our results, the main areas to be preserved in the BVL were the traditional agricultural mosaic fields; the freshwater courses and the subtidal estuarine channels. By combining ecology with the analysis of social preferences, this study shows how co-developed solutions can support adaptive management and the conservation of coastal ecosystems.

7.
Sci Total Environ ; 652: 1463-1473, 2019 Feb 20.
Artículo en Inglés | MEDLINE | ID: mdl-30586831

RESUMEN

Green and Blue Infrastructure (GBI) is a network designed and planned to deliver a wide range of ecosystem services and to protect biodiversity. Existing GBI designs lacked a systematic method to allocate restoration zones. This study proposes a novel approach for systematically selecting cost-effective areas for restoration on the basis of biodiversity, ecosystem services, and ecosystem condition to give an optimal spatial design of GBI. The approach was tested at a regional scale, in a transboundary setting encompassing the Intercontinental Biosphere Reserve of the Mediterranean in Andalusia (Spain) - Morocco (IBRM), across three aquatic ecosystems: freshwater, coastal and marine. We applied Marxan with Zones to stakeholder-defined scenarios of GBI in the IBRM. Specifically, we aimed to identify management zones within the GBl that addressed different conservation, restoration and exploitation objectives. Although almost all conservation targets were achieved, our results highlighted that the proportion of conservation features (i.e., biodiversity, ecosystem services) that would be compromised in the GBl, and the proportion of provisioning services that would be lost due to conservation (i.e., incidental representation) are potentially large, indicating that the probability of conflicts between conservation and exploitation goals in the area is high. The implementation of restoration zones improved connectivity across the GBI, and also achieved European and global policy targets. Our approach may help guide future applications of GBI to implement the flexible conservation management that aquatic environments require, considering many areas at different spatial scales, across multiple ecosystems, and in transboundary contexts.

8.
Philos Trans R Soc Lond B Biol Sci ; 369(1639): 20120286, 2014 Apr 05.
Artículo en Inglés | MEDLINE | ID: mdl-24535393

RESUMEN

As societal demand for food, water and other life-sustaining resources grows, the science of ecosystem services (ES) is seen as a promising tool to improve our understanding, and ultimately the management, of increasingly uncertain supplies of critical goods provided or supported by natural ecosystems. This promise, however, is tempered by a relatively primitive understanding of the complex systems supporting ES, which as a result are often quantified as static resources rather than as the dynamic expression of human-natural systems. This article attempts to pinpoint the minimum level of detail that ES science needs to achieve in order to usefully inform the debate on environmental securities, and discusses both the state of the art and recent methodological developments in ES in this light. We briefly review the field of ES accounting methods and list some desiderata that we deem necessary, reachable and relevant to address environmental securities through an improved science of ES. We then discuss a methodological innovation that, while only addressing these needs partially, can improve our understanding of ES dynamics in data-scarce situations. The methodology is illustrated and discussed through an application related to water security in the semi-arid landscape of the Great Ruaha river of Tanzania.


Asunto(s)
Ecología/métodos , Ecosistema , Abastecimiento de Alimentos/métodos , Crecimiento Demográfico , Abastecimiento de Agua , Ecología/tendencias , Humanos , Factores Socioeconómicos , Tanzanía
9.
PLoS One ; 9(3): e91001, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-24625496

RESUMEN

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant "one model fits all" paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES--both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.


Asunto(s)
Conservación de los Recursos Naturales/métodos , Monitoreo del Ambiente/métodos , Algoritmos , Toma de Decisiones , Ecosistema , Geografía , Clase Social , Programas Informáticos , Washingtón , Contaminantes del Agua/análisis
10.
Environ Manage ; 39(6): 887-99, 2007 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-17453273

RESUMEN

Assessment and economic valuation of services provided by ecosystems to humans has become a crucial phase in environmental management and policy-making. As primary valuation studies are out of the reach of many institutions, secondary valuation or benefit transfer, where the results of previous studies are transferred to the geographical, environmental, social, and economic context of interest, is becoming increasingly common. This has brought to light the importance of environmental valuation databases, which provide reliable valuation data to inform secondary valuation with enough detail to enable the transfer of values across contexts. This paper describes the role of next-generation, intelligent databases (IDBs) in assisting the activity of valuation. Such databases employ artificial intelligence to inform the transfer of values across contexts, enforcing comparability of values and allowing users to generate custom valuation portfolios that synthesize previous studies and provide aggregated value estimates to use as a base for secondary valuation. After a general introduction, we introduce the Ecosystem Services Database, the first IDB for environmental valuation to be made available to the public, describe its functionalities and the lessons learned from its usage, and outline the remaining needs and expected future developments in the field.


Asunto(s)
Conservación de los Recursos Naturales/economía , Bases de Datos como Asunto , Ecosistema , Contaminación Ambiental/economía , Administración de Residuos/economía , Abastecimiento de Agua/economía , Animales , Conservación de los Recursos Naturales/métodos , Contaminación Ambiental/legislación & jurisprudencia , Contaminación Ambiental/prevención & control , Humanos , Modelos Económicos , Formulación de Políticas , Administración de Residuos/métodos , Abastecimiento de Agua/legislación & jurisprudencia
11.
Environ Manage ; 29(3): 335-48, 2002 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-11830764

RESUMEN

Environmental decision-making and policy-making at all levels refers necessarily to synthetic, approximate quantification of environmental properties such as vulnerability, conservation status, and ability to recover after perturbation. Knowledge of such properties is essential to informed decision-making, but their definition is controversial and their precise characterization requires investments in research, modeling, and data collection that are only possible in the most developed countries. Environmental agencies and governments worldwide have increasingly requested numerical quantification or semiquantitative ranking of such attributes at the ecosystem, landscape, and country level. We do not have a theory to guide their calculation, in general or specific contexts, particularly with the amount of resources usually available in such cases. As a result, these measures are often calculated with little scientific justification and high subjectivity, and such doubtful approximations are used for critical decision-making. This problem applies particularly to countries with weak economies, such as small island states, where the most precious environmental resources are often concentrated. This paper discusses frameworks for a "least disappointing," approximate quantification of environmental vulnerability. After a review of recent research and recent attempts to quantify environmental vulnerability, we discuss models and theoretical frameworks for obtaining an approximate, standardizable vulnerability indicator of minimal subjectivity and maximum generality. We also discuss issues of empirical testing and comparability between indicators developed for different environments. To assess the state of the art, we describe an independent ongoing project developed in the South Pacific area and aimed to the comparative evaluation of the vulnerability of arbitrary countries.


Asunto(s)
Conservación de los Recursos Naturales , Ecosistema , Formulación de Políticas , Política Pública , Toma de Decisiones , Contaminantes Ambientales/efectos adversos , Guías como Asunto , Medición de Riesgo
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