Decision Support Tools for Land Management

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 15869

Special Issue Editors

Rocky Mountain Research Station, USDA Forest Service, Rapid City, SD 57702, USA
Interests: coupled human-environment systems; fire; grasslands; land use and land change
Special Issues, Collections and Topics in MDPI journals
USDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59801, USA
Interests: climate change effects on rangelands; decision support tools; adaptation
Special Issues, Collections and Topics in MDPI journals
USDA Northwest Climate Hub, Forest Service Pacific Northwest Research Station, Portland, OR 97204, USA
Interests: agricultural economics; rangeland ecosystem services; decision-making under climate variability

Special Issue Information

Dear Colleagues,

This Special Issue is focused on decision support tools for management and planning at multiple scales. Decision support tools typically integrate data into models to provide explicit, practical decision support for a variety of problems, both current and future. Becoming ready for the future means doing everything we can today to increase resiliency and deploy adaptation strategies in a cost-effective manner.

We welcome research about a variety of tool types that directly or indirectly support economic and ecological resiliency and/or preparedness in a changing climate. Tools can range from static GIS overlays, automated remote sensing applications, multi-criteria assessments, and conceptual structured decision-making steps. Within the decision-support context, contributors from different fields are invited to submit their articles on topics including (but not limited to): identification of vulnerabilities to extreme events, adaptive approaches to climate change, prescribed fire and post-fire restoration, prioritization of landscapes for conservation (vs. random acts of conservation), watershed restoration, land zoning and planning, water use, food production, energy siting, invasive species detection, rare species conservation, and public land management. Research should center around tangible tools that provide actionable and easily communicated decision support information to managers, planners, agricultural producers, and/or other key decision-makers. Demonstrated decision support applications (matching support tools to decision-makers) and quantifiable outcomes are highly encouraged.

Dr. Brice B. Hanberry
Dr. Matthew Reeves
Dr. Anna T. Maher
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Application
  • Adaptation
  • Adaptive capacity
  • Climate
  • Conservation
  • Disturbance
  • Energy
  • Fire
  • Food production
  • Invasive species
  • Landscape prioritization
  • Management
  • Model
  • Planning
  • Rare species
  • Restoration
  • Resiliency
  • Vulnerability
  • Water
  • Watershed

Published Papers (7 papers)

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Research

35 pages, 3583 KiB  
Article
Mapping Firescapes for Wild and Prescribed Fire Management: A Landscape Classification Approach
by Nicholas P. Gould, Lars Y. Pomara, Sandhya Nepal, Scott L. Goodrick and Danny C. Lee
Land 2023, 12(12), 2180; https://doi.org/10.3390/land12122180 - 17 Dec 2023
Cited by 1 | Viewed by 1263
Abstract
Risks associated with severe wildfire are growing in forest landscapes due to interactions among climate change, fuel accumulation from fire suppression, an expanding wildland–urban interface, and additional factors. People, infrastructure, ecosystem services, and forest health all face varying degrees of risk. The spatial [...] Read more.
Risks associated with severe wildfire are growing in forest landscapes due to interactions among climate change, fuel accumulation from fire suppression, an expanding wildland–urban interface, and additional factors. People, infrastructure, ecosystem services, and forest health all face varying degrees of risk. The spatial distributions of the many social and ecological factors that influence wildfire, its impacts, and management responses are an important landscape-level context for managing risks and fostering resilient lands and communities. Decision-support tools that integrate these varied distributions can provide a holistic and readily interpreted characterization of landscapes, helping fire management decision making be appropriate, efficient, and effective. Firescapes—landscape types defined in relation to fire, its drivers, and its effects as a socioecological system—fill this role, providing a way to organize and interpret spatial variation along multiple relevant dimensions. We describe a quantitative approach for classifying and mapping firescapes for decision support, using the southeastern United States as a case study. We worked with regional partners to compile relevant large-scale datasets and identify 73 variables for analysis. We used factor analysis to reduce the data to eight factors with intuitive interpretations relevant to fire dynamics, fire history, forest characteristics, climate, conservation and ecosystem service values, social and ecological landscape properties, and social vulnerabilities. We then used cluster analysis on the factors to generate quantitative landscape classes, which we interpreted as nine distinctive firescape classes. The firescapes provide a broad-scale socioecological information context for wildfire risk management and planning. The analytical approach can accommodate different data types at a variety of scales, incorporate new monitoring data as they are available, and can be used under data-driven scenarios to assess possible consequences of future change. The resulting firescape maps can provide decision support to forest managers, planners, and other stakeholders, informing appropriate strategies to manage fire and associated risks, build community and forest resilience to fire, and improve conservation outcomes. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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25 pages, 8947 KiB  
Article
Wildfire Risk Assessment for Strategic Forest Management in the Southern United States: A Bayesian Network Modeling Approach
by Sandhya Nepal, Lars Y. Pomara, Nicholas P. Gould and Danny C. Lee
Land 2023, 12(12), 2172; https://doi.org/10.3390/land12122172 - 16 Dec 2023
Cited by 1 | Viewed by 1044
Abstract
Wildfire occurrences have increased and are projected to continue increasing globally. Strategic, evidence-based planning with diverse stakeholders, making use of diverse ecological and social data, is crucial for confronting and mitigating the associated risks. Prescribed fire, when planned and executed carefully, is a [...] Read more.
Wildfire occurrences have increased and are projected to continue increasing globally. Strategic, evidence-based planning with diverse stakeholders, making use of diverse ecological and social data, is crucial for confronting and mitigating the associated risks. Prescribed fire, when planned and executed carefully, is a key management tool in this effort. Assessing where prescribed fire can be a particularly effective forest management tool can help prioritize efforts, reduce wildfire risk, and support fire-resilient lands and communities. We collaborated with expert stakeholders to develop a Bayesian network model that integrated a large variety of biophysical, socioecological, and socioeconomic spatial information for the Southeastern United States to quantify where risk is high and where prescribed fire would be efficient in mitigating risk. The model first estimated wildfire risk based on landscape-scale interactions among the likelihoods of fire occurrence and severity and the people and resources potentially exposed—accounting for socioeconomic vulnerabilities as well as key ecosystem services. The model then quantified the potential for risk reduction through prescribed fire, given the existing fuel load, climate, and other landscape conditions. The resulting expected risk estimates show high risk concentrated in the coastal plain and interior highland subregions of the Southern US, but there was considerable variation among risks to different ecosystem services and populations, including potential exposure to smoke emissions. The capacity to reduce risk through fuel reductions was spatially correlated with risk; where these diverged, the difference was largely explained by fuel load. We suggest that both risk and the capacity for risk reduction are important in identifying priorities for management interventions. The model serves as a decision support tool for stakeholders to coordinate large-landscape adaptive management initiatives in the Southern US. The model is flexible with regard to both empirical and expert-driven parameterizations and can be updated as new knowledge and data emerge. The resulting spatial information can help connect active management options to forest management goals and make management more efficient through targeted investments in priority landscapes. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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13 pages, 1608 KiB  
Article
Modeling Herbaceous Biomass for Grazing and Fire Risk Management
by Edward C. Rhodes, Douglas R. Tolleson and Jay P. Angerer
Land 2022, 11(10), 1769; https://doi.org/10.3390/land11101769 - 12 Oct 2022
Cited by 2 | Viewed by 1337
Abstract
Both grazing and fine fuels management are dependent on the temporal and spatial distribution of herbaceous biomass production. Rangeland and wildland fire managers can both benefit from knowing when and where there is excessive herbaceous biomass buildup. In this study, we compared modeled [...] Read more.
Both grazing and fine fuels management are dependent on the temporal and spatial distribution of herbaceous biomass production. Rangeland and wildland fire managers can both benefit from knowing when and where there is excessive herbaceous biomass buildup. In this study, we compared modeled herbaceous biomass outputs from the Phytomass Growth Simulator (Phygrow) to observe and predict herbaceous production on desert, juniper, and pine sites on the Coconino National Forest in Arizona. Models were validated with: (a) 2 years of quarterly data, and (b) fire season-only data. The Phygrow model showed strong agreement between observed and predicted values year-round on the desert (r2 = 0.73) and pine sites (r2 = 0.69), and a lower, but positive agreement in the juniper sites (r2 = 0.54). Fire season predictions were strong for all ecosystem types (desert r2 = 0.89; juniper r2 = 0.62; pine r2 = 0.94), suggesting that the Phygrow model is well suited to provide valuable decision support information with which to address both rangeland and fire management objectives. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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19 pages, 4015 KiB  
Article
The Bighorn Habitat Assessment Tool: A Method to Quantify Conservation Value on Landscapes Impacted by Mining
by Dayan J. Anderson, Vernon C. Bleich and Jeffrey T. Villepique
Land 2022, 11(4), 552; https://doi.org/10.3390/land11040552 - 08 Apr 2022
Viewed by 1648
Abstract
We present a methodology to assess the conservation value of mitigation lands for desert bighorn sheep (Ovis canadensis nelsoni) within landscapes impacted by historic and ongoing industrial uses. The Bighorn Habitat Assessment Tool (BHAT) was developed to support the adaptive management [...] Read more.
We present a methodology to assess the conservation value of mitigation lands for desert bighorn sheep (Ovis canadensis nelsoni) within landscapes impacted by historic and ongoing industrial uses. The Bighorn Habitat Assessment Tool (BHAT) was developed to support the adaptive management of the Cushenbury population of bighorn sheep located on the north slope of the San Bernardino Mountains in southern California, USA. We use a novel formulation of conservation value integrating the results of resource selection function analysis and reclamation credits, reflecting the degree to which degraded habitat is enhanced to benefit wild sheep. Our method seeks to balance conservation objectives simultaneously with the economic development of a working mine landscape. Specifically, the BHAT can be used to (a) establish a habitat reserve providing maximum benefit to the unique requirements of bighorn sheep; (b) incentivize voluntary action by industry to ensure mining activities are compatible with conservation; (c) allow for the evaluation of multiple mine planning and resource management alternatives; and (d) ensure that future compensatory mitigation actions for mining activity are grounded in the best available science. Our methodology is transferrable to the management of other wild sheep populations occupying mine-influenced landscapes for which sufficient data are available to complete resource selection analyses. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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23 pages, 8189 KiB  
Article
Tree Advisor: A Novel Woody Plant Selection Tool to Support Multifunctional Objectives
by Gary Bentrup and Michael G. Dosskey
Land 2022, 11(3), 397; https://doi.org/10.3390/land11030397 - 08 Mar 2022
Cited by 3 | Viewed by 2747
Abstract
Purposefully planted trees and shrubs can provide multiple benefits when appropriately planned and designed. Tools to help select species that will function more effectively than other species for ecosystem services, production, and aesthetic purposes are generally lacking. To address this challenge, we developed [...] Read more.
Purposefully planted trees and shrubs can provide multiple benefits when appropriately planned and designed. Tools to help select species that will function more effectively than other species for ecosystem services, production, and aesthetic purposes are generally lacking. To address this challenge, we developed an interactive plant selection tool entitled Tree Advisor that rates woody species for a wide range of different purposes based on plant attributes. In this prototype decision support tool, 90 species of trees and shrubs are rated for 14 different purposes in the northern and central Great Plains region of the United States. A rating algorithm was developed based on the scientific literature regarding plant functions and related attributes that determine relative performance of a species for each purpose. User input and best practices for developing effective decision support tools informed the tool development process. Based on user feedback, the tool supports multifunctional planning and enables a user to quickly develop a short list of the better species to use which can then be refined by the user based on suitability under local site conditions, commercial availability, and availability of locally adapted cultivars and hybrids. This tool development approach can serve as a model for producing multifunctional woody plant selection tools for other ecoregions. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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21 pages, 2737 KiB  
Article
Conservation Prioritization in a Tiger Landscape: Is Umbrella Species Enough?
by Vaishali Vasudeva, Sujata Upgupta, Ajay Singh, Nazrukh Sherwani, Supratim Dutta, Rajasekar Rajaraman, Sankarshan Chaudhuri, Satyam Verma, Jeyaraj Antony Johnson and Ramesh Krishnamurthy
Land 2022, 11(3), 371; https://doi.org/10.3390/land11030371 - 03 Mar 2022
Cited by 4 | Viewed by 3696
Abstract
Conservation approaches in tiger landscapes have focused on single species and their habitat. Further, the limited extent of the existing protected area network in India lacks representativeness, habitat connectivity, and integration in the larger landscape. Our objective was to identify sites important for [...] Read more.
Conservation approaches in tiger landscapes have focused on single species and their habitat. Further, the limited extent of the existing protected area network in India lacks representativeness, habitat connectivity, and integration in the larger landscape. Our objective was to identify sites important for connected tiger habitat and biodiversity potential in the Greater Panna Landscape, central India. Further, we aimed to set targets at the landscape level for conservation and prioritize these sites within each district in the landscape as specific management/conservation zones. We used earth observation data to derive an index of biodiversity potential. Marxan was used to identify sites that met tiger and biodiversity conservation targets with minimum costs. We found that to protect 50% of the tiger habitat with connectivity, 20% of the landscape area must be conserved. To conserve 100% of high biodiversity potential, 50% moderate biodiversity potential, and 25% low biodiversity potential, 55% of the landscape area must be conserved. To represent both tiger habitat and biodiversity, 62% of the total landscape area requires conservation or restoration intervention. The prioritized zones can prove significant for hierarchical decision making, involving multiple stakeholders in the landscape, including other tiger range areas. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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13 pages, 1434 KiB  
Article
Assessing the Impacts of Rural Development Plan Measures on the Sustainability of Agricultural Holdings Using a PMP Model
by Christina Moulogianni and Thomas Bournaris
Land 2021, 10(5), 446; https://doi.org/10.3390/land10050446 - 22 Apr 2021
Cited by 5 | Viewed by 2206
Abstract
Rural Development Plan (RDP) measures support farmers in improving the sustainability of their agricultural holdings. The implementation of these policies has economic, social, and environmental impacts, which are monitored either ex-ante, ongoing, or ex-post, as required from the European Commission impact assessment guidelines. [...] Read more.
Rural Development Plan (RDP) measures support farmers in improving the sustainability of their agricultural holdings. The implementation of these policies has economic, social, and environmental impacts, which are monitored either ex-ante, ongoing, or ex-post, as required from the European Commission impact assessment guidelines. In this frame, this paper aims to assess the impacts of RDP measures on the sustainability of agricultural holdings. For this reason, a positive mathematical programming (PMP) model was developed and implemented in combination with a set of economic, social, and environmental indicators. The model was used to assess the ex-post impacts of the measure titled ‘Modernization of agricultural holdings’ of the Greek RDP 2007–2013. This research was conducted on a sample of 219 agricultural holdings in a region of northern Greece. The impacts were measured through the changes of the crop plan in the agricultural land. The results show that the measure has positive economic impacts, negative social impacts, and negative impacts on most of the environmental indicators. The results also underline the significant role of the impact assessment process in supporting policymakers in understanding the impacts of their policies. Full article
(This article belongs to the Special Issue Decision Support Tools for Land Management)
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