Restoration Based on Cost-Benefit Optimization: A Grasslands Pilot Study
Ecological restoration is key for meeting global biodiversity conservation goals, but limited budgets make it challenging to decide where efforts will have the greatest impact. Scientists supported by this project developed a spatially explicit modeling framework that integrates land-use history, species distributions, and economic costs to optimize restoration site selection, helping conservation practitioners target resources more effectively.
Project Summary:
Ecological restoration is essential to addressing biodiversity loss, yet deciding where to restore habitat remains a key challenge, especially when restoration must account for habitat features that do not currently exist on the landscape. With growing interest in ecological restoration and finite resources, decision-makers need tools that help them evaluate tradeoffs and identify locations where restoration actions are most likely to succeed.
To address this need, the project team developed a spatially explicit modeling framework that integrates land-use history, species distribution data, and economic costs to identify priority areas for ecological restoration. The approach directly accounts for both ecological benefits and financial constraints, allowing users to explore alternative restoration scenarios. The framework is demonstrated through a case study on highly threatened grassland ecosystems in the Great Plains region of Kansas, USA.
The modeling framework is designed to be flexible and adaptable. It can be altered for future analyses of different ecosystems, species, and conservation priorities, as well as alternative restoration goals. By providing a data-driven approach to restoration planning, this project offers a decision-support tool that can help practitioners optimize restoration site selection and allocate limited resources more strategically.
- Source: USGS Sciencebase (id: 68d3fc51d4be023091a47f5e)
Toni Lyn Morelli, Ph.D.
Research Ecologist, Northeast CASC
Sarah Weiskopf, Ph.D.
Research Ecologist, National CASC
Ecological restoration is key for meeting global biodiversity conservation goals, but limited budgets make it challenging to decide where efforts will have the greatest impact. Scientists supported by this project developed a spatially explicit modeling framework that integrates land-use history, species distributions, and economic costs to optimize restoration site selection, helping conservation practitioners target resources more effectively.
Project Summary:
Ecological restoration is essential to addressing biodiversity loss, yet deciding where to restore habitat remains a key challenge, especially when restoration must account for habitat features that do not currently exist on the landscape. With growing interest in ecological restoration and finite resources, decision-makers need tools that help them evaluate tradeoffs and identify locations where restoration actions are most likely to succeed.
To address this need, the project team developed a spatially explicit modeling framework that integrates land-use history, species distribution data, and economic costs to identify priority areas for ecological restoration. The approach directly accounts for both ecological benefits and financial constraints, allowing users to explore alternative restoration scenarios. The framework is demonstrated through a case study on highly threatened grassland ecosystems in the Great Plains region of Kansas, USA.
The modeling framework is designed to be flexible and adaptable. It can be altered for future analyses of different ecosystems, species, and conservation priorities, as well as alternative restoration goals. By providing a data-driven approach to restoration planning, this project offers a decision-support tool that can help practitioners optimize restoration site selection and allocate limited resources more strategically.
- Source: USGS Sciencebase (id: 68d3fc51d4be023091a47f5e)