TY - GEN
T1 - A multi-objective optimization approach associated to climate change analysis to improve systematic conservation planning
AU - Schlottfeldt, Shana
AU - Timmis, Jon
AU - Walter, Maria Emilia
AU - Carvalho, André
AU - Simon, Lorena
AU - Loyola, Rafael
AU - Diniz-Filho, José Alexandre
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Biodiversity conservation has been since long an academic community concern, leading scientists to propose strategies to effectively meet conservation goals. In particular, Systematic Conservation Planning (SCP) aims to determine the most cost effective way of investing in conservation actions. SCP can be formalized by the Set-Covering Problem, which is NP-hard. SCP is inherently multi-objective, although it has been usually treated with a monobjective and static approach. Here, we propose a multi-objective solution for SCP, increasing its flexibility and complexity, and, at the same time, augmenting the quality of provided information, which reinforces decision-making. We used ensemble forecasting, considering future climate simulations to estimate species occurrence projected to 2080. Our method identifies sites: 1) of high priority for conservation; 2) with significant risk of investment; and, 3) that may become attractive in the future. To the best of our knowledge, this application to a real-world problem in ecology is the first attempt to apply multi-objective optimization to SCP associated to climate forecasting, in a dynamic spatial prioritization analysis for biodiversity conservation.
AB - Biodiversity conservation has been since long an academic community concern, leading scientists to propose strategies to effectively meet conservation goals. In particular, Systematic Conservation Planning (SCP) aims to determine the most cost effective way of investing in conservation actions. SCP can be formalized by the Set-Covering Problem, which is NP-hard. SCP is inherently multi-objective, although it has been usually treated with a monobjective and static approach. Here, we propose a multi-objective solution for SCP, increasing its flexibility and complexity, and, at the same time, augmenting the quality of provided information, which reinforces decision-making. We used ensemble forecasting, considering future climate simulations to estimate species occurrence projected to 2080. Our method identifies sites: 1) of high priority for conservation; 2) with significant risk of investment; and, 3) that may become attractive in the future. To the best of our knowledge, this application to a real-world problem in ecology is the first attempt to apply multi-objective optimization to SCP associated to climate forecasting, in a dynamic spatial prioritization analysis for biodiversity conservation.
KW - Biodiversity conservation
KW - Climate change
KW - Multi-objective optimization
KW - Parameter tuning
KW - Spatial conservation prioritization
KW - Systematic conservation planning
KW - Uncertainty in simulations
UR - http://www.scopus.com/inward/record.url?scp=84925339428&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-15892-1_31
DO - 10.1007/978-3-319-15892-1_31
M3 - Conference Proceeding (Non-Journal item)
AN - SCOPUS:84925339428
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 458
EP - 472
BT - Evolutionary Multi-Criterion Optimization - 8th International Conference, EMO 2015, Proceedings
A2 - Gaspar-Cunha, António
A2 - Antunes, Carlos Henggeler
A2 - Coello, Carlos A. Coello
PB - Springer Nature
T2 - 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015
Y2 - 29 March 2015 through 1 April 2015
ER -
