Operations research applicability in spatial conservation planning.

Area of Science:

• Conservation Science
• Operations Research
• Environmental Management

Background:

• Human activities drive significant biodiversity loss, creating conflicts with societal needs.
• Protected area designation highlights the tension between ecological goals and economic interests.
• Conventional conservation planning struggles with the volume and complexity of modern data.

Purpose of the Study:

• To provide an overview of spatial conservation models supported by Operations Research (OR).
• To discuss the evolution and optimization of OR models in spatial conservation planning.
• To explore future challenges and opportunities for OR in Big Data-driven conservation.

Main Methods:

• Review of past, present, and future challenges in OR-supported spatial conservation.
• Discussion of OR model progress and optimization via algorithms and computational tools.
• Exploration of interdisciplinary collaborative platforms for Big Data conservation.

Main Results:

• Operations Research provides analytical tools to resolve conflicts between ecology and economy in conservation.
• Technological advances necessitate new OR models to handle large, diverse datasets.
• Optimized OR models and collaborative platforms can enhance cost-effective biodiversity persistence.

Conclusions:

• OR is crucial for developing sophisticated spatial conservation models.
• Integrating Big Data requires interdisciplinary collaboration and advanced computational tools.
• Expanding conservation horizons with OR enables better decision-making for biodiversity persistence in complex environments.