Spatial weed distribution models under climate change: a short review.

Area of Science:

• Ecology
• Agronomy
• Environmental Science

Background:

• Climate change poses significant risks to global agriculture, necessitating enhanced efficiency.
• Increasing human populations and global trade/tourism drive the introduction and spread of invasive weed species.
• Species distribution models (SDMs) are increasingly utilized to understand weed behavior under changing climatic conditions.

Approach:

• A systematic review of 59 articles published since 2017 focusing on modeled weeds and climate change.
• Analysis of study characteristics including species, scale, location, algorithms (MaxEnt), validation (AUC), scenarios, variables, and data sources.
• Evaluation of the distribution of research between developed and developing countries.

Key Points:

• Maximum entropy (MaxEnt) and area under the curve (AUC) were the most common modeling software and validation methods.
• Environmental and topographic variables were prioritized over pedological and anthropogenic factors in the reviewed studies.
• Europe was the most studied continent, with China, the USA, and India being the most frequently studied countries.

Conclusions:

• The current body of research on weed species distribution modeling in response to climate change is unbalanced, favoring developed countries.
• Knowledge gaps persist, particularly in developing countries with high population densities, hindering effective weed management.
• Further research is crucial to improve understanding and develop strategies for managing weed challenges exacerbated by climate change.