Utilizing niche overlap to improve predictive modeling in biological control strategies

Invasive species significantly impact ecosystems and economies. Classical biological control (CBC) provides a sustainable alternative by utilizing natural enemies to manage invasive populations. However, the variable success of CBC highlights the necessity for more predictive and systematic approaches. This study investigates the potential of niche overlap between invasive species and their biocontrol agents (BCAs) as a predictor of biocontrol efficacy, hypothesizing that greater overlap correlates with increased success.

Our research examines environmental factors influencing niche overlap, including temperature, precipitation, soil conditions, and anthropogenic activities. We assess the degree of niche overlap to pinpoint regions where BCAs could successfully establish and control target pests. The methodology integrates data collection on species occurrences and environmental variables into a raster stack, with principal component analysis (PCA) identifying critical factors. Ecological niche modeling is performed using EcoSpat package in R studio, calibrated to enhance prediction accuracy. Predictive mapping delineates areas suitable for both invasive species and BCAs, and background similarity tests assess ecological similarities between the native and invasive ranges.

Preliminary findings support the hypothesis that higher niche overlap leads to better biocontrol outcomes. This evidence suggests that integrating ecological principles and predictive modeling can substantially improve the predictability and effectiveness of biocontrol strategies, reducing reliance on chemical pesticides and enhancing ecological stability. Our results underscore the importance of understanding niche dynamics in biocontrol efficacy and offer valuable insights for developing more effective strategies.