Predicting potential suitable habitat of by integrating parasitic constraints and land use data into MaxEnt modeling.

INTRODUCTION

Understanding the impacts of climate change and land use dynamics on parasitic plants is crucial for ecological restoration and sustainable resource management in arid regions. This study proposes a two-dimensional modeling framework that integrates parasitic constraints and land use dynamics to predict the potential suitable habitat of , a medicinal plant obligately parasitic on Haloxylon ammodendron.

METHODS

Using an optimized MaxEnt model, host suitability probability was incorporated as a continuous probabilistic constraint, and high-resolution land use data were coupled to enhance ecological realism. The framework was applied to assess habitat suitability under current (1970-2000) and future climate scenarios (2050s, 2070s, 2090s, SSP126, SSP370, SSP585).

RESULTS

The inclusion of parasitic constraints reduced the suitable habitat area by 4.5% (from 138.20 × 104 km² to 131.92 × 104 km²) and exacerbated habitat fragmentation, particularly in Northwest China. Future projections reveal a decrease in the total suitable habitat area but an increase in the area of highly suitable regions, with the centroid shifting towards the northwest. Land use analysis demonstrated that unused land (70.21%) and grassland (13.81%) constitute the primary habitats, highlighting their significance for sustainable cultivation. Key environmental drivers identified include July precipitation, soil pH, and temperature of the warmest quarter. The model exhibited high predictive accuracy (AUC: 0.947-0.949).

DISCUSSION

The framework provides a reliable tool for assessing host-parasite interactions and land use impacts. These findings offer valuable insights for adaptive management strategies that balance ecological restoration and the sustainability of medicinal resources in arid ecosystems.