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从出现数据推导得出的热不匹配模型可预测青蛙体内病原体的流行情况。

Thermal mismatch models derived from occurrence data predict pathogen prevalence in frogs.

作者信息

Duncan Richard P, Scheele Ben C, Clulow Simon

机构信息

Centre for Conservation Ecology and Genomics, Institute for Applied Ecology, University of Canberra, Bruce, ACT 2617, Australia.

Fenner School of Environment and Society, Australian National University, Canberra, ACT 2601, Australia.

出版信息

Proc Natl Acad Sci U S A. 2025 Jul 29;122(30):e2423706122. doi: 10.1073/pnas.2423706122. Epub 2025 Jul 21.

Abstract

Emerging infectious diseases increasingly threaten many wildlife populations, yet the impacts of pathogens vary considerably both within and among host species. The environmental tolerance mismatch hypothesis (ETMH) suggests that this variability stems in part from differences in the relative performance of hosts and pathogens under varying environmental conditions. According to the ETMH, pathogen impacts should be more severe in environments where pathogen performance is high and host performance is low, and vice versa. However, testing the ETMH with field data is challenging due to the difficulty of measuring host and pathogen performance among locations and quantifying performance mismatches. Here, we demonstrate that a measure of thermal mismatch, based on species realized thermal niches derived from species occurrence data, can reliably predict variation in the prevalence of the amphibian fungal pathogen (Bd-chytrid fungus) within and among 42 frog host species in Australia. Specifically, we show that 1) within species, more warm-adapted host species show a steeper decline in Bd prevalence with increasing mean annual temperature, potentially reflecting greater host advantage at warmer temperatures; and 2) among host species, mean pathogen prevalence declines as the thermal affinity of hosts diverges from that of the pathogen. Our findings strongly support the ETMH and, importantly, offer a promising approach to predicting pathogen outcomes both spatially and temporally using species occurrence data. This approach enhances our understanding of variability in pathogen impacts and could inform management actions to mitigate these effects.

摘要

新发传染病对许多野生动物种群的威胁日益增加,然而病原体的影响在宿主物种内部和之间存在很大差异。环境耐受性不匹配假说(ETMH)表明,这种变异性部分源于宿主和病原体在不同环境条件下相对表现的差异。根据ETMH,在病原体表现高而宿主表现低的环境中,病原体的影响应该更严重,反之亦然。然而,由于难以在不同地点测量宿主和病原体的表现以及量化表现不匹配,用实地数据检验ETMH具有挑战性。在这里,我们证明,基于从物种出现数据得出的物种实际热生态位的热不匹配度量,可以可靠地预测澳大利亚42种蛙类宿主物种内部和之间两栖类真菌病原体(蛙壶菌)流行率的变化。具体来说,我们表明:1)在物种内部,更适应温暖环境的宿主物种随着年平均温度升高,蛙壶菌流行率下降得更陡峭,这可能反映了在温暖温度下宿主具有更大优势;2)在宿主物种之间,随着宿主与病原体的热亲和力差异增大,病原体平均流行率下降。我们的研究结果有力地支持了ETMH,重要的是,提供了一种利用物种出现数据在空间和时间上预测病原体结果的有前景的方法。这种方法增强了我们对病原体影响变异性的理解,并可为减轻这些影响的管理行动提供信息。

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