Utilization of Community Science Data to Explore Habitat Suitability of Basal Termite Genera
Utilization of Community Science Data to Explore Habitat Suitability of Basal Termite Genera
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DOI：
10.1093/isd/ixac019
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发表时间：
2022-07
影响因子：
3.4
通讯作者：
Aaron M. Goodman;Jonah J Allen;Jinna Brim;Alessa Codella;Brittney Hahn;Hassan Jojo;Zoila BondocGawa Mafla-Mills;Salka’Tuwa Bondoc Mafla;Agnes Oduro;Megan M. Wilson;J. Ware
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文献类型：
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作者：
Aaron M. Goodman;Jonah J Allen;Jinna Brim;Alessa Codella;Brittney Hahn;Hassan Jojo;Zoila BondocGawa Mafla-Mills;Salka’Tuwa Bondoc Mafla;Agnes Oduro;Megan M. Wilson;J. Ware
摘要社区科学数据库的出现，结合博物馆标本的位置信息，以指数方式增加了生态位建模（ENM）的能力和准确性。增加发生的数据提供了巨大的潜力，了解鲜为人知的或濒危物种，包括节肢动物的分布。虽然白蚁的生态位建模已经进行了入侵和有害生物物种的背景下，很少有研究已经进行了解基白蚁属的分布。利用标本记录从美国自然历史博物馆（AMNH）以及当地的数据库，我们产生了生态位模型的12个基白蚁种，属于6属，3科。我们从Worldclim 19生物气候数据集v2中提取环境数据，沿着SoilGrids数据集，并使用MaxEnt生成模型。我们选择最优模型的基础上部分接收操作特征（pROC）和遗漏率标准，并确定变量的重要性，使用排列分析。我们还计算了响应曲线，以了解适应性随环境变量变化的变化。我们的12个白蚁物种的最佳模型范围的复杂性，但没有明显的模式，属，科，或地理范围。排列分析表明，生境适宜性主要受季节或月的温度和降水量的变化。我们的研究结果不仅突出了主要基于社区科学和博物馆的数据集的有效性，而且我们的模型为预测未来在栖息地破坏和气候变化的情况下鲜为人知的节肢动物物种的丰度提供了基线。图形摘要
Abstract The advent of community-science databases in conjunction with museum specimen locality information has exponentially increased the power and accuracy of ecological niche modeling (ENM). Increased occurrence data has provided colossal potential to understand the distributions of lesser known or endangered species, including arthropods. Although niche modeling of termites has been conducted in the context of invasive and pest species, few studies have been performed to understand the distribution of basal termite genera. Using specimen records from the American Museum of Natural History (AMNH) as well as locality databases, we generated ecological niche models for 12 basal termite species belonging to six genera and three families. We extracted environmental data from the Worldclim 19 bioclimatic dataset v2, along with SoilGrids datasets and generated models using MaxEnt. We chose Optimal models based on partial Receiving Operating characteristic (pROC) and omission rate criterion and determined variable importance using permutation analysis. We also calculated response curves to understand changes in suitability with changes in environmental variables. Optimal models for our 12 termite species ranged in complexity, but no discernible pattern was noted among genera, families, or geographic range. Permutation analysis revealed that habitat suitability is affected predominantly by seasonal or monthly temperature and precipitation variation. Our findings not only highlight the efficacy of largely community-science and museum-based datasets, but our models provide a baseline for predictions of future abundance of lesser-known arthropod species in the face of habitat destruction and climate change. Graphical Abstract