Evaluating predictive performance of statistical models explaining wild bee abundance in a mass-flowering crop
Evaluating predictive performance of statistical models explaining wild bee abundance in a mass-flowering crop
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DOI：
10.1111/ecog.05308
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发表时间：
2021-01-19
期刊：
影响因子：
5.9
通讯作者：
Clough, Yann
中科院分区：
文献类型：
--
作者：
Blasi, Maria;Bartomeus, Ignasi;Clough, Yann
野生蜜蜂种群受到世界许多地区当前农业做法的威胁，这可能会使授粉服务和作物产量面临风险。授粉服务的损失可以通过将蜜蜂丰度与小规模土地利用联系起来的模型来预测，但对这些统计模型在时间和空间上的可转移程度知之甚少。本研究评估了野生蜜蜂丰度模型在大规模开花作物跨空间（从一个区域到另一个区域）和跨时间（从一年到另一年）的可转移性。这些模型使用了关于冬季油菜田中大黄蜂和孤蜂丰度的现有数据，以及高分辨率土地使用作物覆盖和半自然栖息地数据，这些数据来自四个国家（瑞典，德国，荷兰和英国）五个不同地区在三个不同年份（2011年，2012年，2013年）进行的研究。我们开发了一个分层模型，结合所有的研究和评估的可转移性，使用交叉验证。我们发现，大量开花作物的大规模覆盖和永久性半自然栖息地，包括草原和森林，是所有地区野生蜜蜂丰富的重要驱动因素。然而，虽然增加大量开花作物对传粉者密度的负面影响在研究之间是一致的，但半自然栖息地的影响方向在研究之间是可变的。这些统计模型的可移植性有限，特别是在区域之间，但在时间上也是如此。我们的研究表明，使用统计模型结合广泛使用的土地利用作物覆盖类来推断跨年份和地区的传粉者密度的局限性，可能部分是因为输入变量，如半自然栖息地的覆盖，很难捕捉到地区和年份之间传粉者资源的变化。
Wild bee populations are threatened by current agricultural practices in many parts of the world, which may put pollination services and crop yields at risk. Loss of pollination services can potentially be predicted by models that link bee abundances with landscape-scale land-use, but there is little knowledge on the degree to which these statistical models are transferable across time and space. This study assesses the transferability of models for wild bee abundance in a mass-flowering crop across space (from one region to another) and across time (from one year to another). The models used existing data on bumblebee and solitary bee abundance in winter oilseed rape fields, together with high-resolution land-use crop-cover and semi-natural habitats data, from studies conducted in five different regions located in four countries (Sweden, Germany, Netherlands and the UK), in three different years (2011, 2012, 2013). We developed a hierarchical model combining all studies and evaluated the transferability using cross-validation. We found that both the landscape-scale cover of mass-flowering crops and permanent semi-natural habitats, including grasslands and forests, are important drivers of wild bee abundance in all regions. However, while the negative effect of increasing mass-flowering crops on the density of the pollinators is consistent between studies, the direction of the effect of semi-natural habitat is variable between studies. The transferability of these statistical models is limited, especially across regions, but also across time. Our study demonstrates the limits of using statistical models in conjunction with widely available land-use crop-cover classes for extrapolating pollinator density across years and regions, likely in part because input variables such as cover of semi-natural habitats poorly capture variability in pollinator resources between regions and years.