Rothamsted Insect Survey, Biointeractions and Crop Protection, Rothamsted Research, Harpenden, UK.
Centre for Ecology & Hydrology, Wallingford, Oxfordshire, UK.
Glob Chang Biol. 2019 Jun;25(6):1982-1994. doi: 10.1111/gcb.14592. Epub 2019 Mar 22.
Global warming has advanced the timing of biological events, potentially leading to disruption across trophic levels. The potential importance of phenological change as a driver of population trends has been suggested. To fully understand the possible impacts, there is a need to quantify the scale of these changes spatially and according to habitat type. We studied the relationship between phenological trends, space and habitat type between 1965 and 2012 using an extensive UK dataset comprising 269 aphid, bird, butterfly and moth species. We modelled phenologies using generalized additive mixed models that included covariates for geographical (latitude, longitude, altitude), temporal (year, season) and habitat terms (woodland, scrub, grassland). Model selection showed that a baseline model with geographical and temporal components explained the variation in phenologies better than either a model in which space and time interacted or a habitat model without spatial terms. This baseline model showed strongly that phenologies shifted progressively earlier over time, that increasing altitude produced later phenologies and that a strong spatial component determined phenological timings, particularly latitude. The seasonal timing of a phenological event, in terms of whether it fell in the first or second half of the year, did not result in substantially different trends for butterflies. For moths, early season phenologies advanced more rapidly than those recorded later. Whilst temporal trends across all habitats resulted in earlier phenologies over time, agricultural habitats produced significantly later phenologies than most other habitats studied, probably because of nonclimatic drivers. A model with a significant habitat-time interaction was the best-fitting model for birds, moths and butterflies, emphasizing that the rates of phenological advance also differ among habitats for these groups. Our results suggest the presence of strong spatial gradients in mean seasonal timing and nonlinear trends towards earlier seasonal timing that varies in form and rate among habitat types.
全球变暖已经提前了生物事件的时间，可能导致营养级之间的混乱。有人认为，物候变化作为种群趋势的驱动因素具有重要意义。为了充分了解可能产生的影响，需要根据空间和栖息地类型对这些变化的规模进行量化。我们利用包含 269 种蚜虫、鸟类、蝴蝶和飞蛾物种的广泛英国数据集，研究了 1965 年至 2012 年间物候趋势、空间和栖息地类型之间的关系。我们使用广义加性混合模型来模拟物候，该模型包含地理（纬度、经度、海拔）、时间（年份、季节）和栖息地（林地、灌丛、草地）的协变量。模型选择表明，具有地理和时间成分的基线模型比空间和时间相互作用的模型或没有空间项的栖息地模型更好地解释了物候的变化。该基线模型强烈表明，物候随时间逐渐提前，海拔升高导致物候延迟，空间成分决定物候时间，特别是纬度。物候事件的季节性时间（即它是否发生在一年的上半年或下半年），对于蝴蝶来说并没有导致明显不同的趋势。对于飞蛾，早期季节的物候变化比后期记录的物候变化更快。尽管所有栖息地的时间趋势都导致物候随时间提前，但农业栖息地的物候明显比其他大多数研究的栖息地晚，可能是因为非气候驱动因素。对于鸟类、飞蛾和蝴蝶，具有显著栖息地-时间相互作用的模型是最佳拟合模型，这强调了这些物种的物候提前率在不同栖息地之间也存在差异。我们的研究结果表明，存在强烈的平均季节性时间的空间梯度，以及非线性的提前季节性时间趋势，这种趋势在形式和速度上因栖息地类型而异。
