Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America
Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America
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DOI：
10.1016/j.jag.2020.102110
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发表时间：
2020-07
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影响因子：
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通讯作者：
Donal S. O’Leary;D. Inouye;R. Dubayah;Chengquan Huang;G. Hurtt
中科院分区：
文献类型：
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作者：
Donal S. O’Leary;D. Inouye;R. Dubayah;Chengquan Huang;G. Hurtt
春季的到来开启了生态系统中大型营养网资源可用性的重要时期，包括放牧动物的饲料，传粉者的花朵以及依赖这些资源的更高营养级。春天的时间在空间上变化很大，受到积雪（即融雪时间，在季节性积雪的位置），气候，天气，海拔和纬度的强烈影响。当春天的时间发生沿着一个梯度（例如，春天到达后，在较高海拔的山区地形），生物体依赖于春季资源往往迁移，以保持春季资源的最佳位置-一种现象被称为“冲浪的绿色波”。虽然这种行为已经通过跟踪动物观察到，但还没有研究将绿色波量化为跨越空间和时间的运动。此外，考虑到融雪时间有中等功率，以解释绿色的时间为一个给定的位置，我们问的问题：融雪速度预测绿色波的速度？在这里，我们介绍了2001年至2016年北美融雪和绿色波速度的第一个大陆地图，这些地图来自MODIS MCD 12 Q2物候数据集。我们发现，融雪和绿色波速度的地形，包括坡度和方面的影响很大。此外，我们量化的融雪和绿色波速度之间的关系，根据三个变量：方向，速度和距离。我们的结论是，山区生态区，如北美西部科迪勒拉，有最高的对应关系之间的融雪和绿色波速度，相比平坦的地区，如大平原和苔原。这项工作将是野生动物生态学家，生物学家和土地管理者谁寻求保护迁徙动物和支持他们的生态系统的兴趣。
The timing of spring initiates an important period for resource availability for large trophic webs within ecosystems, including forage for grazing animals, flowers for pollinators, and the higher trophic levels that depend on these resources. Spring timing is highly variable across space, being influenced strongly by the departure of snow cover (i.e. snowmelt timing, in locations with a seasonal snowpack), climate, weather, elevation, and latitude. When spring timing occurs along a gradient (e.g. spring arriving later in higher elevations of mountainous terrain), the organisms that rely on spring resources often migrate to maintain an optimal position for spring resources – a phenomenon known as ‘surfing the green wave.’ While this behavior has been observed by tracking animals, there have been no studies to quantify the green wave as a movement across space and time. Furthermore, considering that snowmelt timing has moderate power to explain green-up timing for a given location, we ask the question: does snowmelt velocity predict green wave velocity? Here, we introduce the first continental maps of snowmelt and green wave velocity for North America from 2001 to 2016 as derived from the MODIS MCD12Q2 phenology dataset. We show that both snowmelt and green wave velocities are influenced strongly by topography, including slope and aspect. Furthermore, we quantify the relationships between snowmelt and green wave velocities according to three variables: direction, speed, and distance traveled. We conclude that mountainous ecoregions, such as the western North American cordillera, have the highest correspondence between snowmelt and green wave velocities, compared to flatter regions such as the Great Plains and tundra. This work will be of interest to wildlife ecologists, biologists, and land managers who seek to conserve migratory animals and the ecosystems that support them.