Monroe Adrian P, Nauman Travis W, Aldridge Cameron L, O'Donnell Michael S, Duniway Michael C, Cade Brian S, Manier Daniel J, Anderson Patrick J
U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA.
Natural Resource Ecology Laboratory Colorado State University, in cooperation with the U.S. Geological Survey, Fort Collins Science Center Fort Collins Colorado USA.
Ecol Evol. 2022 Feb 17;12(2):e8508. doi: 10.1002/ece3.8508. eCollection 2022 Feb.
Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985-2018). We modelled recovery on former oil and gas well pads ( = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%-78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.
生态相关的参考数据对于评估生态系统恢复很有用，但当环境条件和干扰在空间和时间上存在异质性时，时间上静态的参考数据可能用处较小。对于以蒿属植物为主导的生态系统而言，这一挑战尤为严峻，因为这些群落可能需要数十年才能从干扰中恢复。我们利用三十年的遥感蒿属植物覆盖度估计数据（1985 - 2018年），展示了动态参考方法在研究蒿属植物恢复中的应用。我们对美国怀俄明州西南部的前油气井场（n = 1200）的恢复情况进行建模，相对于由干扰自动参考工具集确定的配对参考数据。我们还使用分位数回归来考虑恢复中未建模的异质性，并预测整个景观类似干扰后的恢复情况。不同分位数对天气和场地水平因素的响应往往不同，并且当配对参考地点的蒿属植物覆盖度更高时，前井场上蒿属植物的恢复增加得更多。对于低到中分位数，预计不到5%的景观会在100年内恢复，恢复通常发生在年条件凉爽湿润的较高海拔地区。相反，对于蒿属植物覆盖度的高分位数，48% - 78%的景观迅速恢复（在25年内）。我们的研究证明了在研究植被恢复时使用动态参考地点的优势，以及从分位数回归中获得的额外推断如何为管理提供信息。
