پیش بینی تغییرات در توزیع گیاهان بزرگ تحت تغییرات اقلیمی و مدیریت با استفاده از یک مدل اکوسیستم صریح مکانی

Wildlife managers use a variety of interventions to alter species distributions but it is uncertain how effective these techniques will be under shifting climate. There is growing recognition of the importance of including climate change scenarios into management planning and actions, but this is lacking in many systems. The spatially-explicit ecosystem model, SAVANNA, was used to predict shifts in large herbivore distribution from 2020 to 2079 under scenarios of climate change, water management, and elephant population growth in Kruger National Park, South Africa. Directional persistence was used to indicate where five large herbivore species – elephant (Loxodonta africana), buffalo (Syncerus caffer), impala (Aepyceros melampus), wildebeest (Connochaetes taurinus), and zebra (Equus quagga) – were predicted to increase or decrease their density relative to historic conditions. The overlap in herbivore distributions both within and between species was measured to indicate which change agents were likely to influence future distributions as well as when those influences are expected to occur. We found that patterns differed across climate scenarios. Altering artificial water availability had a mixed overall effect on the persistence of herbivore densities across the park, but strongly influenced the overlap in both within- and between-species distributions. Elephant numbers generally only had an influence under the most extreme case of population growth. While management actions at the scale of large protected areas or regions may not be able to directly alter climate outcomes, they have the potential to mitigate other stressors, increasing the opportunity for species and ecosystems to adapt to uncertain climate effects. Simulation studies of future conditions under interacting climate and management, such as presented here, have important potential to inform decision making, but do not remove the need for continued monitoring and adaptive management.