摘要
Background:Anthropogenic disturbances are increasingly affecting the vitality of tropical dry forests.The future condition of this important biome will depend on its capability to resist and recover from these disturbances.So far,the temporal stability of dryland forests is rarely studied,even though identifying the important factors associated with the stability of the dryland forests could serve as a basis for forest management and restoration.Methodology:In a degraded dry Afromontane forest in northern Ethiopia,we explored remote sensing derived indicators of forest stability,using MODIS satellite derived NDVI time series from 2001 to 2018.Resilience and resistance were measured using the anomalies(remainders)after time series decomposition into seasonality,trend and remainder components.Growth stability was calculated using the integral of the undecomposed NDVI data.These NDVI derived stability indicators were then related to environmental factors of climate,topography,soil,tree species diversity,and local human disturbance,obtained from a systematic grid of field inventory plots,using boosted regression trees in R.Results:Resilience and resistance were adequately predicted by these factors with an R^(2) of 0.67 and 0.48,respectively,but the model for growth stability was weaker.Precipitation of the wettest month,distance from settlements and slope were the most important factors associated with resilience,explaining 51%of the effect.Altitude,temperature seasonality and humus accumulation were the significant factors associated with the resistance of the forest,explaining 61%of the overall effect.A positive effect of tree diversity on resilience was also important,except that the impact of species evenness declined above a threshold value of 0.70,indicating that perfect evenness reduced the resilience of the forest.Precipitation of the wettest month was the most important factor explaining 43.52%of the growth stability variation.Conclusion:A combination of climate,topographic factors and local human disturban
基金
PhD IRO grant from KU Leuven and We Forest Ethiopia supported the data collection.It is one of the chapters of a PhD research and there is no specific ID attached to the funds。
