دانلود رایگان مقاله الزویر درباره ارتباط بین شاخص سطح برگ و خرد اقليم در جنگل های استوایی و مزرعه خرمای روغنی: اختلال در جنگل باعث تغییراتی در خرد اقليم می شود (کلیک کنید)
توضیحات :
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مشخصات این مقاله :
عنوان مقاله :
The relationship between leaf area index and microclimate in tropicalforest and oil palm plantation: Forest disturbance drives changes inmicroclimate
ترجمه فارسی عنوان :
ارتباط بین شاخص سطح برگ و خرد اقليم در جنگل های استوایی و مزرعه خرمای روغنی: اختلال جنگل باعث تغییراتی در خرد اقليم می شود
سال انتشار : 2015
متعلق به مجله یا ژورنال : هواشناسی کشاورزی و جنگل (Agricultural and Forest Meteorology)
فرمت: PDF
تعداد صفحات: 9
شماره پروژه: 5007
کلمات کلیدی :
Microclimate, Leaf area index, Land use change, Tropical forest, Disturbance, Oil palma
خرد اقليم، شاخص سطح برگ، تغییر کاربری اراضی، جنگل های استوایی، اختلال، خرمای روغنی
چکیده :
Abstract
Land use change is a major threat to biodiversity. One mechanism by which land use change influences biodiversity and ecological processes is through changes in the local climate. Here, the relationships between leaf area index and five climate variables – air temperature, relative humidity, vapour pressure deficit, specific humidity and soil temperature – are investigated across a range of land use types in Borneo, including primary tropical forest, logged forest and oil palm plantation. Strong correlations withthe leaf area index are found for the mean daily maximum air and soil temperatures, the mean dailymaximum vapour pressure deficit and the mean daily minimum relative humidity. Air beneath canopies with high leaf area index is cooler and has higher relative humidity during the day. Forest microclimateis also found to be less variable for sites with higher leaf area indices. Primary forest is found to be up to2.5◦C cooler than logged forest and up to 6.5◦C cooler than oil palm plantations. Our results indicate thatleaf area index is a useful parameter for predicting the effects of vegetation upon microclimate, whichcould be used to make small scale climate predictions based on remotely sensed data.
مقدمه این مقاله :
Introduction
IntroductionMicroclimate influences a wide range of important ecologicalprocesses, such as plant growth and soil nutrient cycling (Bonan,2008). Species can exploit fine-scale variations in climate (Suggittet al., 2012) and models that incorporate these microclimatic vari-ations are better at predicting population dynamics (Bennie et al.,2013). However, outputs from global and regional climate mod-els generally have horizontal resolutions of 10–100 km, althoughhigher resolution climate projections are becoming available (Plattset al., 2014). This mismatch between what influences organismsand what can be measured could potentially lead to inaccuracieswhen considering the ecological impacts of a changing climate.This is especially important in the habitat-heterogeneous tropi-cal zone, where climate change effects may be felt earlier and where the impacts on biodiversity are likely to be large (Deutschet al., 2008; Tewksbury et al., 2008). Fine-scale heterogeneity in thefuture climate may provide microrefugia of tolerable climate thatwill help species to persist (Noss, 2001). Conversely, heterogeneityin present-day microclimate that is unaccounted for in models maymean that species have greater climatic tolerances than is currentlythought (Logan et al., 2013).Variability in climate on the micro-scale is driven by topogra-phy and vegetation cover. Topographical climate variations includeeffects due to elevation, cold air drainage, wind exposure, slope andaspect (Dobrowski, 2010). These physical processes are relativelywell understood; however, running regional climate models at highenough resolutions to accurately simulate these effects is computa-tionally expensive. Vegetation has long been known to modify theclimate near the ground (Geiger, 1950). Recent work has shown thatclimate differences between different habitats can be on the samescale or larger than those projected to occur under climate change(Suggitt et al., 2011) and that canopy cover has a strong influenceupon extreme climate conditions (Ashcroft and Gollan, 2012).
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