N. Ahmad, M. Ashraf, Sabeeqa Usman Malik, I. Qadir, N. A. Malik, K. Khan
{"title":"Impact of climatic and topographic factors on distribution of sub-tropical and moist temperate forests in Pakistan","authors":"N. Ahmad, M. Ashraf, Sabeeqa Usman Malik, I. Qadir, N. A. Malik, K. Khan","doi":"10.4000/geomorphologie.14564","DOIUrl":null,"url":null,"abstract":"Climatic and topographic factors control the distribution of forests across the globe. The present study investigated the impacts of these factors on spatial distribution of sub-tropical (scrub and pine) and moist temperate forests in Pakistan. The study used Digital Elevation Model (DEM), Sentinel-2 images and climatic data to quantify the impacts of climatic and topographic factors on distribution of forests. The data was statistically analyzed using correlation coefficient (R), liner regression and decision tree. Results specified six forest types during stratification. These types were significantly related to topographic (elevation) and climatic factors. Correlation coefficient (R) indicated strong positive relationship with elevation (R= 0.92) followed by annual mean temperature (R= –0.76). Similarly, annual precipitation indicated positive relation with R value of 0.53. Stepwise linear regression model showed that elevation, precipitation seasonality and annual temperature range were strongly significant with overall R2 of 0.85. Decision trees were developed to explore possible interactions of predictors to determine imperative factors. Results of decision trees of both growing methods (Chi-squared Automatic Interaction Detection (CHAID) and Classification and Regression Trees (CRT)) showed elevation was the most important factor that predicted particular forest type. Moreover, other factors such as temperature of the driest quarter, annual precipitation, precipitation seasonality and slope were identified as important factors in CRT. The present study concluded that forest types were strongly influenced by climate and topography. However, elevation was the best predictor, has significant relative importance and can be used for detailed forest stratification.","PeriodicalId":50418,"journal":{"name":"Geomorphologie-Relief Processus Environnement","volume":"9 1","pages":"157-172"},"PeriodicalIF":0.3000,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geomorphologie-Relief Processus Environnement","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.4000/geomorphologie.14564","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 2
Abstract
Climatic and topographic factors control the distribution of forests across the globe. The present study investigated the impacts of these factors on spatial distribution of sub-tropical (scrub and pine) and moist temperate forests in Pakistan. The study used Digital Elevation Model (DEM), Sentinel-2 images and climatic data to quantify the impacts of climatic and topographic factors on distribution of forests. The data was statistically analyzed using correlation coefficient (R), liner regression and decision tree. Results specified six forest types during stratification. These types were significantly related to topographic (elevation) and climatic factors. Correlation coefficient (R) indicated strong positive relationship with elevation (R= 0.92) followed by annual mean temperature (R= –0.76). Similarly, annual precipitation indicated positive relation with R value of 0.53. Stepwise linear regression model showed that elevation, precipitation seasonality and annual temperature range were strongly significant with overall R2 of 0.85. Decision trees were developed to explore possible interactions of predictors to determine imperative factors. Results of decision trees of both growing methods (Chi-squared Automatic Interaction Detection (CHAID) and Classification and Regression Trees (CRT)) showed elevation was the most important factor that predicted particular forest type. Moreover, other factors such as temperature of the driest quarter, annual precipitation, precipitation seasonality and slope were identified as important factors in CRT. The present study concluded that forest types were strongly influenced by climate and topography. However, elevation was the best predictor, has significant relative importance and can be used for detailed forest stratification.
期刊介绍:
La revue trimestrielle Géomorphologie : Relief, Processus, Environnement accueille des contributions portant sur la géomorphologie dans l’acception la plus large : formes du relief à toutes les échelles, modelés, processus de toutes natures. Elle publie des articles qui étudient les relations entre la géomorphologie et les disciplines voisines : géographie physique, géographie humaine, archéologie, écologie, sciences de la Terre et des planètes ainsi que celles qui s’intéressent à l’environnement naturel. Les études expérimentales, la modélisation, les exposés méthodologiques reçoivent le même accueil que les analyses naturalistes à partir des observations de terrain. Les mises au point thématiques sont les bienvenues, à condition d''être annoncées comme telles, tout comme les comptes rendus d''ouvrages ou les réunions scientifiques et les « tribunes libres ». Publication francophone, largement bilingue, elle est ouverte à des contributions en anglais.