scholarly journals Environmental and anthropogenic factors influencing key cabbage Lepidopteran pests in the southwestern Siberia

Author(s):  
Irina V. Andreeva ◽  
◽  
Elena I. Shatalova ◽  
Margarita V. Shternshis ◽  
◽  
...  
2015 ◽  
Vol 8 (1) ◽  
pp. 309-317 ◽  
Author(s):  
Xing Liting ◽  
Zhou Juan ◽  
Zhang Fengjuan ◽  
Wang Song ◽  
Dou Tongwen ◽  
...  

In karst regions, due to the heterogeneous features of karst medium, the characteristics of the groundwater flow turn to be of high complexity. Researchers have been seeking proper forecasting methods for karst water dynamic for many years. This paper, taking the spring in Jinan as an example, using regression analysis, analyzed the factors influencing spring water dynamic, and quantitatively evaluated the influencing coefficients of spring water level concerning rainfall, exploitation and recharge as well as the natural decay coefficient of spring water in dry seasons. The prediction model coupling multiple factors was built by investigating natural and anthropogenic factors influencing groundwater level, which could be used for forecasting dynamic of spring water in Jinan. The calculated value of model was highly coincided with the observed value. In consideration of the characteristics of uneven precipitation in Jinan, the suitable zones and volume of artificial recharge were investigated finally, which could help to sustain the spewing of Jinan springs significantly.


2007 ◽  
Vol 31 (2) ◽  
pp. 73-84 ◽  
Author(s):  
Kimberley D. Brosofske ◽  
David T. Cleland ◽  
Sari C. Saunders

Abstract Understanding relative influences of ecological and anthropogenic factors on wildfire occurrence can assist decisionmakers in allocating fire management resources. We examined the influences of ecological and anthropogenic variables on probability of modern fire occurrence in the Mark Twain National Forest (MTNF), Missouri, using classification and regression tree (CART) and logistic regression analyses. Models were developed for five classes of fire size. Although CART distinguished some effects of fire size on results, logistic regression indicated a single model developed for all fires was sufficient for predictions. Ecological subsection was a dominating influence on fire occurrence for final CART and logistic models, highlighting the potential usefulness of ecosystem classification as a framework for considering factors influencing modern wildfires. Other influential predictors included ecosystem fire resistance; distance to roads, cities, and railroads; road density; mean October precipitation; elevation; median house value; and population density. Wildfires in the MTNF are caused overwhelmingly by arson, which, when combined with our results, suggests that arsonists may seek out flammable fuel types in remote areas with easy access. Within this general anthropogenic fire regime, we found a more subordinate effect of specific human variables (e.g., population density) on modern fire occurrence than did similar studies in the Upper Midwest, perhaps because our study area encompassed primarily federal forestlands with low population density.


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