Spatial-temporal Pattern and Differences of Land Use Changes in the Three Gorges Reservoir Area of China during 1975-2005

Regional land use changes are an important part of global changes.The research on land use changes in the Three Gorges Reservoir Area of China attracts a lot of attention owing to the Three Gorges Dam building.The Three Gorges Reservoir Area becomes one of the important research areas.This study analyzed the transforming processes and traits of each land use type and the regional differences of land use changes during the past 30 years,summarized the distribution of different land use types in different buffer zones and regresses the equation areas and different buffer distances based on buffer analyses and regression analyses,and then analyzed the transforming rules in different buffer distances,got the optimal influence distances.The research results indicate that,(1) cultivated land lies at the northwest of the reservoir and was decreasing,however,the construction land was increasing,especially the urban construction land,a large number of land was flooded because of the reservoir water level rise;(2) urban area was sprawling quickly in developed and neighboring areas,and a great deal of cultivated land and a considerable amount of grassland were occupied;in the earlier time,rural settlements occupied lots of cultivated land and a sum of forestry land in the later time;(3) the optimum influenced distances for cultivated land and forestry land were 10-35 km,and for urban and rural settlements were in 5-20 km.Overall,this research can reflect the spatial-temporal characteristics of land use changes during the 30 years,and it is helpful for urban planning and land use planning in the reservoir area.

Comparison of machine learning algorithms for mapping mango plantations based on Gaofen-1 imagery

Mango is a commercial crop on Hainan Island,China,that is cultivated to develop the tropical rural economy.The development of accurate and up-to-date maps of the spatial distribution of mango plantations is necessary for agricultural monitoring and decision management by the local government.Pixel-based and object-oriented image analysis methods for mapping mango plantations were compared using two machine learning algorithms(support vector machine(SVM)and Random Forest(RF))based on Chinese high-resolution Gaofen-1(GF-1)imagery in parts of Hainan Island.To assess the importance of different features on classification accuracy,a combined layer of four original bands,32 gray-level co-occurrence(GLCM)texture indices,and 10 vegetation indices were used as input features.Then five different sets of variables(5,10,20,and 30 input variables and all 46 variables)were classified with the two machine learning algorithms at object-based level.Results of the feature optimization suggested that homogeneity and variance were very important variables for distinguishing mango plantations patches.The object-based classifiers could significantly improve overall accuracy between 2–7%when compared to pixel-based classifiers.When there were 5 and 10 input variables,SVM showed higher classification accuracy than RF,and when the input variables exceeded 20,RF showed better performances.After the accuracy achieved saturation points,there were only slightly classification accuracy improvements along with the numbers of feature increases for both of SVM and RF classifiers.The results indicated that GF-1 imagery can be successfully applied to mango plantation mapping in tropical regions,which would provide a useful framework for accurate tropical agriculture land management.

Responses of incubating females to female cuckoo calls in 2 hole-nesting bird species

Acoustic signals play an important role in animal communication systems,and these signals can transfer diverse and meaningful information from a signaler to a receiver(e.g.,Yu et al.2019).Animal signals tend to be honest;however,deception can occur when it is beneficial for receivers to send dishonest signals,such as by mimicking alarm calls to steal food from other individuals(Flower et al.2014).In birds,vocal mimicry is a widespread phenomenon that has 2 major functional explanation categories:intraspecific and interspecific communications(Dalziell et al.2015).Vocal mimicry in intraspecific communication mainly involves sexual selection and social affiliation(Dalziell et al.2015).In interspecific communication,studies on vocal mimicry are mostly related to predator–prey interactions(Dalziell et al.2015).Mimics could mimic calls of predators to scare off other predators or competitors.For example,some species of hole-nesting birds produce a snakelike hissing call to drive nest predators away(e.g.,Dutour et al.2020).Receiver should be particularly sensitive to the deceptive vocals of mimics if failing to respond to an actual model sound is costly.Therefore,the mimics could derive an advantage from mimicking the calls of predators of the receivers.A recent experimental study suggested that the bubbling calls of female common cuckoo Cuculus canorus mimic those of Eurasian sparrowhawk Accipiter nisus,and they primarily serve to distract regular hosts after laying eggs(York and Davies 2017).However,Xia et al.(2019)found that female cuckoo calls have other functions,including attracting mates and repelling rivals.