Journal of Geographical Sciences - Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of... 相似文献
Journal of Geographical Sciences - Building the Belt and Road is initiatives of China to promote win-win international cooperation in the new era, aiming at green, health, intellect and peace and... 相似文献
Self-feeding device is extensively used in aquaculture farms, but for salmonids the individual feeding behavior has seldom been continuously observed. In this article, the individual self-feeding behavior of 10 rainbow trout was continuously monitored with a PIT tag record for 50 days with three replicates. The fish fell into three categories according to their feeding behavior, i.e. high triggering fish (trigger behavior more than 25% of the group, HT), low triggering fish (1%–25%, LT) and zero triggering fish (less than 1%). The results showed that in a group of 10 individual 1–2 HT fish accounted for most of the self-feeding behavior (78.19%–89.14%), which was far more than they could consume. The trigger frequency of the fish was significantly correlated with the initial body weight (P <0.01), however, no significant difference in growth rate among the HT, LT, and ZT fish was observed (P >0.05). Cosinor analysis showed that the two HT fish in the same group had similar acrophase. Though some of the HT fish could be active for 50 d, there were also HT fish decreased triggering behavior around 40 d and the high trigger status was then replaced by other fish, which was first discovered in salimonds. Interestingly, the growth of the group was not affected by the alternation triggering fish. These results provide evidence that in the self-feeding system the HT fish didn’t gain much advantage by their frequent self-feeding behavior, and high trigger status of the HT fish is not only an individual character but also driven by the demand of the group. In the self-feeding system, the critical individual should be closely monitored.
Journal of Geographical Sciences - Runoff generation is an important part of water retention service, and also plays an important role on soil and water retention. Under the background of the... 相似文献
Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone. 相似文献