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Cotton is a revenue source for cotton-producing countries; as the second-largest crop in Pakistan, it significantly contributes to its economy. Over the past few decades, cotton productivity has become unstable in Pakistan, and climate change is one of the main factors that impact cotton yield. Due to climate change, it becomes very important to understand the change trend and its impact on cotton yield at the regional level. Here, we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window. The piecewise regression was fitted to obtain the trend-shifting point of climate factors. The results show that precipitation has experienced an overall decreasing trend of −0.64 mm/yr during the study period, with opposing trends of −1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point, respectively. We found that cotton yield variability increased at a rate of 0.17%/yr, and this trend was highly correlated with the variability of climate factors. The multiple regression analysis explains that climate variability is a dominant factor and controlled 81% of the cotton production in the study area from 1990 to 2019, while it controlled 73% of the production from 1990 to 2002 and 84% from 2002 to 2019. These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level. [ABSTRACT FROM AUTHOR]

Human activities in a transborder watershed are complex under the influence of domestic policies, international relations, and global events. Understanding the forces driving human activity change is important for the development of transborder watershed. In this study, we used global historical land cover data, the hemeroby index model, and synthesized major historical events to analyze how human activity intensity changed in the Heilongjiang River (Amur River in Russia) watershed (HLRW). The results showed that there was a strong spatial heterogeneity in the variation of human activity intensity in the HLRW over the past century (1900—2016). On the Chinese side, the human activity intensity change shifted from the plain areas for agricultural reclamation to the mountainous areas for timber extraction. On the Russian side, human activity intensity changes mostly concentrated along the Trans-Siberian Railway and the Baikal-Amur Mainline. Localized variation of human activity intensity tended to respond to regional events while regionalized variation tends to reflect national policy change or broad international events. The similarities and differences between China and Russia in policies and positions in international events resulted in synchronous and asynchronous changes in human activity intensity. Meanwhile, policy shifts were often confined by the natural features of the watershed. These results reveal the historical origins and fundamental connotations of watershed development and contribute to formulating regional management policies that coordinate population, economic, social, and environmental activities. [ABSTRACT FROM AUTHOR]

The vegetation of alpine tundra in the Changbai Mountains has experienced great changes in recent decades. Narrowleaf small reed ( Deyeuxia angustifolia), a perennial herb from the birch forest zone had crossed the tree line and invaded into the alpine tundra zone. To reveal the driven mechanism of D. angustifolia invasion, there is an urgent need to figure out the effective seed distribution pattern, which could tell us where the potential risk regions are and help us to interpret the invasion process. In this study, we focus on the locations of the seeds in the soil layer and mean to characterize the effective seed distribution pattern of D. angustifolia. The relationship between the environmental variables and the effective seed distribution pattern was also assessed by redundancy analysis. Results showed that seeds of D. angustifolia spread in the alpine tundra with a considerable number (mean value of 322 per m). They were mainly distributed in the low elevation areas with no significant differences in different slope positions. Effective seed number (ESN) occurrences of D. angustifolia were different in various plant communities. Plant communities with lower canopy cover tended to have more seeds of D. angustifolia. Our research indicated reliable quantitative information on the extent to which habitats are susceptible to invasion. [ABSTRACT FROM AUTHOR]

The simulation optimization (S/O) method is widely used in the identification of groundwater contamination sources (IGCSs). However, in most cases, the IGCSs has the characteristics of many variables to be identified and a high degree of nonlinearity. When the grey wolf optimization algorithm (GWO) is used to solve the optimization model for this kind of problem, due to the relatively weak local search ability it has the disadvantage of premature convergence. To improve the GWO, the GWO and gradient descent algorithm were integrated to construct a hybrid grey wolf gradient optimization algorithm (HGWGO) with little dependence on the initial value and a strong local search ability. The HGWGO was then applied to solve the optimization model and improve the accuracy of the IGCSs results. In addition, when solving the optimization model, calling the simulation model hundreds of times will generate a large calculation load and consume a massive amount of computing time, which would seriously hinder the IGCSs. Thus, a surrogate model of the simulation model was established by applying a deep belief neural network (DBNN) to participate in the iterative calculation. The results showed that compared with the simulated annealing algorithm and GWO, the HGWGO had a higher calculation accuracy and could improve the accuracy of IGCSs. Although the HGWGO requires a high computational cost, the improvement in solution accuracy was sufficient to compensate for this shortcoming. The DBNN surrogate model had a high accuracy and could save 99% of the computing time by participating in the iterative calculation instead of the simulation model. [ABSTRACT FROM AUTHOR]

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) time series (1982-2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal (MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends (P < 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types. [ABSTRACT FROM AUTHOR]

Rapid changes in soil temperature are unequivocal under global change, especially in mid-high latitudes. Studies on the relationships between soil temperature and climate system are lacking at regional climatic scale. Here, changes in shallow soil temperature (0, 5, 10, 15, 20 cm), both in the cold temperate zone (CTZ) and the mid-temperate zone (MTZ) in Northeast China, were compared and analyzed using daily data from growing seasons (May to September) from 1964 to 2011. The influences of air temperature and precipitation on soil temperature were analyzed. The results showed that for nearly half a century, the increasing trend of surface soil temperature in the CTZ was lower than that in the MTZ, with + 0.17 and + 0.54 °C/decade, respectively. Air temperature increased faster for the MTZ than the CTZ. Precipitation increased in the CTZ but decreased in the MTZ. Since 1996, the temperature increase and precipitation decrease were more obvious in the MTZ. In summary, given the complex effects of temperature and precipitation, the response of soil temperature was more significant in the MTZ than in the CTZ. These results emphasize the importance of independently researching soil temperature of different climate zones. Susceptibility of soil temperature to global warming will advance our understanding on utilization of climatic resources in the development of agricultural production. [ABSTRACT FROM AUTHOR]

Peatlands are some of the largest carbon reservoirs in terrestrial ecosystems and play a key role in the global carbon cycle. Understanding peatland development, carbon accumulation processes, and the peatland response to varying forcing factors over different temporal and spatial scales helps reveal the underlying processes and general patterns of these ecosystems. To assess the role of climate and local conditions in peatland development, the basal samples from 23 peat cores and three well dated long peat cores were used to explore peatland initiation, lateral expansion, and carbon accumulation rate in the Baijianghe peatland located in the Changbai Mountains, Northeast China. Our results reveal that the Baijianghe peatland was initiated from forest conditions at 7.9 cal. kyr BP and then expanded laterally by paludification. The rapid expansion between 5 and 4 cal. kyr BP likely resulted from high precipitation and gentle topography. The mean carbon accumulation rates of the three long peat cores were 36.3, 39.1 and 48.4 g C m−2 yr−1, respectively, which are higher than rates from the northern peatlands. Both climate and local conditions have exerted an important influence on carbon accumulation rates in the Baijianghe peatland since the middle Holocene. The carbon accumulation patterns between 5 and 1.5 cal. kyr BP were probably linked to local conditions rather than climatic settings, including topography, hydrological conditions, and plant composition. The consistently decreasing carbon accumulation rate values at all locations within the BJH peatland over the last 1.5 cal. kyr BP suggests that climate is the primary control. This study highlights the varying primary controls on the process of peatland development and reveals the important role of local conditions in carbon accumulation. [ABSTRACT FROM AUTHOR]

The identification of groundwater contamination sources (IGCSs) is an important requirement for the remediation and treatment of groundwater contamination. The data assimilation methods such as ensemble Kalman filter (EnKF) and ensemble smoother (ES) have been applied to IGCSs in recent years and obtained good identification results. The unscented kalman filter (UKF) is also a data assimilation method with the potential to simultaneously identify hydraulic conductivity and GCSs. However, when UKF is applied to identify hydraulic conductivity and GCSs, it is necessary to use the observed data at different times separately, which increases the complexity of the update process and this may result in low identification accuracy. ES is a variant of EnKF that updates the system parameters with all observed data in all time periods, which makes ES faster and easier to implement than EnKF. Therefore, inspired by the ES, an unscented kalman smoother (UKS) based on UKF was proposed for simultaneously identifying the hydraulic conductivity and GCSs in this study. The UKS can use the data observed in all time periods simultaneously, while it is also simpler to operate and the calculation speed is faster. Present studies have shown that ES can solve IGCS problems. Thus, ES was also applied to identify the hydraulic conductivity and GCSs in this study, and its identification performance was compared with UKS. In contrast to previous applications of ES to IGCSs, both UKS and ES were set up with stop iteration conditions instead of only performing one update process, and thus both methods applied multiple update processes. The results showed that compared with ES, the identification results obtained by UKS were characterized by greater stability, higher accuracy, and the iterative process required less iteration process and computational time. [ABSTRACT FROM AUTHOR]

Accelerated tree growth in the alpine treeline ecotone (ATE) has been linked to the recent rapid climate warming. However, the role of tree age and elevation in the growth response of trees to climate change remains unclear. Here, we developed basal area increment chronologies of Betula ermanii from the closed forest belt (CFB) at lower elevation to the ATE of Changbai Mountain with three tree age classes (young: 0–60 years, middle-aged: 60–120 years, and old: > 120 years). In ATE, all age classes of B. ermanii have been experiencing dramatic growth acceleration since 1981. Young trees, with higher temperature sensitivity, exhibited the most prominent warming-induced growth enhancement relative to middle and old-aged trees. In CFB, young and middle-aged trees exhibited similar sensitivity to the temperature increase during the warm period relative to the cold period, with strikingly accelerated growth enhancement trends. In contrast, old trees did not show any significant growth trend. Moreover, young trees in ATE showed significantly (p < 0.01) higher growth rates than those in CFB, whereas middle-aged trees in ATE showed significantly (p < 0.05) lower growth rates than those in CFB. Our results reveal that the response of tree growth to climate change varies with tree age and elevation. Therefore, these factors should be considered to avoid overestimation or underestimation of tree growth trends and bias in estimating potential forest production. [ABSTRACT FROM AUTHOR]

Traditionally, patch-based analysis at the landscape scale fragmentation has been used in the study of landscape ecology while the study of boundary and node has not been considered as much detail until recently. This study investigated the possibility of applying boundary- and node-based methods in landscape pattern analysis to the upper reaches of the Minjiang River in the southwestern China. Boundary-based and node-based landscape indices were selected to be used in analyzing changes in landscape patterns, and the results were compared with analysis using traditional pattern indices. We compared the responses of patch-area-based, boundary-length-based and node-number-based indices, and concluded that boundary-based and node-based indices are more sensitive to disturbance than patch-based indices with various patterns, and node-based indices are even more sensitive than boundary-based ones. Thus, the results suggest that boundary-based and node-based pattern analysis methods provide helpful supplementary information to traditional patch-based pattern analysis methods. The results about pattern dynamics of landscapes in the upper reaches of the Minjiang River based on boundaries and nodes showed that with human disturbance, the dominance of forest landscape was weakened by other landscape types; thus the landscape pattern of the study area became more homogeneous and the boundary network became more complex. These changes further augmented disturbance interfaces in the landscape and increased the possibilities of further landscape fragmentation. [ABSTRACT FROM AUTHOR]

As one of the most sensitive regions to global climate change, alpine tundra in many places around the world has been undergoing dramatic changes in vegetation communities over the past few decades. Herbaceous plant species in the Changbai Mountains area have significantly expanded into tundra shrub communities over the past 30 yr. Soil microbial communities, enzyme activities, and soil nutrients are intertwined with this expansion process. In order to understand the responses of the soil microbial communities to such an expansion, we analyzed soil microbial community structures and enzyme activities in shrub tundra as well as areas with three different levels of herbaceous plant expansion. Our investigation was based on phospholipid fatty acid (PLFA) analysis and 96-well microtiter plates. The results showed that herbs have expanded greatly in the tundra, and they have become the dominant species in herbaceous plant expansion areas. There were differences for community composition and appearance among the shrub tundra and the mild expansion, moderate expansion, and severe expansion areas. Except for soil organic matter, soil nutrients were increased in herbaceous plant expansion areas, and the total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP) were greatest in moderate expansion areas (MOE), while soil organic matter levels were highest in the non-expanded areas (CK). The total soil PLFAs in the three levels of herbaceous plant expansion areas were significantly higher than those in the non-expanded areas, and total soil PLFAs were highest in the moderately expanded area and lowest in the severely expanded area (SEE). Bacteria increased significantly more than fungi and actinomycetes with herbaceous plant expansion. Soil hydrolase activities (β-1,4-glucosidase (βG) activity, β-1, 4-N-acetylglucosaminidase (NAG) activity, and acid phosphatase (aP) activity) were highest in MOE and lowest in the CK treatment. Soil oxidase activities (polyphenol oxidase (PPO) activities and peroxidase (PER) activities) were also highest in MOE, but they were lowest in the SEE treatment. The variations in total soil PLFAs with herbaceous plant expansion were mostly correlated with soil organic matter and available phosphorus concentrations, while soil enzyme activities were mostly correlated with the total soil nitrogen concentration. Our results suggest that herbaceous plant expansion increase the total soil PLFAs and soil enzyme activities and improved soil nutrients. However, soil microorganisms, enzyme activity, and nutrients responded differently to levels of herbaceous plant expansion. The soil conditions in mild and moderate expansion areas are more favorable than those in severe expansion areas. [ABSTRACT FROM AUTHOR]

Vegetation in high altitude areas normally exhibits the strongest response to global warming. We investigated the tundra vegetation on the Changbai Mountains and revealed the similarities and differences between the north and the southwest slopes of the Changbai Mountains in response to global warming. Our results were as follows: 1) The average temperatures in the growing season have increased from 1981 to 2015, the climate tendency rate was 0.38°C/10yr, and there was no obvious change in precipitation observed. 2) The tundra vegetation of the Changbai Mountains has changed significantly over the last 30 years. Specifically, herbaceous plants have invaded into the tundra zone, and the proportion of herbaceous plants was larger than that of shrubs. Shrub tundra was transforming into shrub-grass tundra. 3) The tundra vegetation in the north and southwest slopes of the Changbai Mountains responded differently to global warming. The southwest slope showed a significantly higher degree of invasion from herbaceous plants and exhibited greater vegetation change than the north slope. 4) The species diversity of plant communities on the tundra zone of the north slope changed unimodally with altitude, while that on the tundra zone of the southwest slope decreased monotonously with altitude. Differences in the degree of invasion from herbaceous plants resulted in differences in species diversity patterns between the north and southwest slopes. Differences in local microclimate, plant community successional stage and soil fertility resulted in differential responses of tundra vegetation to global warming. [ABSTRACT FROM AUTHOR]