Search Results (9)

The lower reaches of the Jinsha River, serving as a vital ecological barrier in southwestern China and playing a crucial role in advancing targeted poverty alleviation efforts, remain underexplored in terms of the coupling between ecological and economic development, creating a gap in understanding the region’s sustainable development potential. This study combines the remote sensing ecological index (RSEI) derived from MODIS data and the biodiversity richness index (BRI) based on land use data to create the ecological environment index (EEI) using a weighted approach. It also develops the economic development index (EDI) from economic data using the entropy weight method. By integrating the EEI and EDI, the study calculates key metrics, including the ecological–economic coupling degree (EECD), coupling coordination degree (EECCD), and relative development degree (EERDD), and examines their spatiotemporal changes from 2000 to 2020. Additionally, the study applies a geographic detector model to identify the spatial drivers of the EEI, an obstacle factor diagnosis model to pinpoint the main barriers to EDI, and a neural network model to uncover the underlying forces shaping EECCD. The results indicate that: (I) From 2000 to 2020, the overall improvement rate of the ecological and economic subsystems was greater than that of the ecological–economic coupling system. The entire region is still in the Running-In Stage, and the coordination level has been upgraded from near imbalance to marginal coordination. About 85% of the counties’ EERDDs are still in the EDI Behind EEI Stage. (II) The structural composition of the EEI shows a pattern of low Dry Hot Valley Area and high in other areas, mainly driven by natural factors, although human activities had a notable impact on these interactions. (III) Originating from an impact model primarily driven by economic factors and supplemented by ecological factors, both EDI and EECCD exhibit a pattern of high in the south and low in the north, with improvements spreading northward from the urban area of Kunming. The development gradient differences between 24 poverty-stricken counties and 16 non-poverty-stricken counties have been reduced. (IV) For the six types of ecological–economic coupling development zones, it is essential to adopt localized approaches tailored to the differences in resource and environmental characteristics and development stages. Key efforts should focus on enhancing ecological protection and restoration, increasing financial support, implementing ecological compensation mechanisms, and promoting innovative models for sustainable development. Full article

Non-photosynthetic vegetation (NPV) significantly impacts ecosystem degradation, drought, and wildfire risk due to its flammable and persistent litter. Yet, the accurate estimation of NPV in heterogeneous landscapes, such as dry–hot valleys, has been limited. This study utilized multi-source time-series remote sensing data from Sentinel-2 and GF-2, along with field surveys, to develop an NDVI-DFI ternary linear mixed model for quantifying NPV coverage (f_NPV) in a typical dry–hot valley region in 2023. The results indicated the following: (1) The NDVI-DFI ternary linear mixed model effectively estimates photosynthetic vegetation coverage (f_PV) and f_NPV, aligning well with the conceptual framework and meeting key assumptions, demonstrating its applicability and reliability. (2) The RGB color composite image derived using the minimum inclusion endmember feature method (MVE) exhibited darker tones, suggesting that MVE tends to overestimate the vegetation fraction when distinguishing vegetation types from bare soil. On the other hand, the pure pixel index (PPI) method showed higher accuracy in estimation due to its higher spectral purity and better recognition of endmembers, making it more suitable for studying dry–hot valley areas. (3) Estimates based on the NDVI-DFI ternary linear mixed model revealed significant seasonal shifts between PV and NPV, especially in valleys and lowlands. From the rainy to the dry season, the proportion of NPV increased from 23.37% to 35.52%, covering an additional 502.96 km². In summary, these findings underscore the substantial seasonal variations in f_PV and f_NPV, particularly in low-altitude regions along the valley, highlighting the dynamic nature of vegetation in dry–hot environments. Full article

Yuanjiang dry–hot valley is located in the southwest of mainland China. It is a sparsely vegetated area with a fragile arid ecosystem. Although the valley previously had forest cover, it has become a tropical montane savannah in recent decades. Mechanisms controlling plant species distribution in such dry–hot valleys are unclear. Clarifying this will be beneficial to sustainable ecosystem management in dry–hot valleys. This study explored the relationship between diversity patterns of plant species and their environments in the lowland of this dry–hot valley. To achieve this, transects and plots were arranged along the river channel. Alpha and beta diversity indices were calculated to quantify biodiversity changes between species and environments. Estimated species, rarity, and abundance indices were also utilized to examine the correlation among species, their population size, and their environment: Species_estimated (expected number of species in t pooled plots), Singletons (the number of species with only one individual in t pooled plots), Uniques (the number of species living in one plot in t pooled plots), ACE (species richness estimator with coverage-based abundance), ICE (species richness estimator with coverage-based incidence), and Chao2 (species richness estimator extrapolated from Singletons). Fifty years of meteorological records, including temperature and precipitation, were utilized as climate variables. The results indicated the following findings: (1) alpha diversity was higher closer to the river, whereas the beta diversity was higher towards the lower sections of the river (Bray–Curtis < 0.5), but this trend was reversed in the perpendicular transects; (2) total phosphorous (TP) and total potassium (TK) were higher on flatter ground, tending to be associated with raised nitrogen (TN) and organic matter (OM); (3) soil nutrients were higher towards the lower sections of the river, corresponding to an increased number of species; (4) water supply determined plant distribution, with soil condition determining water retention; (5) the estimated species and their rarity and abundance indices were associated with proximity to the river, indicating heterogeneity of habitats and soil condition; and (6) fern species could be used as indicators representing the xeric environment of Yuanjiang dry–hot valley. Plant cover was reduced at low altitudes, with high temperatures and a low water supply. These results draw attention to the need for specific policy formation to protect the microhabitats and manage the environment of the Yuanjiang valley. Full article

A plant species can have diverse hydraulic strategies to adapt to different environments. However, the water transport divergence of co-occurring species in contrasting habitats remains poorly studied but is important for understanding their ecophysiology adaptation to their environments. Here, we investigated whole-branch, stem and leaf water transport strategies and associated morphology traits of 11 co-occurring plant species in Yuanjiang valley-type savanna (YJ) with dry–hot habitats and Xishuangbanna tropical seasonal rainforest (XSBN) with wet–hot habits and tested the hypothesis that plants in YJ have a lower water transport efficiency than co-occurring species in XSBN. We found high variation in whole-branch, stem and leaf hydraulic conductance (K_shoot; K_stem and K_leaf) between YJ and XSBN, and that K_stem was significantly higher than K_leaf in these two sites (K_stem/K_leaf: 16.77 in YJ and 6.72 in XSBN). These plants in YJ with significantly lower K_shoot and K_leaf but higher sapwood density (WD) and leaf mass per area (LMA) showed a lower water transport efficiency regarding less water loss and the adaptation to the dry–hot habitat compared to co-occurring species in XSBN. In contrast, these co-occurring plants in XSBN with higher K_shoot and K_leaf but lower WD and LMA tended to maximize water transport efficiency and thus growth potential in the wet–hot habitat. Our findings suggest that these co-occurring species employ divergent hydraulic efficiency across YJ and XSBN so that they can benefit from the contrasting hydraulic strategies in adaptation to their respective habitats. Full article

Southwest China’s arid river valleys represent ecologically vulnerable areas with intense human activity. Understanding the historical changes in LULC and land cover and projecting the impacts of various development scenarios on future LULC have become crucial for regional spatial information management and territorial spatial planning. This research analyzes the land-use changes in the Yuanmou dry-hot valley over a 30-year span from 1990 to 2020. Building upon the PLUS model, we established a coupled habitat quality spatial and multi-scenario land-use simulation model. Four development scenarios were proposed: natural progression, economic development, ecological conservation, and balanced development. We conducted simulations and evaluations of land-use in the Yuanmou dry-hot valley for 2030 using the PLUS mode, assessing the sustainability of future development scenarios under varying ecological constraints. During the simulation, three distinct RESI regions were employed as restricted development zones, integrating the three ecological constraints with the four simulation scenarios. We introduced a novel approach based on ecological environmental quality as the ecological constraint, providing a scientific reference for sustainable development in ecologically vulnerable areas. The results indicate that under ecological conservation scenarios with high-to-low RESI constraints, the ecological environment is superior to the other three scenarios. The results show the following: (1) From 1990 to 2020, aside from a continuous decrease in grassland area, there was an increasing trend in the areas of water bodies, forests, croplands, construction lands, and unused lands in the Yuanmou dry-hot valley. (2) By 2030, under all four development scenarios, the cropland area is expected to expand rapidly, while forested areas will decrease; grassland areas will decline under natural and economic development scenarios but show opposite trends under the other scenarios; and construction land and unused land areas will decrease under the ecological conservation and balanced development scenarios. (3) Land-use intensity analysis for the four scenarios indicated that, by 2030, unused lands in the Yuanmou dry-hot valley are more likely to be converted into water bodies, forests are more likely to be converted into croplands and grasslands, grasslands are more likely to be converted into croplands, croplands are more likely to be converted into grasslands, and construction lands are more likely to become unused lands. (4) Sustainable LULC management evaluations based on landscape indices reveal that ecological conservation and balanced development scenarios exhibit superior landscape connectivity and clustering. Thus, the balanced development scenario is the most appropriate LULC strategy for the Yuanmou dry-hot valley in the future. These findings provide scientific references for balancing ecological conservation and economic development in the arid river valleys of Southwest China. Full article

Deep learning networks might require re-training for different datasets, consuming significant manual labeling and training time. Transfer learning uses little new data and training time to enable pre-trained network segmentation in relevant scenarios (e.g., different vegetation images in rainy and dry seasons); however, existing transfer learning methods lack systematicity and controllability. So, an MTPI method (Maximum Transfer Potential Index method) was proposed to find the optimal conditions in data and feature quantity for transfer learning (MTPI conditions) in this study. The four pre-trained deep networks (Seg-Net (Semantic Segmentation Networks), FCN (Fully Convolutional Networks), Mobile net v2, and Res-Net 50 (Residual Network)) using the rainy season dataset showed that Res-Net 50 had the best accuracy with 93.58% and an WIoU (weight Intersection over Union) of 88.14%, most worthy to transfer training in vegetation segmentation. By obtaining each layer’s TPI performance (Transfer Potential Index) of the pre-trained Res-Net 50, the MTPI method results show that the 1000-TDS and 37-TP were estimated as the best training speed with the smallest dataset and a small error risk. The MTPI transfer learning results show 91.56% accuracy and 84.86% WIoU with 90% new dataset reduction and 90% iteration reduction, which is informative for deep networks in segmentation tasks between complex vegetation scenes. Full article

Identifying differences in ecophysiology between simple and compound leaves can help understand the adaptive significance of the compound leaf form and its response to climate change. However, we still know surprisingly little about differences in water and nutrient use, and photosynthetic capacity between co-occurring compound-leaved and simple-leaved tree species, especially in savanna ecosystems with dry-hot climate conditions. From July to September in 2015, we investigated 16 functional traits associated with water use, nutrients, and photosynthesis of six deciduous tree species (three simple-leaved and three compound-leaved species) coexisting in a valley-savanna in Southwest China. Our major objective was to test the variation in these functional traits between these two leaf forms. Overall, overlapping leaf mass per area (LMA), photosynthesis, as well as leaf nitrogen and phosphorus concentrations were found between these coexisting valley-savanna simple- and compound-leaved tree species. We didn’t find significant differences in water and photosynthetic nitrogen or phosphorus use efficiency between simple and compound leaves. Across these simple- and compound-leaved tree species, photosynthetic phosphorus use efficiencies were positively related to LMA and negatively correlated with phosphorus concentration per mass or area. Water use efficiency (intrinsic water use efficiency or stable carbon isotopic composition) was independent of all leaf traits. Similar ecophysiology strategies among these coexisting valley-savanna simple- and compound-leaved species suggested a convergence in ecological adaptation to the hot and dry environment. The overlap in traits related to water use, carbon assimilation, and stress tolerance (e.g., LMA) also suggests a similar response of these two leaf forms to a hotter and drier future due to the climate change. Full article

The sparse and fragile vegetation in the arid-hot valley is an important indicator of ecosystem health. Understanding the correlation between this vegetation and its environment is vital to the plant restoration. We investigated the differences of soil moisture and fertility in typical vegetation (Dodonaea viscosa and Pinus yunnanensis) under a range of elevations, slopes, and aspects in an arid-hot valley of China’s Jinsha River through field monitoring and multivariate statistical analysis. The soil moisture differed significantly between the dry and rainy seasons, and it was higher at high elevation (>1640 m) and on shade slopes at the end of the dry season. Soil fertility showed little or no variation among the elevations, but was highest at 1380 m. Dodonaea viscosa biomass increased, then decreased, with increasing elevation on the shade slopes, but decreased with increasing elevation on the sunny slopes. On the shade slopes, Pinus yunnanensis biomass was higher at low elevations (1640 m) than it was on sunny slopes, but lower at high elevation (1940 m) on the sunny slopes. We found both elevation and soil moisture were significantly positively correlated with P. yunnanensis biomass and negatively correlated with D. viscosa biomass. Thus, changes in soil moisture as a function of elevation control vegetation restoration in the arid-hot valley. Both species are adaptable indigenous plants with good social and ecological benefits, so these results will allow managers to restore the vegetation more effectively. Full article

Farmed catchments have greater temporal and spatial heterogeneity of soil moisture than natural catchments. Increased knowledge about the variation of soil moisture in farmed catchments has important implications for the adoption of appropriate tillage measures for agriculture. The purpose of this study was to determine the spatial and temporal variability of soil moisture as controlled by the environment on a farmed catchment in a typical dry-hot valley (DHV) by integrating geostatistical and redundancy analysis (RDA). We monitored soil moisture in topsoil (0–20 cm) and subsoil (20–40 cm) layers at 51 points on eight occasions from July 2012 to March 2014, and determined the environmental factors of soil particle-size distribution, soil organic matter, slope aspect, slope gradient, elevation, and a topographic wetness index (WI) modified for semiarid conditions at each point. The results showed that, under the influence of high evaporation, soil moisture in the topsoil was significantly lower than that of subsoil in the DHV. In this study, we observed a strong temporal variation of soil moisture, which was influenced by the seasonal variation of crop cover and lagged behind that of rainfall. Relatively high soil moisture levels were found on the watershed divide and hillside sites of the catchment, and lower on the valleyside sites. Different from other studies, RDA analysis indicated that the WI was not correlated with soil moisture in the DHV; instead, clay and sand levels were the dominant control factor of soil moisture in the farmed DHV. We proposed that soil erosion in the DHV could lead to such increases of sand and decreases of clay content, thus influencing soil moisture content. Soil and water conservation measures will be especially important for valleyside sites with steep slopes. Full article