Zhixiang Zhou

Spatial variability of soil organic carbon in Three Gorges Reservoir area, China

Soil organic carbon (SOC) is an important component of the global carbon pool. It is a critical indicator of soil quality. We studied SOC content (SOCC) and SOC density (SOCD) of the Three Gorges Reservoir (TGR) area in China. Soil samples from 306 sites across the study area were assessed for SOCC, SOCD and bulk density. Total SOC stocks in the TGR area were estimated at 5.82×10-1Pg. We examined relationships between SOCC and SOCD, and the environmental and land-use/land-cover (LULC) variables. The plow layer (0-0.3m) had a significantly higher mean SOCC (20.6gkg-1) than the subsoil layer (16.5gkg-1); elevation, LULC, soil type and soil thickness were the most influential factors affecting SOCC in the plow layer. In the subsoil layer, elevation and soil thickness were dominant in determining SOCC and SOCD. To study the spatial variability of SOC, we used statistical modeling and GIS-based techniques to map the distribution of SOCC and SOCD of the study area. Both SOCC and SOCD in the plow layer showed patchy distribution and were positively correlated with elevation and vegetation coverage. Spatial variability of SOCD in the subsoil layer showed a gradual transition between LULC categories. The lower SOCC of farmland appeared to be related to the repeated removal of agricultural produce from the land. Preservation of permanent vegetation cover and changing of the traditional farming practices will help to improve SOC stock and increase soil productivity in the TGR area.

Responses of landscape metrics to altering grain size in the Three Gorges Reservoir landscape in China

Quantifying the response of landscape metrics to an altering observation scale is crucial to understanding environmental changes and managing ecosystem services. Whereas the scaling behaviors of landscape metrics in spatial heterogeneity analysis have been well identified by previous research, there remains a need to examine these effects in areas undergoing rapid change. Here, we aim to reveal the landscape scale effect in the Three Gorges Reservoir (TGR) area, China, using a case study on Zigui County. We applied a suite of common landscape metrics (12 indices at the class level and 17 indices at the landscape level) to characterize the landscape pattern and examine the response of the metrics to altering grain size using a series of land-use/land-cover data with gradient resolutions. The results reveal that significant scale effects exist in most pattern metrics in the TGR landscape. In addition, the different responses to the altering grain size occurred with different landscape metrics and various land-use/land-cover types. With respect to changing grain size, all of the selected pattern metrics at the landscape level displayed high or medium sensitivity in response to changing grain size except the Fractal Dimension Index and the landscape-diversity indices. The behavior of the metrics in response to altering grain size can be grouped into four types (Type 1, Type 2, Type 3, and Type 4). The class-level metrics with high sensitivity were Mean Patch Size, the Contiguity Index, the Euclidean Nearest-Neighbor Distance, the Perimeter-Area Ratio, and Patch Density for all land-use/land-cover types, whereas low sensitivities were detected in the response of the Fractal Dimension Index and the Largest Patch Index. Based on the response to the altering resolution of input data, the class-level metrics could be grouped into three types (Type a, Type b, and Type c). Considering the scaling behavior of landscape metrics, we suggest using a set of suitable remote-sensing images to quantify the landscape pattern in the TGR landscape and similar areas.

How is biodiversity changing in response to ecological restoration in terrestrial ecosystems? A meta-analysis in China

Biodiversity is an important ecosystem characteristic, and is vital for maintaining ecosystem health and stability. However, biodiversity was often ignored in previous Chinese restoration planning and design due to its complex roles and the unclear mechanisms in providing human well-being. In order to evaluate the response of biodiversity to ecological restoration in terrestrial ecosystems, we assembled biodiversity in different metrics and different organisms and generated a large dataset comprised 2099 observations from 103 published studies to conduct a meta-analysis in China. Our results revealed that the biodiversity of restored ecosystem increased by 43% compared with degraded state, but it was difficult to recover to the natural level across the whole China. The gap between restored and natural ecosystems was about 13%. Ecological restorations have contributed not only to increasing vegetation coverage but also to improving soil environment and habitat quality. The recovery levels of vascular plant, soil microorganism and soil invertebrate were 30%, 73% and 48%, respectively. Biodiversity recovery would be better reflected in enhancing the structure feature (65%) such as plant height and density rather than the diversity feature (18%) such as diversity indices of Shannon and Simpson. Moreover, the response of biodiversity to ecological restoration varied with restoration actions (i.e., initial land use/cover type, restoration approach and restoration age), and the interaction effects among restoration actions significantly impacted biodiversity recovery. Passive approach performed better than active approach for biodiversity recovery. Meanwhile, the magnitude and direction of the impact of ecological restoration on biodiversity greatly altered with environmental conditions (i.e., climate condition and altitude). Our findings could facilitate priority setting and selection of treatment methods for biodiversity recovery during ecological restoration planning and assessment to ensure high effectiveness and sustainability.

Effects of mixed leaf litter from predominant afforestation tree species on decomposition rates in the Three Gorges Reservoir, China

To determine whether mixed plantations can improve nutrient cycling and to elucidate the mechanisms of such effects, a field litterbag experiment with seven treatments involving Pinus massoniana (P.), Cupressus funebris (C.) and Quercus variabilis (Q.) litter in equal mass proportions (pure litter; pairwise combinations; and the combination of all three species) was conducted in a Pinus massoniana plantation in the region of the Three Gorges Reservoir, China. We measured mass loss and the release of C, N and P from the litter treatments and assessed the effects of mixing litter in each sampling phase and for various decomposition periods. At the end of the study, the mass loss and release of C, N and P among the treatments relative to their initial contents ranged from 47.6% to 62.8%, 59.5% to 75.2%, 63.5% to 78.2% and 58.9% to 72.6%, respectively. Primary mass loss and nutrient release occurred during a phase with high temperatures and precipitation, and decomposition was closely correlated with the initial lignin/N ratio and N concentration. Compared with the decay values of Quercus litter, mixing litter increased N release by 1.2% for the P. + Q. and C. + Q. combinations and increased P release by 3.0-6.3% for the three litter mixture combinations. Additionally, the P. + Q. and C. + Q. two-species mixtures exhibited greater decay than the three-species mixture. Mixing the two coniferous species (P. + C.) also increased decomposition. Furthermore, positive nonadditive mass loss occurred after incubation for 240 d, and mixing effects on the nonadditive release of C, N and P occurred immediately in 60 d incubations in all treatments. In conclusion, mixing these three species or two of species can improve material cycling in plantations, and Quercus appears to be a priority candidate for mixed planting with Pinus and/or Cupressus.

Geotechnology-Based Modeling to Optimize Conservation of Forest Network in Urban Area

Forest network development in urban areas faces the challenge from forest fragmentation, human-induced disturbances, and scarce land resources. Here, we proposed a geotechnology-based modeling to optimize conservation of forest network by a case study of Wuhan, China. The potential forest network and their priorities were assessed using an improved least-cost path model and potential utilization efficiency estimation. The modeling process consists of four steps: (i) developing species assemblages, (ii) identifying core forest patches, (iii) identifying potential linkages among core forest patches, and (iv) demarcating forest networks. As a result, three species assemblages, including mammals, pheasants, and other birds, were identified as the conservation targets of urban forest network (UFN) in Wuhan, China. Based on the geotechnology-based model, a forest network proposal was proposed to fulfill the connectivity requirements of selected species assemblages. The proposal consists of seven forest networks at three levels of connectivity, named ideal networks, backbone networks, and comprehensive network. The action priorities of UFN plans were suggested to optimize forest network in the study area. Additionally, a total of 45 forest patches with important conservation significance were identified as prioritized stepping-stone patches in the forest network development. Urban forest conserve was also suggested for preserving woodlands with priority conservation significance. The presented geotechnology-based modeling is fit for planning and optimizing UFNs, because of the inclusion of the stepping-stone effects, human-induced pressures, and priorities. The framework can also be applied to other areas after a sensitivity test of the model and the modification of the parameters to fit the local environment.