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By referring to the sustainable livelihood analysis and capability approach and taking Fuhong town in Qingbaijiang district, China, as an example, this paper classifies the livelihood assets of farm households before their residential land exit using the livelihood asset quantification method, and then analyzes the changes in their welfare after exit from residential land by adopting fuzzy comprehensive evaluation. The research results indicate that (1) the sample farm households are classified into three types, i.e., richness type, balance type, and shortage type, according to the configuration of livelihood assets, including human capital, natural capital, physical capital, financial capital, and social capital, before the exit from residential land; (2) after the exit from the residential land, the welfare of farm households has generally been improved, but the extent of such improvements varies from type to type; (3) there is a certain relationship between the configuration of livelihood assets before the exit from residential land and the welfare level after such an exit. It is suggested that importance should be attached to the heterogeneity or level of differentiation of farm households, and furthermore, measures should be taken so as to ensure that the welfare level will not be downgraded after farm households exit from their residential land.

Mountain forest ecosystems play an important role in global carbon sequestration and may respond differently to variations in climate. The timely and accurate assessment of the factors (abiotic and biotic) that affect forest types will improve our understanding of the ecological mechanisms underlying forest carbon stock and dynamics. Here, we used linear mixed effect models to assess the impact of abiotic and biotic factors on the rate of net tree C accumulation, growth, and mortality, over nearly four decades in 1248 permanent forest plots, in different forest types along an elevational gradient on the eastern Qinghai-Tibet Plateau in China. We found that the annual rise in net tree C stock ranged from 0.13 to 0.23 Mg C ha−1 yr−1, as forest growth increased from 1979 to 2017. The highest rates of growth and mortality were in coniferous broad-leaved mixed forest (CBMF), followed by deciduous broad-leaved forests (BDF), evergreen, deciduous broad-leaved mixed forest (EDBMF), and coniferous forest (CF). Mortality increased in EDBMF and CF during the study period. The most important biotic factors were tree richness and tree density, especially in BDF and CBMF. The most important abiotic factors driving these biological responses were a significant rise in monthly mean temperature (MMT) and a decline in precipitation in the growing season. The decrease in precipitation was negatively correlated with net tree C in CBMF and CF. The increase of MMT was positively correlated with growth and mortality of each forest type, and generally more important than richness and density, and overall had a positive effect on net tree C in CBMF and CF. Overall, we suggest that tree carbon stocks will continue to increase in CBMF and CF in the coming decades due to the warming.

By now, there is little research on evaluation of the tow similar candidate sites for the selection substation’s location. To improve this problem, in this paper, the comprehensive evaluation method based on the Delphi, analytic Hierarchy process, Gray relations analysis and Fuzzy integrated evaluation (DHGF) was newly selected to choose the substation’s location. To build the evaluation system, Grid structure, Economic performance and External environment as the main influences and thirteen indexes were selected, and the comprehensive evaluation approach based on DHGF was established. The address selection of a 220 kV substation in the east of Xianxian county was studied by the method. At first, we graded the two similar candidate sites by Delphi approach, then the analytic hierarchy process was used to obtain the combined weights, at last the GF model was used to evaluate the two candidate schemes. Based on the DHGF comprehensive evaluation method, we selected the better location for the 220 kV substation from two similar candidate sites. The results showed that the comprehensive evaluation method based on DHGF can be used to choose the location of substation from the tow similar candidate sites. From this case, the effectiveness of the evaluation method based on DHGF to locate the substation was verified.

Forest landscape models (FLMs) are important tools for simulating forest changes over broad spatial and temporal scales. The ability of FLMs to accurately predict forest changes may be significantly influenced by the formulations of site-scale processes including seedling establishment, tree growth, competition, and mortality. The objectives of this study were to investigate the effects of site-scale processes and interaction effects of site-scale processes and harvest on landscape-scale forest change predictions. We compared the differences in species’ distribution (quantified by species’ percent area), total aboveground biomass, and species’ biomass derived from two FLMs: (1) a model that explicitly incorporates stand density and size for each species age cohort (LANDIS PRO), and (2) a model that explicitly tracks biomass for each species age cohort (LANDIS-II with biomass succession extension), which are variants from the LANDIS FLM family with different formulations of site-scale processes. For early successional species, the differences in simulated distribution and biomass were small (mostly less than 5 %). For mid- to late-successional species, the differences in simulated distribution and biomass were relatively large (10–30 %). The differences in species’ biomass predictions were generally larger than those for species’ distribution predictions. Harvest mediated the differences on landscape-scale predictions. The effects of site-scale processes on landscape-scale forest change predictions are dependent on species’ ecological traits such as shade tolerance, seed dispersal, and growth rates.

Soil coarseness is the main process decreasing soil organic matter and threatening the productivity of sandy grasslands. Previous studies demonstrated negative effect of soil coarseness on soil carbon storage, but less is known about how soil base cations (exchangeable Ca, Mg, K, and Na) and available micronutrients (available Fe, Mn, Cu, and Zn) response to soil coarseness. In a semi-arid grassland of Northern China, a field experiment was initiated in 2011 to mimic the effect of soil coarseness on soil base cations and available micronutrients by mixing soil with different mass proportions of sand: 0 % coarse elements (C0), 10 % (C10), 30 % (C30), 50 % (C50), and 70 % (C70). Soil coarseness significantly increased soil pH in three soil depths of 0–10, 10–20 and 20–40 cm with the highest pH values detected in C50 and C70 treatments. Soil fine particles (smaller than 0.25 mm) significantly decreased with the degree of soil coarseness. Exchangeable Ca and Mg concentrations significantly decreased with soil coarseness degree by up to 29.8 % (in C70) and 47.5 % (in C70), respectively, across three soil depths. Soil available Fe, Mn, and Cu significantly decreased with soil coarseness degree by 62.5, 45.4, and 44.4 %, respectively. As affected by soil coarseness, the increase of soil pH, decrease of soil fine particles (including clay), and decline in soil organic matter were the main driving factors for the decrease of exchangeable base cations (except K) and available micronutrients (except Zn) through soil profile. Developed under soil coarseness, the loss and redistribution of base cations and available micronutrients along soil depths might pose a threat to ecosystem productivity of this sandy grassland.

Accurate and timely monitoring of gross primary production GPP at regional and global scales is necessary for understanding the terrestrial biosphere carbon balance. In this article, 8-day composite GPP is estimated using the region production efficiency model REG-PEM in the Heihe river basin from 2006 to 2008. The result indicates that GPP meets the seasonal cycle well and varies with different land covers. Analysis of uncertainty and sensitivity of the REG-PEM model are implemented by the Monte Carlo method. GPP is simulated with a test data set; the data set includes three groups, and each group has 8000 points. The three groups obey uniform distribution, normal distribution and beta distribution, respectively. Uncertainty is assessed by the quantification of mean values and standard deviation of outputs. The distribution of simulated GPP is slightly different from that of model-calculated GPP over the study sites. Among the input parameters, the land surface water index LSWI and air temperature T make less of a contribution to model output than photosynthetic active radiation PAR and the enhanced vegetation index EVI. The main sources of model uncertainty are input data uncertainty and uncertainty from the specific model.

Temperate forests in Northeast China have been severely exploited by timber harvesting in the last century. To reverse this trend, China implemented the Classified Forest Management policy in the Natural Forest Conservation Program in 1998 to protect forests from excessive harvesting. However, the policy was unable to meet the 2020 commitment of increasing growing stock (set in the Kyoto Protocol) because of high-intensity harvesting. Accordingly, China banned all commercial harvesting in Northeast China in 2014. In this study, we investigated the long-term impacts of the no commercial harvest (NCH) policy on ecosystem services and biodiversity using a forest landscape model, LANDIS PRO 7.0, in the temperate forests of the Small Khingan Mountains, Northeast China. We designed three management scenarios: The H scenario (the Classified Forest Management policy used in the past), the NCH scenario (the current Commercial Harvest Exclusion policy), and the LT scenario (mitigation management, i.e., light thinning). We compared total aboveground forest biomass, biomass by tree species, abundance of old-growth forests, and diversity of tree species and age class in three scenarios from 2010 to 2100. We found that compared with the H scenario, the NCH scenario increased aboveground forest biomass, abundance of old-growth forests, and biomass of most timber species over time; however, it decreased the biomass of rare and protected tree species and biodiversity. We found that the LT scenario increased the biomass of rare and protected tree species and biodiversity in comparison with the NCH scenario, while it maintained aboveground forest biomass and abundance of old-growth forests at a high level (slightly less than the NCH scenario). We concluded there was trade-off between carbon storage and biodiversity. We also concluded that light thinning treatment was able to regulate the trade-off and alleviate the negative effects associated with the NCH policy. Our results highlighted limitations of the NCH policy and provided new insights into sustainable forest management and the interdependence between human society and the forest ecosystem.

Spatial scaling is very important to evaluation terrestrial carbon balance. In this paper, Gross primary production (GPP) are calculated using the Region Production Efficiency Model(REG-PEM) based the Moderate Resolution Imaging Spectrometer(MODIS) and Landsat TM data, respectively, and some issues related to spatial scaling are analyzed. The minimum and maximum values of parameters and GPP are significantly different at different scale. The mean values of parameters and GPP based on TM image are smaller than that based on MODIS image.

Photosynthetically active radiation (PAR) is a key parameter for almost all terrestrial ecosystem models. However, the usefulness of the currently available PAR products is constricted by their limited spatial and temporal resolution. In this paper, the processes of PAR in Heihe River Basin are thoroughly studied by improved Eck and Dye model during the period 2000–2008. 8-day composite and annual PAR are calculated using TOMS (Total Ozone Mapping Spectrometer) and OMI (Ozone Monitoring Instrument) reflectance data during 9 years. The results indicate that that the changes of estimated PAR in study area are totally fluctuating over the past several years. Annual total PAR increases from upstream to downstream. Meanwhiles, four representative sites with different landscape types in study area are selected for analyzing seasonal dynamics and interannual variations. Further, because of the remotely sensed data with higher resolutions in 2005–2008, the discrepancies of total annual PAR between these study sites are more obvious over last 4 years.