应用生态学报最新文献

As an important component of aquatic ecosystem, fish habitat is crucial for maintaining aquantic ecosystem, species diversity, and sustainable fisheries. To reveal the suitability of habitat factors and distribution patterns of Schizothorax wangchiachii in the Heishui River of the lower Jinsha River tributary, we selected the habitat indicators by the Spearman correlation single tail test, calculated the fish habitat suitability index by the random forest algorithm and weighted average method, based on the fish catch data and 16 related environmental factor data collected from 2018 to 2019. The results showed that the optimal range of water temperature, water depth, and altitude for S. wangchiachii was 16.3-16.8 ℃, 35-60 cm, and 637-816 m, respectively. From the upper reaches to the lower reaches, the habitat suitability of S. wangchiachii showed a longitudinal increasing trend. The proportion of the habitat quality below the good standard was 70%, while the proportion reaching the good and very good stan-dards was only 30%. The habitat of S. wangchiachii was mainly distributed in the natural flowing river sections with high hydrological connectivity of the river course, shallow water depth, abundant bait organisms and slow flow rate. The obvious spatial differences of its habitat suitability might be caused by human disturbances such as the construction of small dams.

This study aimed to clarify the impacts of elevating CO₂ concentration (e[CO₂]) on maize "source-sink" characteristics in maize intercropping with peanut system. We investigated the impacts of e[CO₂] on leaf "source" quantity, gas exchange parameters, population "source" productivity, "sink" capacity, grain to leaf ratio, yield and intercropping advantage of maize under 0 (P₀) and 180 kg P₂O₅·hm^-2(P₁₈₀). The results showed that compared with ambient CO₂ concentration (a[CO₂]), e[CO₂] augmented leaf "source" quantity and "source" activity of intercropping maize, and significantly increased productivity of population "source". The silk maximum number, actual seed number and effective "sink" capacity were increased by 8.0%-9.3%, 10.0%-13.4%, and 10.4%-20.8%, respectively. Concurrently, the average dry matter accumulation rate of grains was significantly increased by 10.7%-50.4%. The grain to leaf ratio and harvest index were increased by 3.3%-7.4% and 2.4%-7.9%, respectively. The yield and intercropping advantage were increased by 10.8%-48.7% and 20.4%-102.7%, respectively. Under e[CO₂], phosphorus application could further improve the "source-sink" relationship and maize yield, and increase the intercropping advantage. In summary, e[CO₂] enhanced the "source" performance and "sink" capacity of intercropping maize, promoted grain filling, regulated the "source-sink" relationship, enhanced yield, and thus increased the intercropping advantage.

Water resources are essential for sustaining life, driving economic development, and protecting the environment. We investigated the hydrochemical variations of surface water and groundwater in the Shandian River Basin to identify the driving factors and the transformation relationship between each water body. Precipitation data was collected from May to October 2023, while surface water and groundwater samples were collected in both August (wet season) and October (dry season). We analyzed water samples by Piper triplex diagram, Gibbs diagram, ion ratio method, hydrogen and oxygen isotope analysis, and MixSIAR mixed model. The results indicated that both groundwater and surface water were generally weakly alkaline. The dominant type of groundwater chemical composition was HCO₃^--Ca²⁺·Na⁺.During the process of surface water transitioning from the wet season to the dry season, the predominant surface water chemistry type shifted from HCO₃^--Ca²⁺-Na⁺ to HCO₃^--Na⁺-Mg²⁺, as well as HCO₃^--Ca²⁺-Na⁺-Mg².Furthermore, the main hydrochemical types of surface water changed during the transition from wet season to dry season. The hydrochemical characteristics of different types of water were influenced by weathering of rocks, evaporation and concentration of water, as well as cation exchange. Additionally, significant enrichment of δD and δ¹⁸O isotopic values in surface water was observed during the wet season, and the ground-water remained in a depleted state during both wet and dry seasons. During the wet and dry seasons, the slope of surface water line was lower than that of the precipitation line, and the slope of groundwater line during the wet season was similar to that of the precipitation line and the surface water line, indicating the complexity of the conversion relationship between various water bodies during the wet season. The precipitation served as ~70% primary recharge source for surface waters, whereas underground aquifers contributed ~30%, being the secondary recharge source. During the dry season, groundwater replenished surface water. These findings would provide fundamental support for effective resource management and protection practices related to the basin.

Farmland ecosystems are strongly affected by climate change, but the effects of global warming and precipitation changes and their interactions on soil organic carbon and enzyme activities in farmland soils and their relationships are still poorly understood. In this study, we employed the Open-Top Chamber (OTC) warming platform and the precipitation manipulative platform to investigate the effects of warming and precipitation changes on soil organic carbon and enzyme activities in semi-arid spring wheat farmland in Loess Plateau of the central Gansu Pro-vince. There were six treatments: control (CK), 30% precipitation reduction (-P₃₀), 30% precipitation increase (+P₃₀), warming (W), warming and 30% precipitation reduction (W-P₃₀), and warming and 30% precipitation increase (W+P₃₀). The results showed that OTC warming significantly elevated soil organic carbon (SOC), microbial biomass carbon (MBC), readily oxidizable organic carbon (KMnO₄-C), dissolved organic carbon (DOC), and particulate organic carbon (POC) contents. In contrast, the mineral associated organic carbon (MAOC) content changed little. Under ambient temperature, neither an increase nor a decrease in precipitation resulted in a significant alteration of soil organic carbon fractions. However, under the warming condition, elevated precipitation resulted in a notable enhancement in DOC and POC contents. Warming and precipitation significantly interacted to affect SOC, DOC, and KMnO₄-C contents. The interaction between precipitation and warming resulted in an increase in the carbon pool management index (CMI), the carbon pool index (CPI), the activity of soil cellobiose hydrolase, urease, sucrase, N-acetyl-β-D-glucosidase, as well as crop biomass. The correlations between soil temperature, moisture, soil organic carbon fractions and enzyme activities were positive. There was a negative correlation between soil temperature and sucrase activity. The random forest modelling analysis demonstrated that soil physicochemical properties, enzyme activities, temperature and water content together explained 52.4% to 71.1%, and the five factors with higher correlation importance were soil urease activity, soil temperature, soil moisture, soil N-acetyl-β-D-glucosidase activity, and effective phosphorus. However, the selected factors only accounted for 21.5% of the observed variation in MAOC content. In conclusion, warming and precipitation changes significantly affected soil properties, enzyme activities and crop biomass, and thus soil organic carbon pools, in semi-arid wheatland soil of Loess Plateau of central Gansu Province.

Soil salinization and alkalization is a serious constraint to sustainable development of agriculture. Timely acquisition of soil salinity content (SSC) and pH information is crucial for improvement and rational utilization of saline-alkaline farmlands. We collected the data of field hyperspectral information and salt and alkali indicators in the surface layer (0-20 cm) and sub-surface layer (20-40 cm) in Pingluo County, Shizuishan City from Ningxia. We transformed the original spectral reflectance by Savitzky-Golay (SG) smoothing with the fractional order differentiation (FOD) of order 0-2 (with an interval of 0.25), constructed nine spectral indices, and established the inverse models of SSC and pH based on three machine learning algorithms, namely partial least squares regression (PLSR), random forest (RF) and extreme random tree (ERT), after the screening of feature covariates according to the correlation between the indices and the examined salt and alkali indicators. The results showed that 1) the spectral reflectance of the surface layer was always multiplicative with the subsurface layer, and the FOD transform could effectively eliminate the baseline drift of the spectral curves, highlighting the subtle spectral information. 2) Both surface and subsurface SSC were most strongly correlated with the difference index (DI), the optimal spectral index (OSI), and the soil-adjusted spectral index (SASI), with optimal transformation orders of 1.5 and 0.75, respectively. For pH, the strongest correlations were with the ratio index (RI), the generalized index (GDI), and the normalized index (NDI), with optimal orders of 0.5 and 0.25, respectively. 3) The ERT model performed the best with respect to the salt and alkali indicators of different soil layers. The accuracy of SSC inversion was higher in the surface layer than in the subsurface layer, while the opposite was true for pH. The coefficient of determination for the validation set (R_p²), root mean square error (RMSE), and relative predictive deviation (RPD) for the surface SSC-1.5 order-ERT model were 0.980, 0.547, and 5.229, whereas the R_p², RMSE, and RPD of the subsurface pH-0.25 order-ERT model were 0.958, 0.111, and 4.685, respectively. Those values indicated high accuracy of the models. This study would provide technical support for the rapid acquisition and inversion mapping of farmland salinity and alkalinity information.

Mountainous and hilly regions are one of the mainstays of national ecological security barriers. To avoid the impact of terrain undulations on the ecological environment quality assessment, we used the normalized difference mountain vegetation index (NDMVI) as the greenness ecological factor, combined with the humidity, aridity, and thermal factors, to construct the improved the hilly remote sensing ecological index (HRSEI) for mountainous areas based on the remote sensing ecological index (RSEI). We assessed ecological quality in two typical mountai-nous and hilly areas, i.e., Changting County in Longyan City, Fujian Province, and Shanyang County in Shangluo City, Shaanxi Province. We compared the ecological quality grade transition paths of HRSEI and RSEI, and verified the applicability of HRSEI in mountainous areas. The results showed that NDMVI could extract more vegetation information in mountainous areas than NDVI. The greater the topographic relief, the stronger the ability of NDMVI to extract vegetation information. Verified through average correlation and stepwise regression equations, HRSEI was representative for the ecological quality assessment of mountainous and hilly areas. HRSEI mainly upgraded the vegetation ecological grade from good to excellent for some areas affected by shadows. Compared with the extraction results of RSEI, areas classified as excellent increased by 13.75 and 41.88 km² in Changting and Shangyang, respectively. Combined with high-resolution imagery, the areas with improved ecological quality corresponded to high-vegetation-cover areas affected by mountain shadows, indicating that HRSEI could effectively improve the identification accuracy of high-vegetation-cover areas influenced by shadows, making it more practical.

Due to natural factors and influences from neighboring countries, wild fires frequently occur in China's border areas. To quantify the activities of wild fires in border areas, we analyzed the regime of wild fires within a 2 km buffer zone on both sides of China's land borders based on MODIS fire spot data, including fire types, fre-quency, seasonality, and spatial distribution. Between 2001 and 2022, a total of 25918 vegetation fires occurred in China's border regions, with forests, cropland, and grasslands accounting for 42.0%, 30.4%, and 14.4% of the fire incidents, respectively. Forest fires were most common in broadleaved forests. Cropland fires mainly resulted from traditional farming practices and the lack of fire prevention awareness among border residents, which often caused fires to spread to nearby forests, leading to forest fires. Among grassland fires, meadow steppe posed the highest risk, and grassland fires in forest-grassland ecotones were likely to trigger forest fires. There were significant differences in fire types and seasonal distribution across regions. In the northeastern border region, grassland fires, deciduous broadleaved forest fires, and cropland fires were predominant, with spring and autumn being the primary seasons for fire occurrences, especially in April and October. In the southwestern border region, evergreen broadleaved forest fires and cropland fires were predominant, with spring and winter being peak periods for fires, especially in March and December. In the northwestern border region, grassland fires and cropland fires were predominant, with more vegetation fires occurring in summer and autumn, peaking in September. Within a 2 km range on both sides of the border, the number of fire spots outside the country far exceeded those within, particularly in the border areas of Inner Mongolia, Jilin, Yunnan, and Guangxi, increasing the risk of cross-border fires in these regions. Fire spots showed significant clustering, with major clusters found in the border region of Xishuangbanna Dai Autonomous Prefecture in Yunnan, Hulunbuir City in Inner Mongolia, Huma County and Jiamusi City in Heilongjiang, and Hunchun City in Jilin. Different fire prevention strategies should be developed based on the characteristics of vegetation fires in different border regions, targeting vegetation types, seasonal periods, and clustering areas prone to fires, to implement effective vegetation fire prevention and control measures in border areas.

Gymnadenia conopsea is an endangered medicinal plant. Due to climate change and human activities, as well as the low reproductive capacity, the wild resources of G. conopsea are extremely scarce and it has been listed in the Chinese National Second Level Protected Plant List. Predicting the potential suitable distribution area of G. conopsea is crucial for the conservation and sustainable utilization. With climate and soil data from 118 distribution points, we used MaxEnt model combined with ArcGIS technology to predict the suitable distribution area of G. conopsea in China under future climate change. The results showed that the area value (ACU) under the receiver operating characteristic curve (ROC) was 0.808, indicating good prediction performance. The main environmental factors affecting the distribution of G. conopsea were mean temperature of the warmest quarter, seasonal precipita-tion, soil factors such as the subsoil sodicity (30-100 cm), topsoil gravel (0-30 cm), subsoil cation exchange capacity (30-100 cm), annual precipitation and precipitation of the driest month. At present, the potential total suitable distribution area of G. conopsea in China was about 50.22×10⁵ km², concentrated in north, northeast and southwest China, including Inner Mongolia, Heilongjiang, Jilin, Liaoning, Sichuan, Shanxi and Southeast Xizang. Under future climate scenarios, the suitable habitat range would shrink, and migrate to higher altitude regions such as Xizang, Yunnan, and Sichuan, indicating that global warming may pose a threat. This result could provide scientific basis for the ecological protection, resource development, and sustainable utilization strategies of G. conopsea germplasm resources.

Soil conditioners are efficacy in ameliorating saline-alkali soils and fostering crop growth. To explore the effect and physiological mechanism of soil conditioner on improving the adaptability of maize to saline-alkali stress, we conducted a field randomized block experiment in Liuzhong Village, Pingluo County, Ningxia Province in 2022. We investigated the variations of antioxidant capacity, key enzyme activities and photosynthetic fluorescence properties of maize induced by soil conditioners under saline-alkali stress, with "Xianyu 1255" maize as the experimental material under four treatments: T₀(no conditioner, control), T₁(humic acid), T₂(microsilica fume + wood vine-gar solution), T₃(humic acid + wood vinegar solution + microsilica fume). The results showed that soil conditioner could enhance the antioxidant capacity, key enzyme activity and photosynthetic fluorescence characteristics of maize leaves. The superoxide anion scavenging rate and superoxide dismutase activity of each treatment in the two growth stages (jointing stage-big flare stage and grain filling stage) were significantly increased and the content of malon-dialdehyde was significantly decreased. The aquaporin activity of each treatment in the jointing stage-big flare stage was significantly enhanced. Transpiration rate, net photosynthetic rate, stomatal conductance, non-photochemical quenching coefficient, apparent synthetic electron transfer rate and actual photochemical efficiency were significantly enhanced, while the intercellular carbon dioxide concentration was significantly decreased in T₂ and T₃ treatments. The hydroxyl radical scavenging rate and initial fluorescence of each treatment were significantly increased in each treatment at the grain filling stage. T₃ performed the best. Structural equation modeling and membership function analysis confirmed that soil conditioners could bolster the antioxidant system and aquaporin activity in maize, mitigate membrane lipid peroxidation, enhance stomatal conductance, and improve photosynthesis, thereby improve the resistance of maize to saline-alkali. The combined application of humic acid, wood vinegar, and microsilica fume was the most effective one.

Grazing exclusion is the most effective measure to restore the structure and function of degraded grasslands, and plays a crucial role in increasing ecosystem carbon (C) sequestration capacity. The dynamics and dri-ving mechanisms of soil organic carbon (SOC) after grazing exclusion have attracted great concerns, especially in the context of global change. By reviewing the current research on the SOC sequestration dynamics and its driving mechanisms after grazing exclusion, we aimed to clarify the SOC sequestration dynamics, explore the influencing mechanisms of plant C input and microbial community on SOC, analyze the driving mechanisms of photosynthetic C input and litter decomposition on SOC sequestration, and explore the contribution of plant and microbial necromass C to SOC sequestration after grazing exclusion. Long-term grazing exclusion improve the structure and function of soil microorganisms by increasing plant carbon inputs, and increase the content and proportion of soil stable organic C (such as mineral-associated organic C, plant and microbial necromass C, etc.), reducing mineralization efficiency of SOC and improving microbial C utilization efficiency, and consequently promoting SOC accumulation. In addition, SOC sequestration shows two trends of "first increasing and then stabilizing" and "first decreasing, following increasing and then stabilizing", which are affected by the initial SOC level. Future studies should be strengthened in the SOC fraction dynamics, the C flow of SOC input, the decomposition process of SOC, and the microbial dri-ving mechanism after grazing exclusion.