Biodiversity is the foundation of human survival, and its accurate assessment is a prerequisite for effective conservation and sustainable use. Most studies only assessed the state of biodiversity, but lacked a comprehensive understanding of the pressures and responses of biodiversity. In this paper, we took Yunnan Province (Yunnan) as a pilot area and constructed a comprehensive assessment system of biodiversity pressure-state-response (PSR) to comprehensively evaluate biodiversity in Yunnan. The results showed that: (1) Yunnan was one of the richest regions in the world in terms of biodiversity resources, and among the 16 cities and prefectures, Honghe Hani and Yi Autonomous Prefecture (Honghe), Nujiang Lisu Autonomous Prefecture (Nujiang), and Xishuangbanna Dai Autonomous Prefecture (Banna) ranked in the top three for biodiversity state index; (2) From 2010 to 2020, the pressure on biodiversity in Yunnan decreased by 19%, with only a slight increase in the biodiversity pressure index in Nujiang; in 2020, Kunming City (Kunming) faced the greatest pressure on biodiversity, scoring 2.21, while Diqing Tibetan Autonomous Prefecture (Diqing) had the least pressure, scoring 0.32; (3) Diqing had the highest biodiversity response index of 1.46, while Lincang City (Lincang) had the lowest response index of 0.61. Most of cities and prefectures had not shown good balance and consistency in their responses to biodiversity conservation in Yunnan Province. (4) Considering the comprehensive PSR assessment results, Nujiang had the highest biodiversity score, while Kunming had the lowest. The study comprehensively evaluated the biodiversity state and the main pressures faced by each city and prefecture in Yunnan, and the findings can provide theoretical support for the assessment and policy formulation of biodiversity conservation in Yunnan and the indicator system and assessment methods developed in the paper have reference significance for biodiversity assessment and management in other similar areas in the international arena.

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The mechanism underlying the effects of livestock grazing on grassland ecosystem traits has been greatly discussed. However, as a common small burrowing mammal on the Tibetan Plateau grasslands, the plateau pika's (Ochotona curzoniae) influence on alpine grassland ecosystem traits has rarely been investigated, especially beyond the plot scale. In this study, we flew an unmanned aerial vehicle (UAV) over a grassland landscape under grazing and nongrazing treatments. Mounted visible spectral remote sensing, in combination with field surveys, was utilized to explore how livestock and pika grazing modify grassland ecosystem traits at the landscape scale on the Tibetan Plateau (TP). Using object-oriented classification and partial least squares regression, we retrieved the pika burrow distribution and grassland ecosystem traits. Then, the relationships among livestock grazing, pika burrowing and ecosystem traits were evaluated. The results indicated that livestock grazing reduces the alpine meadow community height by 0.13 cm and the species number by 0.25 while increasing the vegetation coverage by 9.69 % and the aboveground biomass (AGB) by 10.07 g/m2. A lower statue grassland community with greater coverage caused by livestock grazing promotes pika burrowing. Pika burrow density increases 100/ha per 1.70 % increase in vegetation coverage, a 1.87 g/m2 increase in AGB or a 0.08 m decrease in community height. Under livestock grazing, both community structure and nutrients are more strongly associated with pika burrow density. The structural equation model demonstrated that livestock grazing regulates pika burrow density by moderating structural value and subsequently affecting nutritional value. Pika burrowing activity explains 40 % of the total variation in nutritional value. Our findings revealed an intrinsic linkage between mammal activities and alpine grassland ecosystems, which can provide guidelines for grassland management through pika population control by adjusting grazing intensity on the TP.

Despite extensive research on impacts of climate change on wetland ecosystem services (ES), the role of public conservation investments has been underexplored. This study examines the effects of various ecological conservation investments on five major wetland ecosystem services: microclimate regulation, carbon fixation, water regulation, soil retention, and sandstorm prevention across mainland China (excluding Hong Kong and Macau) from 2015 to 2019. Using spatial ecosystem service valuation (ESV) tools and fixed-effects panel regression, we found that a 1% increase in wetland restoration investment enhances the value of microclimate regulation and water regulation services by 1.67% and 1.86%, respectively. Similarly, a 1% increase in forest conservation investment predicts a 1.48% increase in carbon fixation and a 0.5% increase in water regulation services. Our uncertainty analysis, incorporating varying conservation investment levels and climate conditions, uses a random forest approach to predict future changes in wetland ES. Results indicate that most wetland ES remain stable under future scenarios, except for a universal decline in carbon fixation. Additionally, soil retention and sandstorm prevention services, which often go hand in hand, are projected to increase in northwestern and northeastern provinces. These findings provide insights for policymakers on optimizing conservation investments to maximize ecological and economic returns amidst climate change.

Temperature and precipitation are important abiotic factors affecting net primary productivity (NPP) in grassland ecosystems. However, findings on how elevation influences the effects of these factors on NPP in alpine grasslands are not yet consistent. In addition, the impact of varied patterns of climate change on NPP sensitivity with elevation remain unclear. Therefore, alpine grassland on the Tibetan Plateau (TP) was selected to profile the spatial and temporal patterns of NPP from 2001 to 2022, and subsequently to reveal the effects of temperature and precipitation on the sensitivity of NPP with altitudinal gradient. The results showed that (1) 91% of the TP grassland experienced positive NPP trends, and the NPP trends followed a unimodal curve with elevation, with the largest mean value at 2500 m; (2) a positive correlation between precipitation and NPP dominated the grassland NPP up to an elevation of 3400 m, and a positive correlation between temperature and NPP dominated the grassland NPP above an elevation of 3400 m; (3) temperature, precipitation, and their interaction explained, on average, 21% of the temporal variation in the NPP of TP grassland, and the explanatory capacity decreased significantly with elevation; and (4) elevation, temperature, and precipitation variations together explained 35% of the NPP sensitivity of the TP grasslands. This study reveals the altitudinal characteristics of NPP in grasslands affected by climate, and reminds us to take elevation into account when carrying out grassland management.

青藏高原及周边地区作为"亚洲水塔",拥有广大的冰川、冻土和湖泊,是重要的储水区域,为陆地生态系统提供了最基本的水分资源。生态系统赖以生存的水分资源主要来自自然降水,同时温度的改变会通过调节蒸发散而影响土壤湿度,从而影响生态系统过程。文章从生态系统群落组成和结构,植被物候、覆盖度和生产力,以及生态系统水源涵养功能等多个角度,综述近年来水资源变化给青藏高原生态系统带来的影响,旨在深入了解内部机制,为理论研究和环境治理提供参考。在群落组成和结构方面,水分条件改变引起群落盖度和多样性改变,影响草地群落物种的比例及其相对重要性,进而驱动群落演替。在物候方面,增加季前降水使春季物候提前,生长季降水的增加使秋季物候推迟,季前降水同时调节了物候对温度的响应。植被覆盖度和生产力总体态势为变好,但局部变化存在差异,增温和降水的非协调性变化对植被造成复杂的影响,体现在不同地区的生态控制因子存在差异。水源涵养功能是土壤-植被-大气系统相互作用的结果,受到气候、植被、土壤和人类活动等多种因素影响。在未来需要用系统的思想和方式,关注气候要素和植被覆盖变化对水源涵养量的耦合作用,探究各组分的作用效果和强度。

Land surface albedo (LSA) is a key parameter in the process of vegetation feedback to climate due to its decisive role in land surface radiation budget. However, our current knowledge on the relationship between LSA and vegetation changes is limited by one-sided attention to sole vegetation growth change or land use/land cover change (LULCC). How vegetation growth or LULCC respectively contributes to LSA change under their interactions remains poorly quantified. In this study, the arid and semi-arid areas of China (ASAC) with profound vegetation changes were selected to tackle this problem. The LSA showed a general downward trend (-0.00009 year -1) during 2000-2018 in response to ASAC's wide-range greening (0.0086 m(2)m(-2)year(-1)). Pairwise comparison analysis revealed that under the same unit of vegetation coverage change, the LSA change magnitude was contracted when grassland was converted to cultivated land or forest land, while the conversions of forest land to other vegetations led to an amplified change magnitude of LSA. Vegetation type directly leads to a difference in LSA change magnitude under greening due to their distinct canopy spectral characteristics. Grassland possesses lower LAI and its pixel-level LSA is more prone to be contaminated by background coverage, while LSA of forest land contains more vegetation canopy signal. In most areas where vegetation type converted, greening dominated LSA change with a contribution rate up to 98.14 %, except for the conversion of grassland to forest land, where LULCC accounted for about 66.38 % of LSA change. This study could improve the estimation of LSA from LAI, which is useful for optimizing vegetation-climate interaction models.

The denitrification process profoundly affects soil nitrogen (N) availability and generates its byproduct, nitrous oxide, as a potent greenhouse gas. There are large uncertainties in predicting global denitrification because its controlling factors remain elusive. In this study, we compiled 4301 observations of denitrification rates across a variety of terrestrial ecosystems from 214 papers published in the literature. The averaged denitrification rate was 3516.3 +/- 91.1 mu g N kg(-1) soil day(-1). The highest denitrification rate was 4242.3 +/- 152.3 mu g N kg(-1) soil day(-1) under humid subtropical climates, and the lowest was 965.8 +/- 150.4 mu g N kg(-1) under dry climates. The denitrification rate increased with temperature, precipitation, soil carbon and N contents, as well as microbial biomass carbon and N, but decreased with soil clay contents. The variables related to soil N contents (e.g., nitrate, ammonium, and total N) explained the variation of denitrification more than climatic and edaphic variables (e.g., mean annual temperature (MAT), soil moisture, soil pH, and clay content) according to structural equation models. Soil microbial biomass carbon, which was influenced by soil nitrate, ammonium, and total N, also strongly influenced denitrification at a global scale. Collectively, soil N contents, microbial biomass, pH, texture, moisture, and MAT accounted for 60% of the variation in global denitrification rates. The findings suggest that soil N contents and microbial biomass are strong predictors of denitrification at the global scale.

Aim Ecosystem carbon use efficiency (CUEe) is a core parameter of ecosystem process models, but its relationships with climate are still uncertain, especially for ecosystems with harsh environments. Large inconsistencies in climate impacts on the CUEe have been reported among various spatial scales. The goal of this study was to examine whether warming promotes or restricts the CUEe and whether the CUEe responds to a warming gradient in a linear or nonlinear manner. Location Tibetan Plateau. Time period 2000-2018. Major taxa studied Alpine grassland ecosystem. Methods We integrated multiple-source data of carbon fluxes and CUEe, including warming experiments at a site scale, eddy covariance observations at a landscape scale and synthesized warming experiments and ecosystem process models at a regional scale. Next, we deployed a statistical model to examine the warming impacts on the CUEe across scales; the effects of biotic and abiotic factors on the CUEe and its components were summarized based on the results of standardized major axis tests and routines, structural equation modelling and nonlinear models. Results This study reported a suppressive warming impact on the CUEe, which followed a nonlinear curve with severe inhibition in the high-level warming treatment. With a warming threshold of 1.5-2.0 degrees C, CUEe response patterns transitioned from no change to a significant decrease. The restriction effects can be ascribed to the joint adverse and asymmetric effects of warming on CUEe components under multiple-level warming. Warming-modified relationships among CUEe components and the nonlinear effects of biotic and abiotic factors led to the nonlinear responses of CUEe to warming. Main conclusions This study revealed suppressive and nonlinear effects of warming on the CUEe, including especially dramatic CUEe decreases with high-level warming. These findings are critical for optimizing model parameters and improving predictions of the carbon sequestration capacity of alpine grasslands.

Quantifying drought-induced ecosystem vulnerability, e.g. in terms of plant productivity, based on vulnerability curves and coupled processes is a frontier issue and a challenge in the field of climate change risk. Primary productivity vulnerability to drought varies among and within ecosystem types, obscuring generalized patterns of ecological stability. Thus, we constructed drought vulnerability curves between aboveground net primary productivity (ANPP) and drought intensity for forest and grassland, through global data collection, bias checking, and systematic integration. Based on the improvement of theoretical analysis of ecosystem vulnerability and quantitative evaluation methods, we investigated the processes of sensitivity and adaptation to reveal vulnerability mechanisms. The ANPP was nonlinearly reduced along with drought intensity gradients, with an increasing trend for forests and a decreasing trend for grasslands. Under the same drought duration, both the forest and grassland ANPP decreased with increasing intensities (from light to severe drought). However, the forest and grassland ANPP exhibited divergent responses with durations under the same drought intensity. The combinations of drought duration and intensities also affected the ANPP. For example, negative responses of the grassland ANPP to increasing intensities differed among the durations (p = 0.001) and maximum occurred under the severe drought. Furthermore, we quantified the vulnerability by analyzing sensitivity and adaptation to short- (<= 3years) and long-term (> 3 years) drought. Grasslands showed higher sensitivity to short-term drought than to long-term drought, and the contrary for forests. Forests exhibited a certain adaptation to long-term drought, but to a lesser extent than grasslands. Comprehensively, grasslands presented lower vulnerability to growing-season drought with higher adaptation and lower sensitivity than forests. These findings suggest that quantitative assessment on ecosystem response to drought from the viewpoints of vulnerability curves and processes should be promoted in and coupled with future climate change risks and sustainable management of different ecosystems.

Ecosystem trait is a standardized description of biological features of a community, and it bridges individual plants and ecosystem. Conventionally most ecosystem trait data are collected from field survey and the generated data is hard to meet the requirements as set in the concept of ecosystem trait. To a great extent, remotely piloted aircraft systems (RPAS) remote sensing, which is capable of retrieving ecosystem traits across multiple scales, can overcome constraints in field plot survey. In this study, we selected alpine grassland ecosystem on the Tibetan Plateau (TP), which is under‐studied due to scarcity of field monitoring data, as the research target. A new data framework was proposed by integrating field plot and RPAS remote sensing data to map spatial patterns of ecosystem traits for the alpine grasslands. Across four landscapes on the TP, ecosystem traits of vegetation coverage (CVC), species number (CSN), individual number (CIN), above ground biomass (AGB), organic carbon content (OC%) and total nitrogen content (TN%) were retrieved. We also calculated Shannon's Diversity Index and Shannon's Evenness Index for each plot. The results showed that RPAS‐based high spatial resolution RGB image is capable of predicting both physical and chemical ecosystem traits for alpine grasslands on the TP. Remote sensing on physical traits are overall more efficient than on chemical traits, with the highest R 2 of 0.86 and 0.48 for physical trait and chemical one, respectively. The bands of Red and Green contributed more to the prediction model than band of Blue did, and the spectral mean value played a greater role than the spectral standard deviation. Based on the retrieved results, a set of spatial patterns on ecosystem traits can be revealed. This study represents an advance on ecosystem trait study and can significantly improve our understanding on ecosystem functions of the alpine ecosystem on the TP.

It's generally believed that elevated CO2 (eCO(2)) could stimulate plant growth and the ecosystem carbon (C) sink. However, great uncertainties exist in terms of the CO2 fertilization effect (CFE) magnitude, and how it is regulated by other global change factors. The lack of experimental evidence from the Alpine Region also limits our cognition on the CFE. By conducting a five-year manipulative field experiment in a semi-arid grassland of the Tibetan Plateau, we are aimed to explore the behavior of ecosystem C exchange in response to eCO(2) and N availability under contrasting natural precipitation regimes. The experiment showed that eCO(2) stimulated both gross ecosystem productivity (GEP) and ecosystem respiration (ER), and resulted in a neutral effect on net ecosystem productivity (NEP). The reduction of leaf N concentration under eCO(2) constrained the eCO(2) effects on C fluxes, especially on GEP and NEP. As N addition replenishes N availability in soil and leaf, GEP benefited more from the N addition than the ER. The eCO(2) strengthened the C sink when exogenous N was added simultaneously. Furthermore, precipitation variability played an importance role in mediating the eCO(2) effect among growing seasons. The eCO(2) effects on C fluxes tended to decline with increased water availability. The CFE was suppressed with excessive precipitation when the water-use efficiency (WUE) response was weak and eCO(2)-induced water-saving disappeared. The negative impact of precipitation on the CFE may also be attributed to the short precipitation intervals and insufficient radiation caused by high-frequency precipitation. Our study demonstrates that eCO(2) only stimulates net C uptake under conditions of N addition or during drier periods. Given the widespread N limitation, the efficacy of terrestrial ecosystems in mitigating climate change under rising CO2 may be weaker than projected and is closely related to the precipitation variability.

The ecological consequences of precipitation change and increased atmospheric nitrogen (N) deposition have profound impacts on ecosystem CO2 exchange in grassland ecosystems. Water and N can largely influence grassland productivity, community composition and ecosystem functions. However, the influences of water and N addition on the ecosystem CO2 exchange of alpine grassland ecosystems remain unclear. A field manipulative experiment with water and N additions was conducted in an alpine meadow on the Tibetan Plateau over 4 years with contrasting precipitation patterns. There were four treatments: control (Ctrl), N addition (N), water addition (W) and N and water addition (NW), each replicated three times. N addition, but not water addition, increased gross ecosystem productivity (GEP), plant biomass, community cover and community-weighted mean height. The responses of ecosystem CO2 exchange to water and N addition varied between the wet and dry years. Water addition had a positive effect on net ecosystem carbon exchange (NEE) due to a larger increase in GEP than in ecosystem respiration (ER) only in the dry year. On the contrary, N addition significantly enhanced ecosystem CO2 exchange only in the wet year. The increased GEP in N addition was attributed to the larger increase in NEE than ER. Moreover, N addition stimulated NEE mainly through increasing the cover of dominant species. Our observations highlight the important roles of precipitation and dominant species in regulating ecosystem CO2 exchange response to global environmental change in alpine grasslands.

Soil nitrogen (N) mineralization is crucial for the sustainability of available soil N and hence ecosystem productivity and functioning. Metabolic quotient of N mineralization (Qmin), which is defined as net soil N mineralization per unit of soil microbial biomass N, reflects the efficiency of soil N mineralization. However, it is far from clear how soil Qmin changes and what are the controlling factors at the global scale. We compiled 871 observations of soil Qmin from 79 published articles across terrestrial ecosystems (croplands, forests, grasslands, and wetlands) to elucidate the global variation of soil Qmin and its predictors. Soil Qmin decreased from the equator to two poles, which was significant in the North Hemisphere. Soil Qmin correlated negatively with soil pH, total soil N, the ratio of soil carbon (C) to N, and soil microbial biomass C, and positively with mean annual temperature and C:N ratio of soil microbial biomass at a global scale. Soil microbial biomass, climate, and soil physical and chemical properties in combination accounted for 41% of the total variations of global soil Qmin. Among those predictors, C:N ratio of soil microbial biomass was the most important factor contributing to the variations of soil Qmin (the standardized coefficient = 0.39) within or across ecosystem types. This study emphasizes the critical role of microbial stoichiometry in soil N cycling, and suggests the necessity of incorporating soil Qmin into Earth system models to better predict N cycling under environmental change.

One-third of the global fossil fuel CO2 emissions is offset by carbon uptake of terrestrial ecosystems, while its strength is highly sensitive to drought events. It is predicted that frequencies of drought events would increase under a changing climate, which entails improving our understanding about their effects. Here, we combined direct observations at plot (experiment sites) and landscape (eddy-covariance, EC) scales with remote sensing observations at a regional scale, and evaluated the linkages between ecological resistance (summer drought loss, SDL) and resilience (post-drought regrowth, PDR). The study was conducted for an alpine grassland ecosystem on the Tibetan Plateau, which is highly vulnerable to climate changes. The results showed that alpine grasslands possess low resistance to drought. A summer drought of 2015 reduced net primary productivity (NPP) or net ecosystem productivity (NEP) by 25.4 g C m (- 2), 48.6 g C m (- 2) and 14.2 Tg C at the plot, landscape and regional scale relative to the baseline, respectively. In another dry summer of 2017, NEP was 11.0 g C m (- 2) and 7.5 g C m (- 2) lower than the baseline at the landscape and plot scale, respectively. To be noted, NEP or NPP completely recovered and exceeded the baseline due to rewetting induced PDR, compensating for the prior SDL to a certain extent. In 2015, the SDL of NEP or NPP was compensated by 39.0%, 17.3% and 10.6% due to the PDR effects at the plot, landscape and regional scale, respectively. The PDR of NEP in 2017 offset 23.6% and 70.7% of the prior SDL at the landscape and plot scale, respectively. Overall, these results demonstrated that weakened ecosystem function due to drought (e.g., low resistance) does not preclude rapid ecosystem recovery and regrowth (e.g., high resilience), which compensates for the prior loss to a certain degree.

The study evaluated GIMMS NDVI based on MODIS NDVI and SPOT NDVI over the same period from 2000 to 2015. We assessed their absolute values, dynamics, trends and cross-relationships between any two of the NDVIs for the national scale, as well as four separate land use types, i.e., paddy field, dry land, forest, and grassland. GIMMS NDVI was numerically greater than MODIS NDVI and SPOT NDVI. The three NDVIs exhibited equal capability of capturing monthly phenological variations. During the study period, the three NDVIs showed increasing trends in most regions, with GIMMS NDVI showing the smallest increment. Pronounced differences were identified in trends between GIMMS NDVI and MODIS NDVI or SPOT NDVI in the northwest, northeast, south-central China, Tibetan Plateau and Yunnan-Guizhou Plateau, implying that GIMMS NDVI trends in these regions should be interpreted with caution. High correlations existed between the three datasets. MODIS NDVI and SPOT NDVI showed stronger correlations at national scale. The GIMMS NDVI and MODIS NDVI were in highest accordance for dry land, while MODIS NDVI and SPOT NDVI were in higher accordance for the paddy field, forest, and grassland than dry lands.

Purpose Glomalin-related soil protein (GRSP), produced by arbuscular mycorrhizal fungi, plays crucial roles in the global carbon cycle and improves soil quality. However, information on GRSP and its contribution to the soil organic carbon (SOC) pool in the process of urbanization is limited. Materials and methods In this study, easily extracted GRSP (EE-GRSP) and total GRSP (T-GRSP) were analyzed in an urban-rural gradient, and a detailed survey of greenspace characteristics (soil properties: pH, electric conductivity [EC], bulk density, temperature, and SOC; forest characteristics: tree density, tree size, tree species, and arbor and shrub richness; land use: road, building, greenspace, and wetland and water) in 306 plots was undertaken. Results and discussion EE-GRSP/SOC and T-GRSP/SOC decreased significantly by 10% in urban plots when compared with the rural plots. From the rural to urban plots, decrease in pH and increases in SOC, EC, tree height, and under branch height (p<0.01) were found in this study. These changes in greenspace characteristics were responsible for variation in GRSP, while their relative explanatory power differed (soil properties: 43.8%, forest characteristics: 25.7%, and land use: 18.6%). Forward selection analysis identified that EC, greenspace proportion, pH, shrub richness, diameter at breast height, wetland and water proportion, bulk density, and under branch height had significant explanatory power for the variation in GRSP (all: p<0.05). Conclusions Our findings indicate that urbanization greatly affects the contribution of GRSP to the SOC pool. The changes in greenspace characteristics played key roles in regulating the pattern of GRSP, especially soil properties. The results of this study may be used as a reference for the exploration of GRSP in urban environments and implementation of soil improvement practices by regulating GRSP.

Abstract Effects of climate warming and changing precipitation on ecosystem carbon fluxes have been intensively studied. However, how they co‐regulate carbon fluxes is still elusive for some understudied ecosystems. To fill the gap, we examined net ecosystem productivity (NEP), gross ecosystem productivity (GEP,) and ecosystem respiration (ER) responses to multilevel of temperature increments (control, warming 1, warming 2, warming 3, warming 4) in three contrasting hydrological growing seasons in a typical semiarid alpine meadow. We found that carbon fluxes responded to precipitation variations more strongly in low‐level warming treatments than in high‐level ones. The distinct responses were attributable to different soil water conditions and community composition under low‐level and high‐level warming during the three growing seasons. In addition, carbon fluxes were much more sensitive to decreased than to increased precipitation in low‐level warming treatments, but not in high‐level ones. At a regional scale, this negative asymmetry was further corroborated. This study reveals that future precipitation changes, particularly decreased precipitation would induce significant change in carbon fluxes, and the effect magnitude is regulated by climate warming size.

采用样方调查法,对长春南湖公园油松林的乔木物种组成和区系特征进行分析;基于一阶格局检验判别理论,并选用径级作为龄级代用指标,研究了油松林的物种结构格局.结果表明:南湖公园油松林乔木共7科9属10种,组成较为单一,科、属、种配置不合理;区系特征明显,科级类别以泛热带居多,混有世界广布科和北温带分布科,属级类别以北温带为主;研究样方中,油松的个体数量、重要值均占绝对优势,但在胸径、高度上优势不明显;径级分布总体呈现正态分布,种群以中龄乔木为主,近熟、成熟乔木次之,幼苗、幼树稀少,属稳定型种群,更新能力较差;油松种群整体为聚集分布,样方尺度上以均匀分布为主,而不同龄级的油松聚集程度判别结果不一致,随空间尺度的缩小,油松格局呈现从聚集向均匀分布的趋势.