A systematic review of vegetation phenology in Africa

The study of vegetation phenology is important because it is a sensitive indicator of climate changes and it regulates carbon, energy and water fluxes between the land and atmosphere. Africa, which has 17% of the global forest cover, contributes significantly to the global carbon budget and has been identified as potentially highly vulnerable to climate change impacts. In spite of this, very little is known about vegetation phenology across Africa and the factors regulating vegetation growth and dynamics. Hence, this review aimed to provide a synthesis of studies of related Africa's vegetation phenology and classify them based on the methods and techniques used in order to identify major research gaps. Significant increases in the number of phenological studies in the last decade were observed, with over 70% of studies adopting a satellite-based remote sensing approach to monitor vegetation phenology. Whereas ground based studies that provide detailed characterisation of vegetation phenological development, occurred rarely in the continent. Similarly, less than 14% of satellite-based remote sensing studies evaluated vegetation phenology at the continental scale using coarse spatial resolution datasets. Even more evident was the lack of research focusing on the impacts of climate change on vegetation phenology. Consequently, given the importance and the uniqueness of both methods of phenological assessment, there is need for more ground-based studies to enable greater understanding of phenology at the species level. Likewise, finer spatial resolution satellite sensor data for regional phenological assessment is required, with a greater focus on the relationship between climate change and vegetation phenological changes. This would contribute greatly to debates over climate change impacts and, most importantly, climate change mitigation strategies.     

藏北高原植被物候时空动态变化的遥感监测研究

利用遥感数据提取的植被物候格局及时空变化特征能很好地反映区域尺度上植被对全球变化的响应。目前关于青藏高原地区植被物候的少量报道基本上是基于物候站点的观测记录展开分析的。该文基于非对称高斯拟合算法重建了藏北高原2001-2010年的MODIS EVI (增强型植被指数)时间序列影像, 然后利用动态阈值法提取整个藏北高原2001-2010年植被覆盖的重要物候信息, 包括植被返青期、枯黄期与生长季长度, 分析了植被物候10年间平均状况的空间分异特征以及年际变化情况, 并结合站点观测记录分析了气温和降水对植被物候变化的影响, 结果表明: (1)藏北高原植被返青期在空间上表现出从东南到西北逐渐推迟的水平地带性与东南高山峡谷区的垂直地带性相结合的特征, 近60%区域的植被返青期提前, 特别是高山地区; (2)植被枯黄期的年际变化不太明显, 大部分地区都表现为自然的年际波动; (3)生长季长度的时空变化特征由植被返青期和枯黄期二者决定, 但主要受返青期提前影响, 大部分地区生长季长度延长; (4)研究区内不同气候区划植被物候的年际变化以那曲高山谷地亚寒带半湿润区和青南高原亚寒带半干旱区的植被返青期提前和生长季延长程度最为明显; (5)基于气象台站数据分析气候变化对物候的影响发现, 返青期提前及生长季延长主要受气温升高的影响, 与降水的关系尚不明确。     

Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite‐derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green‐up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green‐up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green‐up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green‐up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green‐up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature.     

1982—2009年基于卫星数据的北半球中高纬地区植被春季物候动态及其与气候的关系

深入认识北半球植被物候在全球变暖背景下的动态变化特征,对于评估和预测生态系统结构和功能对气候变化的响应有重要的指示作用.遥感技术是获取北半球植被春季物候的最重要方法,但是由于物候提取算法的差异,目前还存在较大的不确定性.本文利用5种方法,基于卫星获取的归一化植被指数估算了北半球中高纬地区1982—2009年植被春季物候开始日期,分析了该日期的多年动态变化的时空特征,并探讨了气候变化对春季物候变化的影响.结果表明: 研究区植被春季物候开始日期呈现提前趋势,研究期间提前(4.0±0.8) d,其中,欧亚大陆提前速率为(0.22±0.04) d·a^-1,显著高于北美大陆的变化速率(0.03±0.02 d·a^-1);不同植被类型的变化趋势不同,5种方法都显示草地表现为显著提前趋势,而林地的提前趋势不显著.区域平均的植被春季物候开始日期的年际波动主要受春季温度的变化所驱动(r² =0.61,P<0.001), 温度每上升1 ℃,可以导致春季物候提前(3.2±0.5) d,而春季降水影响不显著(P>0.05).     

基于通量塔净生态系统碳交换数据的植被物候遥感识别方法评价

选择北美洲72座通量塔观测的净生态系统碳交换（NEE）数据来计算植被物候,并以此作为参考数据,从可行性和准确性两方面对阈值法、移动平均法和函数拟合法三大类常用的植被物候遥感识别方法进行了综合评价.结果表明： 基于局部中值的阈值法对植被物候识别的可行性和准确性均最优;其次为Logistic函数拟合法中的一阶导数方法;移动平均法对植被物候识别的可行性和准确性与移动窗口的大小有关,对于16 d合成的归一化差值植被指数（NDVI）时间序列数据来说,移动窗口大小为15时能获得较优的结果;而全局阈值法对植被物候识别的可行性和准确性均最差;Logistic函数拟合法中的曲率变化率方法在识别植被物候时虽然与基于NEE数据得到的植被物候在数值上存在较大偏差,但二者之间具有较高的相关性,说明基于曲率变化率方法识别出的植被物候能较真实地反映植被物候在时空上的变化趋势.     

东北地区植被物候时序变化

植被与气候的关系非常密切,植被物候可作为气候变化的指示器。东北地区位于我国最北部,是气候变化的敏感区域,研究该区植被物候对气候变化的响应对阐明陆地生态体统碳循环具有重要意义。利用GIMMS AVHRR遥感数据集得到了东北地区阔叶林、针叶林、草原和草甸4种植被25a(1982—2006年)的物候时序变化,得出4种植被春季物候都表现出先提前后推迟的现象,秋季物候的变化则比较复杂,阔叶林和针叶林整体上呈现出秋季物候推迟的趋势,草原和草甸则表现为提前-推迟-提前的趋势。应用偏最小二乘(Partial Least Squares)回归分析了该区域植被物候与气候因子之间的关系,结果表明:春季温度与阔叶林、针叶林和草甸春季物候负相关,前一年冬季温度与草原春季物候正相关,降水与植被春季物候的关系有点复杂;4种植被秋季物候与夏季温度均呈正相关,除草原外,其余3种植被秋季物候均与夏季降水负相关。植被春季物候可能主要受温度影响,而秋季物候很可能主要受降水控制。     

Local Polynomial Estimation of Heteroscedasticity in a Multivariate Linear Regression Model and Its Applications in Economics

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.     

Determining alternative models for vegetation response analysis: a non-parametric approach

Abstract. Vegetation models based on multiple logistic regression are of growing interest in environmental studies and decision making. The relatively simple sigmoid Gaussian optimum curves are most common in current vegetation models, although several different other response shapes are known. However, improvements in the technical means for handling statistical data now facilitate fast and interactive calculation of alternative complex, more data-related, non-parametric models. The aim in this study was to determine whether, and if so how often, a complex response shape could be more adequate than a linear or quadratic one. Using the framework of Generalized Additive Models, both parametric (linear and quadratic) and non-parametric (smoothed) stepwise multiple logistic regression techniques were applied to a large data set on wetlands and water plants and to six environmental variables: pH, chloride, orthophosphate, inorganic nitrogen, thickness of the sapropelium layer and depth of the water-body. All models were tested for their goodness-of-fit and significance. Of all 156 generalized additive models calculated, 77 % were found to contain at least one smoothed predictor variable, i.e. an environmental variable with a response better fitted by a complex, non-parametric, than by a linear or quadratic parametric curve. Chloride was the variable with the highest incidence of smoothed responses (48 %). Generally, a smoothed curve was preferable in 23 % of all species-variable correlations calculated, compared to 25 % and 18 % for sigmoid and Gaussian shaped curves, respectively. Regression models of two plant species are presented in detail to illustrate the potential of smoothers to produce good fitting and biologically sound response models in comparison to linear and polynomial regression models. We found Generalized Additive Modelling a useful and practical technique for improving current regression-based vegetation models by allowing for alternative, complex response shapes.     

Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere

The inter-annual shift of spring vegetation phenology relative to per unit change of preseason temperature, referred to as temperature sensitivity (days °C⁻¹), quantifies the response of spring phenology to temperature change. Temperature sensitivity was found to differ greatly among vegetation from different environmental conditions. Understanding the large-scale spatial pattern of temperature sensitivity and its underlying determinant will greatly improve our ability to predict spring phenology. In this study, we investigated the temperature sensitivity for natural ecosystems over the North Hemisphere (north of 30°N), based on the vegetation phenological date estimated from NDVI time-series data provided by the Advanced Very High Resolution Radiometer (AVHRR) and the corresponding climate dataset. We found a notable longitudinal change pattern with considerable increases of temperature sensitivity from inlands to most coastal areas and a less obvious latitudinal pattern with larger sensitivity in low latitude area. This general spatial variation in temperature sensitivity is most strongly associated with the within-spring warming speed (WWS; r = 0.35, p < 0.01), a variable describing the increase speed of daily mean temperature during spring within a year, compared with other factors including the mean spring temperature, spring precipitation and mean winter temperature. These findings suggest that the same magnitude of warming will less affect spring vegetation phenology in regions with higher WWS, which might partially reflect plants’ adaption to local climate that prevents plants from frost risk caused by the advance of spring phenology. WWS accounts for the spatial variation in temperature sensitivity and should be taken into account in forecasting spring phenology and in assessing carbon cycle under the projected climate warming.     

A comparative study of satellite and ground-based phenology

Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.     

Codominant water control on global interannual variability and trends in land surface phenology and greenness

Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus, we assessed the performance of a new developed phenology module within the LPJmL (Lund–Potsdam–Jena managed Lands) DGVM with a comprehensive ensemble of three satellite data sets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on interannual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season interannual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming‐induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, interannual variability and trends are dominantly controlled by water availability and land‐use and land‐cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated with a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a codominant control for start of growing season and peak greenness trends at the global scale.     

气候变化背景下橡胶树物候研究进展

橡胶树(Heveabrasiliensis)是广布于热带地区的经济林木，是战略物资天然橡胶的主要来源，其物候学的研究对胶园生产管理和评估热带地区植被对全球气候变化的响应方面具有重要意义。早期的物候研究主要服务于苗木繁育、割胶规划和抗逆栽培等生产应用；利用遥感监测植被物候日趋成熟，已广泛应用于橡胶树并成为主流的物候监测方法；橡胶树物候具有明显的时空异质性，对气候变化的响应较为复杂，其中温度和降水是关键影响因子，同时内因(品系、基因和树龄等)和外因(种植密度、地理位置和农业措施等)也共同影响了其物候。为更好服务天然橡胶产业的可持续发展和热区气候变化科学研究，未来的橡胶树物候研究应重点关注多源遥感数据的协同重建、物候指标提取算法的普适化和遥感预测模型的精准化。该文系统梳理了橡胶树物候的监测方法、服务价值、时空格局，提出了存在问题及未来研究方向。     

1982-2013年内蒙古地区植被物候对干旱变化的响应

气候变化引起的植被物候变化正在大幅度改变生态系统,研究植被物候对干旱的响应对保护内蒙古的生态系统具有重要意义。根据1：100万植被区划,把内蒙古划分为8个植被分区,利用多时间尺度气象标准化降水蒸散指数（SPEI）和NDVI3g时序数据所反演的物候指标,分析内蒙古植被物候的时空变化及其对干旱的响应规律。结果显示：1）在1982年至2013年间,内蒙古植被受到不同时间尺度下干旱的高度控制,尤其是时间尺度干旱的影响（SPEI-3）;2）对于整个研究区,生长季开始（SOS）呈提前趋势,生长季结束（EOS）呈延后趋势,生长季长度（LOS）呈延长趋势,像元比例分别为63.79%、59.77%和62.83%;3）内蒙古除荒漠植被类型地区外,同年春季和夏季初期干旱对SOS均具有延迟作用,同年秋季干旱对EOS均具有延迟作用 ;4） 不同植被类型对干旱强度指数的响应程度存在差异,响应程度集中在-10d/0.1-10d/0.1（例如,1d/0.1表示干旱强度指数每增大0.1,会导致物候指数延迟1 d,而-1d/0.1表示干旱强度指数每增大0.1,会导致物候指数提前1 d）。     

秦岭山区植被春季物候的海拔敏感性

植被物候作为自然界规律性、周期性的现象,对自然环境尤其是气候变化有着重要的指示作用,研究其时空变化特征对陆地植被生态环境监测具有重要意义。本研究采用Savitzky-Golay滤波法重建秦岭山区2001—2018年MODIS增强植被指数时间序列影像,利用动态阈值法提取研究区春季物候信息(返青期),并对返青期多年平均值和年际变化与海拔、坡度进行相关分析。结果表明: 海拔每升高100 m,植被返青期推迟1.82 d;返青期的年际变化趋势主要集中在0~5 d·(10 a)^-1。其中,呈推迟趋势的像元主要分布在低海拔地区,呈提前趋势的像元主要分布在高海拔地区。高海拔地区返青期的年际变化比低海拔地区复杂;秦岭山区植被返青期存在南北差异。北坡植被返青期多年平均值较南坡早2.9 d,南坡植被返青期的推迟程度大于北坡。南北坡植被返青期的年际变化在低海拔地区呈推迟趋势,且南北坡相差不大,而提前趋势在中高海拔地区存在显著差异。     

Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006

Aim We intend to characterize and understand the spatial and temporal patterns of vegetation phenology shifts in North America during the period 1982–2006. Location North America. Methods A piecewise logistic model is used to extract phenological metrics from a time‐series data set of the normalized difference vegetation index (NDVI). An extensive comparison between satellite‐derived phenological metrics and ground‐based phenology observations for 14,179 records of 73 plant species at 802 sites across North America is made to evaluate the information about phenology shifts obtained in this study. Results The spatial pattern of vegetation phenology shows a strong dependence on latitude but a substantial variation along the longitudinal gradient. A delayed dormancy onset date (0.551 days year^?1, P= 0.013) and an extended growing season length (0.683 days year^?1, P= 0.011) are found over the mid and high latitudes in North America during 1982–2006, while no significant trends in greenup onset are observed. The delayed dormancy onset date and extended growing season length are mainly found in the shrubland biome. An extensive validation indicates a strong robustness of the satellite‐derived phenology information. Main conclusions It is the delayed dormancy onset date, rather than an advanced greenup onset date, that has contributed to the prolonged length of the growing season over the mid and high latitudes in North America during recent decades. Shrublands contribute the most to the delayed dormancy onset date and the extended growing season length. This shift of vegetation phenology implies that vegetation activity in North America has been altered by climatic change, which may further affect ecosystem structure and function in the continent.     

Land surface phenology and temperature variation in the International Geosphere–Biosphere Program high-latitude transects

The International Geosphere–Biosphere Program has delineated five study areas that form a northern high‐latitude network for the analyses of vegetation and carbon dynamics. We examined the magnitude and significance of changes in the land surface phenologies of ecoregions within these transects using the NASA Pathfinder Advanced Very High‐Resolution Radiometer Land dataset. We applied the seasonal Mann–Kendall (SMK) trend test, a robust and nonparametric approach, to determine the significance of trends in the normalized difference vegetation index (NDVI) over the five transects. The SMK trend test provides an important alternative over the frequently used but unreliable trend analysis based on linear regression. In addition, we modeled the land surface phenology using quadratic or nonlinear spherical models to relate the NDVI data to accumulated growing degree‐days (base 0°C). Nonlinear spherical models parsimoniously describe the green‐up dynamics in taiga and tundra ecoregions. Models for each ecoregion within each transect were fitted separately for two time periods (1985–1988 and 1995–1999) and their parameter coefficient estimates were compared. In 10 of 24 ecoregions that comprise 72% of the land area in the transects, the date of the peak NDVI value was significantly earlier (range 2–18 days) in the second study period than in the first study period. This progression was more pronounced in North America than in Siberia (weighted average of 9.3 vs. 6.3 days earlier). Understanding of what constitutes significant change in land surface phenology amidst background variation is a critical component of global change science. A diversity of datasets, techniques, and study areas has led to a range of conclusions about boreal phenology. We discuss statistical pitfalls in standard analyses and offer a framework to conduct statistically reliable change assessments of land surface phenologies.     

Land Surface Phenology in the Tropics: The Role of Climate and Topography in a Snow-Free Mountain

Leaf phenology represents a major temporal component of ecosystem functioning, and understanding the drivers of seasonal variation in phenology is essential to understand plant responses to climate change. We assessed the patterns and drivers of land surface phenology, a proxy for leafing phenology, for the meridional Espinhaço Range, a South American tropical mountain comprising a mosaic of savannas, dry woodlands, montane vegetation and moist forests. We used a 14-year time series of MODIS/NDVI satellite images, acquired between 2001 and 2015, and extracted phenological indicators using the TIMESAT algorithm. We obtained precipitation data from the Tropical Rainfall Measuring Mission, land surface temperature from the MODIS MOD11A2 product, and cloud cover frequency from the MODIS MOD09GA product. We also calculated the topographic wetness index and simulated clear-sky radiation budgets based on the SRTM elevation model. The relationship between phenology and environmental drivers was assessed using general linear models. Temporal displacement in the start date of the annual growth season was more evident than variations in season length among vegetation types, indicating a possible temporal separation in the use of resources. Season length was inversely proportional to elevation, decreasing 1.58 days per 100 m. Green-up and senescence rates were faster where annual temperature amplitude was higher. We found that water and light availability, modulated by topography, are the most likely drivers of land surface phenology in the region, determining the start, end and length of the growing season. Temperature had an important role in determining the rates of leaf development and the strength of vegetation seasonality, suggesting that tropical vegetation is also sensitive to latitudinal temperature changes, regardless of the elevational gradient. Our work improves the current understanding of phenological strategies in the seasonal tropics and emphasizes the importance of topography in shaping light and water availability for leaf development in snow-free mountains.     

气候变化和人类活动对祁连山国家公园植被净初级生产力的定量影响

祁连山国家公园作为西北地区重要的生态安全屏障和水源涵养地,研究其植被变化对西北地区的生态安全具有重要意义。基于2000—2019年祁连山国家公园的MOD17A3遥感数据,利用一元线性回归、偏相关分析、多元线性回归和残差分析等方法,分析了祁连山国家公园植被净初级生产力(NPP)的时空态势及其与降水、气温和人类活动的相关性,在此基础上量化气候变化和人类活动对植被NPP的影响。结果表明：(1)2000—2019年祁连山国家公园植被NPP整体呈波动上升趋势,且空间上呈东高西低的分布格局,其多年平均值为113.14 g C m^-2 a^-1,年均增长量达1.41 g C m^-2 a^-1;(2)植被NPP与降水、气温均呈正相关,其中降水对植被NPP影响更为显著;(3)人类活动区植被NPP总体呈增加趋势,与2016年相比,2019年人类活动区植被NPP增加的面积占87%,植被NPP降低的面积占13%;(4)在植被恢复区,气候变化和人类活动对植被恢复分别解释了92%和8%;在植被退化区,气候变化和人类活动对植被退化分...     

近十年的国际植被物候研究文献发展态势分析

基于Web of Science数据库的检索结果,利用Histcite、Bibexcel和Netdraw对国际植被物候研究文献进行计量分析。结果表明:1 060篇相关文献刊载于288种期刊,平均载文3.68篇; 共分33个研究方向; 3 380位作者(第一作者904位)、69个国家或地区、1 172个组织参与; 国际合作发文310篇,占比29.25%; 其中中美合作居第一(19次)。分析还表明:2002～2007年是该领域重要发展期; 国际植被物候研究热点主要集中在基于气候(climate)-物候的田间局地观测和基于遥感(remote sensing)的大尺度物候研究。     

盐池县2000-2012年植被变化及其驱动力

荒漠草原区的植被对防治荒漠化、维护生态屏障具有决定性作用,宁夏盐池县作为其典型代表,近13年的植被变化深受气候变化和人类活动的综合影响。基于MODIS NDVI等数据,运用趋势分析、经验模态分解和空间叠置分析等方法,对盐池县2000—2012年的植被动态变化进行研究,结果表明:(1)2000—2012年盐池县NDVI在0.2—0.4之间呈波动上升趋势,上升幅度为0.078/10 a,上升趋势显著;总体来说,植被稳定性低,年际间波动或转换频繁、幅度大;(2)NDVI的波动分量与残余分量方差贡献率各占50%,且NDVI波动呈减弱趋势。促使NDVI波动的主控因子是年降水量,但其影响在减弱;(3)推动NDVI趋势性上升的主要因素是土地利用方式改善和类型变化,但土地利用方式改善对NDVI的贡献远远大于土地利用类型变化对NDVI的贡献。因此,荒漠草原区的生态改善应以保护为主,辅之以必要的生态重建,走以适度开发带动整体保护的道路。