日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_GPP)为第63天,生长季结束时间(EOS_GPP)为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_GPP31天,植被指数EOS滞后EOS_GPP10—17天。虽然基于3种遥...     

基于MODIS-EVI数据和Symlet11小波识别东北地区水稻主要物候期

作物物候信号能够反映温度和降水等变化对植被生长的影响,是进行农作物动态分析和田间管理的重要依据。基于2008年EOS-MODIS多时相卫星遥感数据,研究了我国东北地区水稻的主要物候期的识别方法。首先提取研究区24个农业气象观测站所在位置的MODIS-EVI(Enhanced Vegetation Index,增强型植被指数)指数的时间序列;同时利用小波滤波消除时间序列上的噪音,小波滤波选用函数包含Daubechies(7-20),Coiflet(3-5)和Symlet(7-15)共26种类型。然后根据水稻移栽期、抽穗期和成熟期在EVI时间序列上的表现特征来识别水稻主要物候期。最后与东北地区24个站点水稻物候观测资料对比并分析误差。结果表明,Symlet11小波滤波的效果最好,其移栽期识别结果的误差绝大部分在±16 d,抽穗期和成熟期识别结果的误差在±8 d。表明通过此方法可以较好地识别东北水稻主要物候期,并可进一步应用到整个东北地区水稻的物候空间分布和时间变化特征研究上。     

Ecology of a community of mammals in a seasonailly dry forest in Roraima, Brazilian Amazon

A community of middle-sized and larger mammals was studied in a seasonally dry forest in the far north of the Brazilian Amazon. Diurnal and nocturnal surveys were carried out through the linetransect method, in 5 different forest types along a 10-km transect. Data were collected an density, biomass, and use of the forest types, and forest strata by the mammals. The terrestrial community of mammals was more abundant than the arboreal one, with ungulates contributing to the bulk of the biomass, as a result of Maracá being highly seasonal Overall densities were lower than in other sites in the neotropics, varying from 90.2 ind/km² in mixed forest, to 159.9 ind/km² in Terra Firme forest, whereas biomass, due to the contribution of large mammals, was much higher (2613.2 kg/km² in mixed forest, and 4351.6 kg/km² in Terra Firme forest). This study confirms that the animals surviving in larger numbers in these highly seasonal forests, where food productivity may be very low during the dry season, are those that have larger home ranges and travel longer distances in search of food.     

Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna

Interactions between trees and grasses that influence leaf area index (LAI) have important consequences for savanna ecosystem processes through their controls on water, carbon, and energy fluxes as well as fire regimes. We measured LAI, of the groundlayer (herbaceous and woody plants <1-m tall) and shrub and tree layer (woody plants >1-m tall), in the Brazilian cerrado over a range of tree densities from open shrub savanna to closed woodland through the annual cycle. During the dry season, soil water potential was strongly and positively correlated with grass LAI, and less strongly with tree and shrub LAI. By the end of the dry season, LAI of grasses, groundlayer dicots and trees declined to 28, 60, and 68% of mean wet-season values, respectively. We compared the data to remotely sensed vegetation indices, finding that field measurements were more strongly correlated to the enhanced vegetation index (EVI, r ²=0.71) than to the normalized difference vegetation index (NDVI, r ²=0.49). Although the latter has been more widely used in quantifying leaf dynamics of tropical savannas, EVI appears better suited for this purpose. Our ground-based measurements demonstrate that groundlayer LAI declines with increasing tree density across sites, with savanna grasses being excluded at a tree LAI of approximately 3.3. LAI averaged 4.2 in nearby gallery (riparian) forest, so savanna grasses were absent, thereby greatly reducing fire risk and permitting survival of fire-sensitive forest tree species. Although edaphic conditions may partly explain the larger tree LAI of forests, relative to savanna, biological differences between savanna and forest tree species play an important role. Overall, forest tree species had 48% greater LAI than congeneric savanna trees under similar growing conditions. Savanna and forest species play distinct roles in the structure and dynamics of savanna–forest boundaries, contributing to the differences in fire regimes, microclimate, and nutrient cycling between savanna and forest ecosystems.     

基于日光诱导叶绿素荧光的北半球森林物候研究

植被物候是反映植被生长规律的重要指标, 对气候的反馈具有重要意义。日光诱导叶绿素荧光(SIF)通过复杂的能量耗散机制与光合作用相关联, 提供了从空间直接探测大范围植被物候的可能性。为了探究气候变化背景下SIF反演不同森林类型物候的适用性, 该文以北半球35个全球通量网(FLUXNET)森林站点为研究对象, 利用2007-2014年SIF值和总初级生产力(GPP)通过双逻辑生长模型和动态阈值法来估算3种典型森林类型的物候, 并采用相关性分析等方法评价SIF在估算不同森林类型物候时的差异性。主要结果为: 1) SIF对生长季开始时间(SOS)的估算精度高于生长季结束时间(EOS); 2) SIF能够更准确地估算混交林(MF)的SOS, 但是不能精确追踪落叶阔叶林(DBF)和常绿针叶林(ENF)的SOS; 3)春季季前短波辐射是驱动SOS的主要气候因素。综上, 建议在将来的研究中将SIF数据与其他遥感指数整合, 应用于不同植物类型的物候监测。     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

The interaction between island geomorphology and environmental parameters drives Adélie penguin breeding phenology on neighboring islands near Palmer Station,Antarctica

Despite many studies on Adélie penguin breeding phenology, understanding the drivers of clutch initiation dates (CIDs, egg 1 lay date) is limited or lacks consensus. Here, we investigated Adélie penguin CIDs over 25 years (1991–2016) on two neighboring islands, Torgersen and Humble (<1 km apart), in a rapidly warming region near Palmer Station, Antarctica. We found that sea ice was the primary large‐scale driver of CIDs and precipitation was a secondary small‐scale driver that fine‐tunes CID to island‐specific nesting habitat geomorphology. In general, CIDs were earlier (later) when the spring sea ice retreat was earlier (later) and when the preceding annual ice season was shorter (longer). Island‐specific effects related to precipitation and island geomorphology caused greater snow accumulation and delayed CIDs by ~2 days on Torgersen compared to Humble Island. When CIDs on the islands were similar, conditions were mild with less snow across breeding sites. At Torgersen Island, the negative relationship between CID and breeding success highlights detrimental effects of delayed breeding and/or snow on penguin fitness. Past phenological studies reported a relationship between air temperature and CID, assumed to be related to precipitation, but we found air temperature was more highly correlated to sea ice, revealing a misinterpretation of temperature effects. Finally, contrasting trends in CIDs based on temporal shifts in regional sea ice patterns revealed trends toward earlier CIDs (4–6 day advance) from 1979 to 2009 as the annual ice season shortened, and later CIDs (7–10 day delay) from 2010 to 2016 as the annual ice season lengthened. Adélie penguins tracked environmental conditions with flexible breeding phenology, but their life history remains vulnerable to subpolar weather conditions that can delay CIDs and decrease breeding success, especially on landscapes where geomorphology facilitates snow accumulation.     

Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data

Recent studies using both field measurements and satellite-derived-vegetation indices have demonstrated that global warming is influencing vegetation growth and phenology. To accurately predict the future response of vegetation to climate variation, a thorough understanding of vegetation phenological cycles and their relationship to temperature and precipitation is required. In this paper, vegetation phenological transition dates identified using data from the moderate-resolution imaging spectroradiometer (MODIS) in 2001 are linked with MODIS land surface temperature (LST) data from the northern hemisphere between 35°N and 70°N. The results show well-defined patterns dependent on latitude, in which vegetation greenup gradually migrates northward starting in March, and dormancy spreads southward from late September. Among natural vegetation land-cover types, the growing-season length for forests is strongly correlated with variation in mean annual LST. For urban areas, the onset of greenup is 4–9 days earlier on average, and the onset of dormancy is about 2–16 days later, relative to adjacent natural vegetation. This difference (especially for urban vs. forests) is apparently related to urban heat island effects that result in both the average spring temperature and the mean annual temperature in urban areas being about 1–3°C higher relative to rural areas. The results also indicate that urban heat island effects on vegetation phenology are stronger in North America than in Europe and Asia. Finally, the onset of forest greenup at continental scales can be effectively described using a thermal time-chilling model, which can be used to infer the delay or advance of greenup onset in relation to climatic warming at global scale.     

基于多种遥感植被指数、叶绿素荧光与CO2通量数据的温带针阔混交林物候特征对比分析

植被物候学作为研究植被与环境条件相互作用的科学,在全球气候变化的大背景下已成为国际热点研究领域,其中森林植被在调节全球碳平衡、维护全球气候稳定的过程中有着至关重要的作用。随着遥感技术的发展,多种遥感指数被应用到森林植被物候研究中,其中以MODIS NDVI和EVI应用最为广泛,而叶绿素荧光(SIF)作为植被光合作用的"探针"也被广泛应用于森林植被物候研究中。为了探究3种指数在森林植被物候研究中的差异与特性,本文以长白山温带红松阔叶林通量观测站为研究区域,采用模型拟合结合动态阈值法提取2007—2013森林物候特征参数,并使用通量数据(总初级生产力GPP)进行验证。结果表明:NDVI与EVI、SIF相比,表现为生长季开始时间与结束时间的明显提前和滞后,与GPP数据偏差较大,且夏季生长季峰期曲线形态过宽且平坦,无法较好反映生长季变化特征;EVI相较于NDVI有所改善,整体变化趋势与SIF、GPP基本吻合,但依然存在秋季衰减时间稍迟于SIF与GPP的问题;SIF虽然存在夏季骤降现象,但依然与GPP数据一致性最好,可以较好反映出森林植被季节变化特征。SIF数据与植被光合作用的紧密关联使其在植被物候研究中具有优于植被指数的准确性,并随着遥感平台的增加和反演方法的改善,将会在多尺度、多类型的植被物候监测中发挥更加重要的作用。     

2000-2019年京津冀地区植被覆盖状况变化及驱动因素

近20年来中国和印度通过土地利用活动改变地表覆盖使植被变得更绿,京津冀地区是植被变得更绿的典型地区。收集京津冀地区2000-2019年MODIS增强型植被指数（EVI）、植被覆盖百分比数据,以及年平均温度和降水量等数据,分析该区近20年来自然植被和农田植被EVI变化过程和趋势,揭示其变化的驱动因素,结果显示2000-2019年京津冀地区自然植被和农田植被EVI显著增加,自然植被EVI增加速率是农田植被的1.8倍。99.51%的自然植被和96.95%的农田植被生长状况改善。2000-2019年京津冀地区自然植被EVI与年平均温度和年降水量相关性不显著。农田植被EVI与年平均温度显著相关,与年降水量相关性不显著。农田灌溉和年平均温度变化是农田植被EVI显著增加的主要驱动因素。近20年京津冀地区通过实施以造林为主的生态建设工程,自然植被生长覆盖状况呈现极显著变好。同时森林植被比非森林植被覆盖百分比增加趋势更明显。以造林为主的生态建设工程是京津冀地区自然植被生长覆盖状况显著变好的主要驱动因素。     

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。     

Modeling the Sensitivity of the Seasonal Cycle of GPP to Dynamic LAI and Soil Depths in Tropical Rainforests

The seasonality of pan-tropical wet forests has been highlighted by recent remote sensing and eddy flux measurements that have recorded both increased and sustained dry-season gross primary productivity (GPP). These observations suggest that wet tropical forests are primarily light limited and that the mechanisms for resilience to drought and projected climate change must be considered in ecosystem model development. Here we investigate two proposed mechanisms for drought resilience of tropical forests, deep soil water access and the seasonality of phenology, using the LPJmL Dynamic Global Vegetation Model. We parameterize a new seasonal phenology module for tropical evergreen trees using remotely sensed leaf area index (LAI) and incoming solar radiation data from the Terra Earth Observing System. Simulations are evaluated along a gradient of dry-season length (DSL) in South America against MODIS GPP estimates. We show that deep soil water access is critical for maintaining dry-season GPP, whereas implementing a seasonal LAI did not enhance simulated dry-season GPP. The Farquhar-Collatz photosynthesis scheme used in LPJmL optimizes leaf nitrogen allocation according to light conditions, causing maximum photosynthetic capacity in the dry season. High LAI, characteristic of tropical forests, also dampens the seasonal amplitude of the fraction of photosynthetically active radiation (FPAR). Given the relatively high uncertainty in tropical phenology observations and their corresponding proximate drivers, we recommend that ecosystem model development focus on belowground processes. An improved representation of soil depths and rooting distributions is necessary for modeling the dynamics of dry-season tropical forest functioning and may have important impacts for modeling tropical forest vulnerability to climate change. Author Contributions  BP conceived of the study, analyzed data, and wrote the paper. UH designed study and contributed new methods. WC designed study and contributed to paper.     

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan‐tropical belt (30°N–30°S). We analyzed decadal‐scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982–2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid‐1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time‐dependent regression parameters to study the time evolution of NDVI–climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature‐induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global‐scale effects of climate warming and associated moisture stresses.     

Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ¹⁸O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ¹⁸O are highly correlated and thus the EVI is a good predictor of precipitated δ¹⁸O. We then test the predictability of our EVI-δ¹⁸O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ¹⁸O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ¹⁸O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape.     

2000—2018年黄河流域生长季植被指数变化及其对气候因子的响应

黄河流域位于我国干旱、半干旱地区,生态环境脆弱,探究其植被指数变化和对气候因子的响应对该地区生态建设具有重要意义。基于黄河流域2000—2018年MODIS归一化植被指数、增加型植被指数和气象数据,利用最大值合成法、趋势分析和相关分析等方法,分析了两种植被指数的时空变化特征及受气候因子的影响机制,探讨了NDVI与EVI在反映植被变化和对气候因子响应的差异。结果表明：2000—2018年,黄河流域地区植被NDVI、EVI分别以0.059/10a、0.038/10a的变化率增加,空间上以显著改善为主,面积占比分别为77.13%和75.27%,大多分布在1000—1500 m海拔处,中游地区改善较为良好,林地改善率最高。显著退化区域较小,主要分布在巴颜喀拉山西北部、西宁市、银川市、包头市、呼和浩特市、太原市、西安市及关中盆地和洛阳市周边,建设用地退化率最高。在生长季期间,植被指数变化与气温和降水以正相关为主,气温滞后时间为1个月,降水滞后时间为3个月,都为草地最为相关;与辐射之间为负相关,滞后时间为3个月,其中林地最为相关。在0.05显著性检验水平下,驱动黄河流域生长季植被变化的主要气候因子...     

青藏高原植被样带地上部分生物量的分布格局（英文）

 实测了青藏高原植被样带22个地区不同植被类型的地上部分生物量并进行了格局分析。对于未受人为干扰的以常绿阔叶林为基带的亚高山天然植被,随着海拔升高,地上生物量呈递增趋势,在一定海拔高度达最大,海拔继续升高地上生物量则迅速下降。这一垂直分异规律在一定程度上反映了全球地带性森林植被最大生物量分布的纬向分异性。基于Weber定律的回归分析表明,地上生物量与水热因子的相关关系可用Logistic函数拟合,1月平均气温、7月平均气温、年平均气温、年降水量及其组合因子可解释高原植被样带地上生物量变化的28%～53%,其中年降水量及其同年平均气温的组合与地上生物量的相关性最高（R2为0.46～0.53,p<0.001）。但是,年降水量和平均气温的变化不足以解释西藏色齐拉山暗针叶林具有最高的地上生物量。我们认为,自然植被地上部分生物量的分布格局受到更为复杂的气候因子的制约,例如太阳辐射、湿度、风、水分和能量平衡等。     

Patterns in leaf traits of leguminous and non-leguminous dominant trees along a rainfall gradient in Ghana

Aims Both dominance distribution of species and the composition of the dominant species determine the distribution of traits within community. Leaf carbon (C) and nitrogen (N) isotopic composition are important leaf traits, and such traits of dominant species are associated with ecosystem C, water and N cycling. Very little is known how dominant species with distinct traits (e.g. N-fixing leguminous and non-leguminous trees) mediate resource utilization of the ecosystems in stressful environment.Methods Leaves of 81 dominant leguminous and non-leguminous trees were collected in forest (moist semi-deciduous and dry semi-deciduous ecosystems) and savanna (costal savanna, Guinean savanna and west Sudanian savanna ecosystems) areas and the transitional zone (between the forest and the savanna) along the transect from the south to the north of Ghana. We measured leaf traits, i.e. leaf δ 13 C, leaf δ 15 N, leaf water content, leaf mass per area (LMA) and C and N concentration. Correlation analyses were used to examine trait–trait relationships, and relationships of leaf traits with temperature and precipitation. We used analysis of covariance to test the differences in slopes of the linear regressions between legumes and non-legumes.Important findings Leaf δ 13 C, δ 15 N, leaf water content and LMA did not differ between leguminous and non-leguminous trees. Leaf N concentration and C:N ratio differed between the two groups. Moreover, leaf traits varied significantly among the six ecosystems. δ 13 C values were negatively correlated with annual precipitation and positively correlated with mean annual temperature. In contrast, leaf δ 15 N of non-leguminous trees were positively correlated with annual precipitation and negatively correlated with mean annual temperature. For leguminous trees, such correlations were not significant. We also found significant coordination between leaf traits. However, the slopes of the linear relationships were significantly different between leguminous and non-leguminous trees. Our results indicate that shifts in dominant trees with distinct water-use efficiency were corresponded to the rainfall gradient. Moreover, leguminous trees, those characterized with relative high water-use efficiency in the low rainfall ecosystems, were also corresponded to the relative high N use efficiency. The high proportion of leguminous trees in the savannas is crucial to mitigate nutrient stress.     

基于MODIS-EVI的西南地区植被覆盖时空变化及驱动因素研究

基于MODIS-EVI和气象数据,利用最大值合成法、像元二分模型、趋势分析和相关分析等方法,探讨了西南地区2001-2015年植被覆盖时空变化特征及其对气候因子的响应,并分析了温度和降水对植被覆盖时空变化的驱动作用。结果表明：（1）2001-2015年,西南地区植被EVI以0.1%/a的变化率呈波动增加趋势,但空间异质性显著,呈现出从东南向西北逐渐递减的趋势;（2）西南地区以高和极高植被覆盖度为主,极低植被覆盖度区域约占研究区总面积的8.6%,植被覆盖度增加的区域集中分布在广西省北海-钦州、贵州省邵通-毕节-遵义、四川省广元-广安以及西藏那曲等地区,植被覆盖度呈减少趋势区域主要集中在西藏拉萨-阿里地区和四川成都-阿坝州-甘孜州等地区;（3）植被EVI与同期温度和降水相关性较好,均以正相关为主。在0.05显著水平下,受降水驱动的区域呈斑块状分布在西藏自治区和青海省交界处,以及云南和广西部分地区,约占研究区总面积的3.4%;受温度驱动的区域零星分布在各省、自治区,约占研究区总面积的1.6%;受温度和降水共同驱动的区域约占研究区总面积的7.2%,主要分布在西藏自治区的阿里地区北部,青海省的三江源地区以及四川和贵州两省交界处的小部分地区;西南地区大部分区域的植被EVI指数变化表现为非气候因素驱动。     

Functional differences between summer and winter season rain assessed with MODIS‐derived phenology in a semi‐arid region

Questions: We asked several linked questions about phenology and precipitation relationships at local, landscape, and regional spatial scales within individual seasons, between seasons, and between year temporal scales. (1) How do winter and summer phenological patterns vary in response to total seasonal rainfall? (2) How are phenological rates affected by the previous season rainfall? (3) How does phenological variability differ at landscape and regional spatial scales and at season and inter‐annual temporal scales? Location: Southern Arizona, USA. Methods: We compared satellite‐derived phenological variation between 38 distinct 625‐km² landscapes distributed in the northern Sonoran Desert region from 2000 to 2007. Regression analyses were used to identify relationships between landscape phenology dynamics in response to precipitation variability across multiple spatial and temporal scales. Results: While both summer and winter seasons show increases of peak greenness and peak growth with more precipitation, the timing of peak growth was advanced with more precipitation in winter, while the timing of peak greenness was advanced with more precipitation in summer. Surprisingly, summer maximum growth was negatively affected by winter precipitation. The spatial variations between summer and winter phenology were similar in magnitude and response. Larger‐scale spatial and temporal variation showed strong differences in precipitation patterns; however the magnitudes of phenological spatial variability in these two seasons were similar. Conclusions: Vegetation patterns were clearly coupled to precipitation variability, with distinct responses at alternative spatial and temporal scales. Disaggregating vegetation into phenological variation, spanning value, timing, and integrated components revealed substantial complexity in precipitation‐phenological relationships.