Giant tortoise habitats under increasing drought conditions on Aldabra Atoll—Ecological indicators to monitor rainfall anomalies and related vegetation activity

Aldabra Atoll has the largest population of giant tortoises (Aldabrachelys gigantea) in the world. As such an important biological resource, it is necessary to understand how the effects of climate change will impact this keystone species; in particular the frequency of drought, which is likely to affect tortoise habitat. To assess whether drought frequency has changed over the last 50 years on Aldabra, we calculated the standardized precipitation index (SPI) to identify drought periods using monthly rainfall data collected during 1969–2013. We found that drought frequency has increased to more than six drought months per year today compared with about two months per year in the 1970s (t = 2.884, p = 0.006). We used MODIS normalized difference vegetation index (NDVI) as a proxy for vegetation activity, to determine how vegetation has responded to the changing drought frequency between 2000 and 2013. We found that Aldabra’s vegetation is highly responsive to changes in rainfall: anomalies in long-term mean monthly NDVI across Aldabra were found to decrease below the mean during most drought periods and increase above the mean during most non-drought periods. To investigate the response of tortoise habitat to rainfall, we extracted mean NDVI anomalies for three key habitat types. Open mixed scrub and grasslands, the preferred habitat of tortoises, showed the greatest decrease in vegetation activity during drought periods, and the greatest increase in average greenness during non-drought periods. Recent analysis has shown vegetation changes on Aldabra in recent decades. If these changes are caused by decreased precipitation, then the increased frequency of drought could impact the tortoise population, in both the short and long term, by limiting the quality and quantity of forage and/or shade availability within favoured habitats, and by changing the habitat composition across the atoll.     

植被对不同时间尺度干旱事件的响应特征及成因分析

利用标准化降雨蒸散发指数(SPEI)与归一化植被指数(NDVI)系统研究了中国不同区域、不同土地利用类型的植被对不同时间尺度干旱事件的响应特征,并对成因做出探讨。研究表明:(1)全国大部分区域NDVI与SPEI呈显著正相关,表明中国大部分区域植被生物量变化受干旱时空特征的影响。而沿北纬30度附近的长江流域区域,尤其是长江流域东南部、珠江流域下游等降水相对丰沛区域;黑龙江东北部及长白山地区、四川西部等高寒区域,NDVI与SPEI表现出弱相关性,受干旱影响较小;(2)多年平均水平衡是影响植被对干旱响应的关键因素,土壤水分变化是植被活力与生物量变化的关键影响因子。多年平均日照时数较长的区域,植被变化受干旱影响较大。从对干旱影响敏感性程度来讲,越是水量丰沛的区域,植被受干旱的影响越小,其中,草地对干旱的影响最为敏感,其次为灌木与森林。     

云南省植被NDVI时间变化特征及其对干旱的响应

基于云南省74个气象站点的1997—2012年逐日降水资料和逐旬SPOT-NDVI值,利用标准化降水蒸散指数(SPEI)多尺度分析了云南省干旱时间和强度演变与NDVI时间动态特征及其相关性分析,进而探讨气候变化对植被的影响。结果表明,1999—2013年云南省年平均NDVI值和年最大NDVI值均呈现波浪式的发展趋势,其趋势线斜率分别为0.0017和0.0011;NDVI年内各月变化情况大体上相同;不同季节NDVI的年际变化特征呈现出显著差异。1997—2012年不同时间尺度SPEI均体现出干旱化加剧的趋势,并随SPEI的时间尺度增大而增大;3个月尺度的SPEI值(SPEI3)结果表明,各月的变化呈现先增大后减小的趋势;SPEI3反映出多年季节水平的干旱强度为:冬季秋季春季夏季。总体上,云南省的年均NDVI与SPEI的相关性极弱,年最大NDVI与SPEI呈正相关;多年月均NDVI与不同尺度SPEI的相关性较强且存在滞后性;不同季节NDVI与SPEI的相关性及滞后性有较大差异,其中冬季NDVI、秋季NDVI与其当年当季SPEI的负相关性较强。     

西南干旱对哀牢山常绿阔叶林凋落物及叶面积指数的影响

为探讨2010年初西南干旱对这一地区原生植被林冠和凋落物量的影响,以及这一地区凋落物量和气候条件之间的关系,对比研究了哀牢山亚热带常绿阔叶林2010年和一般年份的凋落物特征以及各层的叶面积指数,并分析了凋落物量和气候因子之间的关系.2010年凋落物总量和往年相比无显著差异,但是叶凋落总量、旱季凋落物总量、旱季叶凋落量为历年来最高,其中旱季叶凋落物量比一般年份平均高35.2％ (0.81 t/hm2).而2010年附生苔蘚年凋落量为历年来最低.2010年最旱月的乔木层和灌木层叶面积指数和2005同期相比无显著差异,但是草本层叶面积指数却极显著低于2005年同期.因此,2010年初西南干旱尽管使哀牢山常绿阔叶林旱季落叶增加,但还没有到显著影响冠层叶面积指数的程度.而草本层和附生苔藓的生长则受到了干旱事件的显著影响.此外,哀牢山常绿阔叶林年总凋落量和年降水量显著正相关,而和年均温却不相关,表明该亚热带森林凋落物量主要由降水而非温度决定.     

Patterns of herbivore species richness in Kenya and current ecoclimatic stability

The increased attention to biodiversity worldwide has stimulatedinterest in understanding biophysical factors associated with indicators ofbiodiversity such as species richness. Although levels of biodiversity may seemto be equivalent in different areas, high species richness may be caused byaccumulation of species over a long time in places where environmentalconditions remained stable and predictable. The advanced very high resolutionradiometer (AVHRR)–normalized difference vegetation index (NDVI) has beenestablished to be a good proxy for studying interannual climate variability aswell as regional drought condition. In this study, I examined the relationshipbetween large herbivore species richness and AVHRR–NDVI derivedclimatic-variability indices, interannual average NDVI and coefficient ofvariation of NDVI at a regional spatial scale in Kenya. Regions with a relativelylow coefficient of variation of NDVI and high interannual average NDVIcharacterize current ecoclimatic stability. By contrast, a high coefficient ofvariation of NDVI and relatively low interannual average NDVI characterizeecoclimatic instability (drought risk). Statistical analyses revealed that a highinterannual average NDVI increases species richness, whereas a high coefficient ofvariation of NDVI lowers species richness. This indicates that maximum numbers ofspecies are found in regions with current ecoclimatic stability. Understandingsuch relationships can help in explaining spatial distribution of speciesrichness and predicting global changes resulting from human impacts on theenvironment.     

Changes in distribution of waterbirds following prolonged drought reflect habitat availability in coastal and inland regions

Provision of suitable habitat for waterbirds is a major challenge for environmental managers in arid and semiarid regions with high spatial and temporal variability in rainfall. It is understood in broad terms that to survive waterbirds must move according to phases of wet–dry cycles, with coastal habitats providing drought refugia and inland wetlands used during the wet phase. However, both inland and coastal wetlands are subject to major anthropogenic pressures, and the various species of waterbird may have particular habitat requirements and respond individualistically to spatiotemporal variations in resource distribution. A better understanding of the relationships between occurrence of waterbirds and habitat condition under changing climatic conditions and anthropogenic pressures will help clarify patterns of habitat use and the targeting of investments in conservation. We provide the first predictive models of habitat availability between wet and dry phases for six widely distributed waterbird species at a large spatial scale. We first test the broad hypothesis that waterbirds are largely confined to coastal regions during a dry phase. We then examine the contrasting results among the six species, which support other hypotheses erected on the basis of their ecological characteristics. There were large increases in area of suitable habitat in inland regions in the wet year compared with the dry year for all species, ranging from 4.14% for Australian White Ibis to 31.73% for Eurasian Coot. With over half of the suitable habitat for three of the six species was located in coastal zones during drought, our study highlights the need to identify and conserve coastal drought refuges. Monitoring of changes in extent and condition of wetlands, combined with distribution modeling of waterbirds, will help support improvements in the conservation and management of waterbirds into the future.     

Increasing elephantLoxodonta africana density is a more important driver of change in vegetation condition than rainfall

The impact of African elephantsLoxodonta africana Blumenbuch, 1797 on biodiversity is hotly debated in wildlife management circles with scientists polarised in their views. This polarisation is largely due to the individual experiences of researchers. We aimed to determine whether elephants or rainfall patterns drove changes in vegetation condition (Normalised Difference Vegetation Index; NDVI) by avoiding a site-specific approach and looking at the issue at a broader scale. We used published estimates of elephant population density from 30 sites and recorded the change in density from 1995–1999, from 1999–2002 and from 2002–2006. We also recorded the deviation of annual rainfall from the long-term mean for those periods. We modelled these variables against the change in NDVI between periods using mixed effects models. We found that elephants were more influential in driving change in vegetation condition than rainfall, and this also occurred at one of our individual test sites where long-term data were available (Kruger). Elephants and rainfall combined to drive change in vegetation condition at our other long-term test site (Amboseli). Management activities (fencing, water provision) may cause the differences between the two long-term study sites. Change in productivity driven by rainfall has ramifications for biodiversity, suggesting that elephant derived changes in vegetation productivity (NDVI) also impacts on biodiversity. Thus, this study supports previous findings from individual sites that elephants impact vegetation, however there is also a suggestion that these impacts may vary according to management actions.     

中国北方草原对气候干旱的响应

草原生长动态受气候条件的影响和制约,在很大程度上取决于水分条件.为了较好阐明草原生长与干旱气候关系,利用表征草原生长变化的NDVI(Normalized Difference Vegetation Index)指数和表征干旱的SPI(Standardized Precipitation Index)指数研究了荒漠草原、典型草原、草甸草原与干旱气候的线性关系,表明荒漠草原的生长动态受季节性干旱影响很大,短期、中长期和长期干旱对荒漠草原影响较小.典型草原对季节性干旱响应较强,而对短期、中长期和长期的干旱响应较弱.草甸草原对季节性和长期干旱响应较强.并且草原对降雨量的响应具有时滞效应,水分盈亏对草原的影响是累积效应.利用基于虚拟变量的回归模型和简单回归模型模拟了草原NDVI对SPI指数的响应关系,基于虚拟变量的回归模型显示出对草原NDVI与SPI关系的较优拟合度.表明了草原生长动态对干旱气候响应具有季节性效应.     

Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology

The green area displayed by a crop is a good indicator of its photosynthetic capacity, while chlorophyll retention or 'stay-green' is regarded as a key indicator of stress adaptation. Remote-sensing methods were tested to estimate these parameters in diverse wheat genotypes under different growing conditions. Two wheat populations (a diverse set of 294 advanced lines and a recombinant inbred line population of 169 sister lines derived from the cross between Seri and Babax) were grown in Mexico under three environments: drought, heat, and heat combined with drought. In the two populations studied here, a moderate heritable expression of stay-green was found-when the normalized difference vegetation index (NDVI) at physiological maturity was estimated using the regression of NDVI over time from the mid-stages of grain-filling to physiological maturity-and for the rate of senescence during the same period. Under heat and heat combined with drought environments, stay-green calculated as NDVI at physiological maturity and the rate of senescence, showed positive and negative correlations with yield, respectively. Moreover, stay-green calculated as an estimation of NDVI at physiological maturity and the rate of senescence regressed on degree days give an independent measurement of stay-green without the confounding effect of phenology. On average, in both populations under heat and heat combined with drought environments CTgf and stay-green variables accounted for around 30% of yield variability in multiple regression analysis. It is concluded that stay-green traits may provide cumulative effects, together with other traits, to improve adaptation under stress further.     

A framework for predicting and visualizing the East African wildebeest migration-route patterns in variable climatic conditions using geographic information system and remote sensing

In the Serengeti–Mara ecosystem of East Africa, the migrating wildebeests (Connochaetes taurinus) response to food resource distribution and terrain complexity impacts their movement characteristics. This manifests in varying ways such as movement speed, direction, turning frequency, and moving distance. To investigate these characteristics, indices derived from vegetation quantity (normalized difference vegetation index, NDVI) and relief (slope) were used in our previous work to quantify the relationships between migration route location versus vegetation, relief complexity, and their combination. Least cost pathways determined using these indices were representative of approximate migration routes. The simulated routes were shown to be strongly influenced by vegetation during the dry season. However the impact of climatic change (rainfall) on route location was not investigated though known to influence vegetation recovery patterns. This paper specifically addresses the impact of climatic change on route location. The mean monthly rainfall data were used to classify the rainy and dry seasons in the Serengeti, the Western, and the Mara areas as normal, drier, or wetter than normal, over the 1986–1997 period. The classification is based on the mean monthly rainfall variability about the 11-year seasonal mean. Regression analysis showed strong linear relationships between rainfall and mean NDVI for each one of the three areas. The subsequent seasonal classification based on the corresponding habitat vegetation characteristics (NDVI) revealed the relative variation of vegetation with rainfall. Using the derived general categories, migration routes are then predicted for the various categories using a route attractivity index. The seasonal migration routes were shown to change depending on the relative abundance of the rainfall during the dry season. Dry season migration routes tended toward areas with better vegetation activity, i.e., those characterized by higher NDVI gradients. Our results showed that during the western trek, wetter dry seasons have the effect of delaying the herds movement northwestward. During the northern trek, wetter dry seasons have the effect of delaying the tendency to move westward. However the variation in rainfall conditions during the rainy and dry season had no significant influence on the southern trek route location. We assume that predicted routes based on average general category conditions for different years are representative of main migration route patterns for similar seasons, therefore they are well suited for approximate route prediction, if the climatic characteristics of the year are known.     

Phenological responses to extreme droughts in a Mediterranean forest

Mediterranean regions are projected to experience more frequent, prolonged and severe drought as a consequence of climate change. We used a retractable rainfall shelter, to investigate the impact of extreme droughts on the development of Quercus ilex leaves, flowers and fruit. In 2008, 97% of rainfall was excluded from a forest plot during the autumn, representing 50% of the 1127 mm of rain that fell during the year. In 2009, 87% of rainfall was excluded during the spring, representing 58% of the 749 mm that fell during the year. The rainfall shelter did not impact neither incident radiation nor air temperature. Autumn rainfall exclusion did not significantly affect leaf, flowers or fruit development. Spring rainfall exclusion resulted in larger and more sustained depression of leaf water potential during the key phases of foliar and floral development. Consequently, only half of the sampled trees (6) reached the shoot lengthening stage which leads to functionally mature leaves (phenophase 4), with one abandoning leaf development at budburst (phenophase 3) and the other two at the bud swelling stage (phenophase 2). All trees of the control plot passed phenophase 4, with most reaching complete leaf development. The impact of extreme droughts on flower development differed between the sexes. The spring exclusion had no effect on male flower, but only one of six trees completed female fruit maturation, compared with four in the control plot. The difference between the male and female drought impacts is likely attributable to the occurrence of male floral development before the period of lowest leaf water potential, and to the lower resource allocation requirements of male flowers. The information provided by our experimental approach may constitute a crucial step to evaluate the impact of increasing drought due to climate change on the most dominant Mediterranean tree species and to help drawing a full picture of the ecological consequences of the decline in water resource on forest dynamics under changing conditions.     

近40年中国干旱特征及其对植被变化的影响

全球变暖影响下，中国干旱事件发生愈加频繁。过去半个世纪里，中国半干旱和半湿润地区的分界线总体南移，干旱面积呈增加趋势，因此了解中国干旱变化趋势对区域生态环境保护具有重要意义。基于GLASS数据产品、ERA5-Land数据，采用游程理论和多元线性回归等方法，探究1982—2018年间多尺度干旱事件基本特征(干旱持续时间、干旱严重度、干旱强度等),并分析植被生产力变化趋势，揭示干旱对植被变化的累积影响。结果表明：(1)新疆、青藏高原以及东南地区干旱较为严峻，而华中、华东大部分区域处于轻旱或无旱状态；(2)1982—2018年间，中国植被生产力整体呈改善态势，显著改善区集中在中国中部，而退化区集中在东南部、内蒙古和西藏南部；(3)中国大部分区域干旱与植被呈正相关，且干旱对植被多为累积影响，在干旱区和半干旱区尤为明显；(4)随着植被覆盖度的增加，植被与近短期尺度干旱的相关性也逐渐增加，由干旱区到湿润区，近短尺度干旱对植被变化的影响逐步增大。其中，SPEI-6(标准化降水蒸散发指数—中期尺度)对植被轻微变化累积影响最显著，而SPEI-12(标准化降水蒸散发指数—长期尺度)对植被显著变化累积影响更...     

AVHRR NDVI与气候因子的相关分析

对中国１６０个气象站１０ａ的连续ＡＶＨＲＲ ＮＤＶＩ数据、气象观测数据进行相关分析,并结合植被覆盖类型资料深入探讨了ＡＶＨＲＲ ＮＤＶＩ／气温和ＡＶＨＲＲ ＮＤＶＩ／降水相关系数的地区差异及其随植被类型变化规律。研究结果表明,对中国的大部分地区,气温对植被的影响超过降水。就自然植被而言,其对降水的敏感性趋势为草本植被大于灌木植被,灌木植被大于乔木植被。就农作物而言,降水影响取决于耕作制度、作物种类     

Effects of precipitation and soil water potential on drought deciduous phenology in the Kalahari

We utilized an ecosystem process model to investigate the influence of precipitation and soil water potential on vegetation phenology in the semi‐arid, drought‐deciduous ecosystems in the Kalahari region of South Africa. The timing of leaf flush was assumed to be the first day during which a rainfall event exceeded that day's estimate of potential evapotranspiration after a defined dry season. Leaf senescence was assumed to be a dynamic feedback between soil water potential and net plant carbon gain and was determined by dynamically modeling the effects of concomitant trends in soil water potential and net primary production on leaf area index (LAI). Model predictions of LAI were compared with satellite‐derived normalized difference vegetation indices (NDVI) for 3 years at two sites along the Kalahari transect. The mean absolute error for the prediction of modeled leaf flush date compared with leaf flush dates estimated from NDVI were 10.0 days for the Maun site and 39.3 days for the Tshane site. Correlations between model predicted 10‐day average LAI and 10‐day composite NDVI for both Maun and Tshane were high (ρ=0.67 and 0.74, respectively, P<0.001), suggesting that this method adequately predicts intra‐annual leaf area dynamics in these dry tropical ecosystems.     

Are certain habitats better every year? A review and a case study on birds of prey

Although habitat studies are essential for species management, little is known about temporal and spatial variation in the wildlife-habitat relationships. This paper explores annual variation in habitat preferences of and relative quality for diurnal raptors and owls. A review of 772 published sources showed that habitat×year interaction had been analysed in only 10% of habitat quality and 5% of habitat preference studies. Two major factors behind the year-effects were the fluctuations in rainfall and prey base, which together influenced a wide variety of species. Yet, 67% of studies had pooled data from different years and 17% relied on data from only one year. The conclusions of the review were validated by analysing a typical situation for which habitat×year interactions could be expected – habitat quality in a vole-specialized raptor, the common buzzard Buteo buteo , in an area of regularly fluctuating vole abundance. According to eleven-year data, the relationships between buzzard productivity and landscape characteristics were distinct between years. Habitat impact was more clear during vole-poor years, when successful buzzards bred in landscapes having diverse land cover, no wetlands and no conspecifics around. In contrast, during vole peaks, better young production was related to homogeneous landscapes. When years were pooled, the relationships were concealed and habitat quality model became not significant. Selecting 'poor-year habitat' or 'rich-year habitat' seemed to give a similar reproductive output for the buzzards in the long-term. The results indicate that one-year approaches to wildlife-habitat relationships can easily lead to erroneous conclusions, significant habitat relationships may become lost in pooled data, and the most typical situations that need annually explicit approach can be recognized while planning the studies.     

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate–plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012–2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011–2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012–2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states—showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.     

An analysis of relationships among plant community phenology and seasonal metrics of Normalized Difference Vegetation Index in the northern part of the monsoon region of China

This study focuses on relationships between the phenological growing season of plant communities and the seasonal metrics of Normalized Difference Vegetation Index (NDVI) at sample stations and pixels overlying them, and explores the procedure for determining the growing season of terrestrial vegetation at the regional scale, using threshold NDVI values obtained by surface–satellite analysis at individual stations/pixels. The cumulative frequency of phenophases has been calculated for each plant community and each year in order to determine the growing season at the three sample stations from 1982 to 1993. The precise thresholds were arbitrarily set as the dates on which the phenological cumulative frequency reached 5% and 10% (for the beginning) and 90% and 95% (for the end). The beginning and end dates of the growing season were then applied each year as time thresholds, to determine the corresponding 10-day peak greenness values from NDVI curves for 8-km² pixels overlying the phenological stations. According to a trend analysis, a lengthening of the growing seasons and an increase of the integrated growing season NDVI have been detected in the central part of the research region. The correlation between the beginning dates of the growing season and the corresponding threshold NDVI values is very low, which indicates that the satellite-sensor-derived greenness is independent of the beginning time of the growing season of local plant communities. Other than in spring, the correlation between the end dates of the growing season and the corresponding threshold NDVI values is highly significant. The negative correlation shows that the earlier the growing season terminates, the larger the corresponding threshold NDVI value, and vice versa. In order to estimate the beginning and end dates of the growing season using the threshold NDVI values at sites without phenological data from 1982 to 1993, we calculated the spatial correlation coefficients between NDVI time-series at each sample station and other contiguous sites year by year. The results provide the spatial extrapolation area of the growing season for each sample station. Thus, we can use the threshold NDVI value obtained at one sample station/pixel for a year to determine the growing season at the extrapolation sites with a similar vegetation type for the same year. Received: 25 October 2000 / Revised: 19 June 2001 / Accepted: 19 June 2001     

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.     

2000—2016年云南地区植被覆盖时空变化及其对水热因子的响应

基于2000-2016年MODIS-NDVI数据,利用趋势分析法以及线性相关分析等方法对云南地区植被月变化趋势、年际变化趋势进行详细分析;探讨植被覆盖变化与主要气候水热因子的关系。结果表明：研究区大部分地区植被覆盖良好,年NDVI的平均值为0.55,其中NDVI较高值（> 0.8）区域主要分布于南部,而西北部和中部城市地区NDVI值较低;自2000年开始,研究区NDVI总体呈显著（P < 0.05）增加趋势,年NDVI的变化斜率为0.0036,植被覆盖呈增加趋势的区域占研究区总面积79.80%;不同季节（春、夏、秋、冬）和生长季的植被状况均呈良性发展趋势;湿润指数和水热综合因子在滇西北与NDVI多呈负相关,在滇中地区以正相关为主;春、夏、秋3个季节NDVI受降水影响较大,而冬季NDVI则受气温影响较大;受降水影响较大的区域主要分布在中部和南部,受气温影响较大区域主要分布在滇西北、滇东北地区;NDVI在不同月份对气候因子的滞后时间存在差异,NDVI与当月气温的相关性强于与当月降水的相关性,植被生长对气温的响应无明显滞后效应,对降水存在3个月的滞后期。     

Drought and its legacy modulate the post‐fire recovery of soil functionality and microbial community structure in a Mediterranean shrubland

The effects of drought on soil dynamics after fire are poorly known, particularly its long‐term (i.e., years) legacy effects once rainfall returns to normal. Understanding this is particularly important for nutrient‐poor soils in semi‐arid regions affected by fire, in which rainfall is projected to decrease with climate change. Here, we studied the effects of post‐fire drought and its legacy on soil microbial community structure and functionality in a Cistus‐Erica shrubland (Spain). Rainfall total and patterns were experimentally modified to produce an unburned control (natural rainfall) and four burned treatments: control (natural rainfall), historical control (long‐term average rainfall), moderate drought (percentile 8 historical rainfall, 5 months of drought per year), and severe drought (percentile 2, 7 months of drought). Soil nutrients and microbial community composition (ester‐linked fatty acid approach) and functionality (enzyme activities and C mineralization rate) were monitored during the first 4 years after fire under rainfall treatments, plus two additional ones without them (six post‐fire years). We found that the recovery of burned soils was lower under drought. Post‐fire drought increased nitrate in the short term and reduced available phosphorus, exchangeable potassium, soil organic matter, enzyme activities, and carbon mineralization rate. Moreover, drought decreased soil total microbial biomass and fungi, with bacteria becoming relatively more abundant. Two years after discontinuing the drought treatments, the drought legacy was significant for available phosphorus and enzyme activities. Although microbial biomass did not show any drought legacy effect, the proportion of fungi and bacteria (mainly gram‐positive) did, being lower and higher, respectively, in former drought‐treated plots. We show that drought has an important impact on soil processes, and that some of its effects persist for at least 2 years after the drought ended. Therefore, drought and its legacy effects can be important for modeling biogeochemical processes in burned soils under future climate change.