Landscape patterns and environmental controls of deciduousness in forests of central Panama

Aim Dry season deciduousness affects intra‐ and inter‐annual patterns of carbon, water and energy balance in seasonal tropical forests. Because it is affected by rainfall, temperature and solar radiation, deciduousness may be an indicator of the response of vegetation to climate change. Better understanding of how spatial patterns of deciduousness are affected by climate and other environmental gradients will improve the ability to predict responses to climate change. This study develops remote sensing methods for quantifying tropical forest deciduousness and examines the relationship between deciduousness and environmental factors in semi‐deciduous tropical forest. Location Central Panama. Methods I applied spectral mixture analysis (SMA) and the normalized difference vegetation index (NDVI) to Landsat images to predict deciduousness which was ground‐truthed with field observations of the percentage of overstorey deciduous trees. Using predicted deciduousness from SMA, patterns of deciduousness at three spatial scales were analysed. I determined how deciduousness varied spatially with rainfall and geological substrate. Results Both SMA and NDVI had strong correlations (r > 0.9) with field observations of deciduousness. On a landscape scale, deciduousness increased as rainfall decreased, but geological substrate altered this relationship. On some geological substrates, deciduousness was much greater than expected for a given rainfall total or showed a slight but significant increase with rainfall. At an intermediate spatial scale, there were highly deciduous patches from 3 to 250 ha in size embedded in non‐deciduous forest, which may have resulted from topography, soil variation or past land use. Main conclusions Dry season deciduousness can be accurately quantified using satellite images indicating that remote sensing can be a valuable tool for detecting change and understanding ecosystem processes in tropical forests from landscape to regional scales.     

Time lag and negative responses of forest greenness and tree growth to warming over circumboreal forests

The terrestrial forest ecosystems in the northern high latitude region have been experiencing significant warming rates over several decades. These forests are considered crucial to the climate system and global carbon cycle and are particularly vulnerable to climate change. To obtain an improved estimate of the response of vegetation activity, e.g., forest greenness and tree growth, to climate change, we investigated spatiotemporal variations in two independent data sets containing the dendroecological information for this region over the past 30 years. These indices are the normalized difference vegetation index (NDVI3g) and the tree‐ring width index (RWI), both of which showed significant spatial variability in past trends and responses to climate changes. These trends and responses to climate change differed significantly in the ecosystems of the circumarctic (latitude higher than 67°N) and the circumboreal forests (latitude higher and lower than 50°N and 67°N, respectively), but the way in which they differed was relatively similar in the NDVI3g and the RWI. In the circumarctic ecosystem, the climate variables of the current summer were the main climatic drivers for the positive response to the increase in temperatures showed by both the NDVI3g and the RWI indices. On the other hand, in the circumboreal forest ecosystem, the climate variables of the previous year (from summer to winter) were also important climatic drivers for both the NDVI3g and the RWI. Importantly, both indices showed that the temperatures in the previous year negatively affected the ecosystem. Although such negative responses to warming did not necessarily lead to a past negative linear trend in the NDVI3g and the RWI over the past 30 years, future climate warming could potentially cause severe reduction in forest greenness and tree growth in the circumboreal forest ecosystem.     

Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices

Wildfires have major effects on forest dynamics, succession and the carbon cycle in the boreal biome. They are a significant source of carbon emissions, and current observed changes in wildfire regimes due to changes in climate could affect the balance of the boreal carbon pool. A better understanding of postwildfire vegetation dynamics in boreal forests will help predict the future role of boreal forests as a carbon sink or source. Time series of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Shortwave Infrared Index (NDSWIR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite were used to investigate whether characteristic temporal patterns exist for stands of different ages in the Siberian boreal forests and whether their postwildfire dynamics are influenced by variables such as prewildfire vegetation cover. Two types of forests, evergreen needle‐leaf (ENF) and deciduous needle‐leaf (DNF), were studied by analysing a sample of 78 burned forest areas. In order to study a longer time frame, a chronosequence of burned areas of different ages was built by coupling information on location and age provided by a forest burned area database (from 1992 to 2003) to MODIS NDVI and NDSWIR time series acquired from 2001 to 2005. For each of the burned areas, an adjacent unburned control plot representing the same forest type was selected, with the aim of separating the interannual variations caused by climate from changes in NDVI and NDSWIR behaviour due to a wildfire. The results suggest that it takes more than 13 years for the temporal NDVI and NDSWIR signal to recover fully after wildfire. NDSWIR, which is associated to canopy moisture, needs a longer recovery period than NDVI, which is associated to vegetation greenness. The results also suggest that variability observed in postwildfire NDVI and NDSWIR can be explained partially by the dominant forest type: while 13 years after a fire NDVI and NDSWIR are similar for ENF and DNF, the initial impact appears to be greater on the NDVI and NDSWIR of ENF, suggesting a faster recovery by ENF.     

Climatic controls of vegetation vigor in four contrasting forest types of India—evaluation from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer datasets (1990–2000)

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R²=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.     

22年来西北不同类型植被NDVI变化与气候因子的关系

 为了研究气候变化对西北地区不同类型植被的影响,利用NASA GIMMS 1982～2003年逐月归一化植被指数（Normalized difference vegetation index, NDVI）数据集和西北地区138个气象站点同期的气温和降水资料,计算了各站22年月平均气温和降水与NDVI的相关系数。同时, 选西北 地区森林、草原、绿洲和雨养农业4类有代表性的植被类型为研究区,对各类植被NDVI与气温和降水的相关关系进行分析。研究结果表明：除无 植被的戈壁沙漠地区外,西北地区NDVI与气温和降水均有较好的相关性。除祁连山中部地区外,西北地区NDVI与气温的相关系数大于降水。天 山、阿尔泰山和秦岭的NDVI与气温相关系数最高,而青海东北部NDVI与降水相关系数最高。西北地区各种类型植被对气候变化反映敏感。其敏 感度因植被类型不同和同类植被所处的地理位置不同而有差异;纬度较高的新疆林区与温度相关性最高,高寒草甸次之。在植被生长最旺盛的 夏季（6～8月）,22年来西北地区各林区的NDVI均呈下降趋势。其中西北东部林区下降趋势显著,与这些地区的降水减少和气温增加有关。草 原区植被以上升趋势为主,高寒草甸和盐生草甸上升趋势最为显著,气温升高是这些地区植被生长加速的原因 之一。西北绿洲是NDVI增加极为 显著的地区,以新疆绿洲NDVI上升趋势最大。气候变暖是近年绿洲NDVI增加的主要驱动力之一,绿洲面积扩大、种植结构调整和种植品种变化 等人为因素对绿洲NDVI增加的作用不可忽视,这种作用在新疆表现的尤为突出。雨养农业区NDVI年际 间波动较大,各区域间变化不太一致。 NDVI的波动与降水变化有很好的正相关,与气温变化有很好的负相关,近年来西北东部气温升高和降水的减少是雨养农业区NDVI下降的原因, 农业措施的实施也改变了植被生长对气候条件的依赖性。     

Rainfall in prior breeding seasons influences population size of a small marsupial

The imposition of the stresses of climate change (higher temperatures and in many regions lower rainfall) on existing stressors, such as habitat loss and degradation, will increase pressures on native fauna already experiencing declines. We focused on assessing how the ‘Big Dry’ (severe drought, 1997–2010) in south‐eastern Australia affected populations of a small marsupial carnivore, the yellow‐footed antechinus (Antechinus flavipes), in box‐ironbark forests, which suffer a range of anthropogenic disturbances. Trapping of the mammal was conducted on 136 (0.25 ha) sites in two box‐ironbark forests in 2004, 2005 and 2011 (46 or 64 sites per year). Capture rates of all distinct individuals, males and second‐year females with suckled teats, and the number of suckled teats were positively associated with rainfall in the previous September (time of lactation and deposition of young in nests). Despite differences between forests in capture rates of all individuals, the positive effect of rainfall was evident in both forests. Populations in one forest, Chiltern, were substantially larger than other locations surveyed in 2004 and 2005, yet crashed to small numbers in 2011. This crash was most likely due to low rainfall in the preceding years including the lowest recorded annual rainfall (2006), below‐average annual rainfall (2007, 2008 and 2009) and well‐below‐average rainfall in September (2006, 2007 and 2008). The predicted drying and warming climate in south‐eastern Australia and habitat loss and degradation pose a threat to the viability of the yellow‐footed antechinus in box‐ironbark forests. An integrated approach to small‐mammal management is necessary given that the region may be facing additional losses, especially during droughts, to those already experienced since the early 1800s. Our work emphasizes the need to identify specific effects of stressors on vital demographic characteristics of species.     

Vegetation structure and greenness in Central Africa from Modis multi-temporal data

African forests within the Congo Basin are generally mapped at a regional scale as broad-leaved evergreen forests, with the main distinction being between terra-firme and swamp forest types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organization and their relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified 22 vegetation types (six savannas, two swamp forests, 14 forest types) improving existing vegetation maps. Among forest types, we showed strong variations in stand structure and deciduousness, identifying (i) two blocks of dense evergreen forests located in the western part of the study area and in the central part on sandy soils; (ii) semi-deciduous forests are located in the Sangha River interval which has experienced past fragmentation and human activities. For all vegetation types enhanced vegetation index profiles were highly seasonal and strongly correlated to rainfall and to a lesser extent, to light regimes. These results are of importance to predict spatial variations of carbon stocks and fluxes, because evergreen/deciduous forests (i) have contrasted annual dynamics of photosynthetic activity and foliar water content and (ii) differ in community dynamics and ecosystem processes.     

近30年中国陆地生态系统NDVI时空变化特征

气候变化已明显影响到陆地植被的活动,但在不同生态系统间存在差异,研究不同陆地生态系统归一化植被指数(NDVI)的时空变化特征,不仅可揭示各生态系统植被活动对气候变化的响应规律,而且可为我国不同生态区制定应对气候变化的策略和生态文明建设提供科学依据。基于1982—2012年GIMMS NDVI3g和中国陆地生态系统类型数据,利用一元线性回归、集合经验模态分解和相关分析等方法,研究了近30年中国各陆地生态系统NDVI的时空变化特征,分析了其与气候事件的关系。结果表明,近30年中国植被活动显著上升,年平均归一化植被指数(ANDVI)的上升幅度为0.0029/10a(P0.05),年最大归一化植被指数(MNDVI)的上升幅度为0.0076/10a(P0.01);植被活动显著增强的区域主要是分布在东部季风区的农田和森林生态系统,显著下降的区域主要是分布于西北的荒漠生态系统和东北的森林生态系统;尽管ANDVI和MNDVI线性趋势的显著性有所差异,但农田、森林、草地和水体与湿地生态系统的NDVI总体呈非稳定的上升趋势,上升过程中伴随着较大波动,荒漠生态系统的NDVI呈下降趋势,植被退化显著;与线性趋势不同,各生态系统植被活动的残差趋势包含"上升—下降"两个阶段,并相继于20世纪90年代到21世纪初发生转折;上述5类生态系统的植被活动存在不同尺度的周期特征,年际周期波动特征(1.9—7.6a)比较显著,而年代际周期(10.7a和22.2a)的显著性相对较差;各生态系统的空间异质性在趋强过程中存在2.1—7.1a的年际周期节律;海洋与大气环流的短周期脉动与各生态系统植被活动的周期性节律有着明显关联,ENSO事件和太阳活动是推动植被活动周期性振荡的重要因素。     

Satellite‐based evidence for shrub and graminoid tundra expansion in northern Quebec from 1986 to 2010

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air‐photo studies have documented recent changes in high‐latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24‐year (1986–2010) Landsat time series in a latitudinal transect across the boreal forest‐tundra biome boundary in northern Quebec province, Canada. This region has experienced rapid warming during both winter and summer months during the last 40 years. Using a per‐pixel (30 m) trend analysis, 30% of the observable (cloud‐free) land area experienced a significant (P < 0.05) positive trend in the Normalized Difference Vegetation Index (NDVI). However, greening trends were not evenly split among cover types. Low shrub and graminoid tundra contributed preferentially to the greening trend, while forested areas were less likely to show significant trends in NDVI. These trends reflect increasing leaf area, rather than an increase in growing season length, because Landsat data were restricted to peak‐summer conditions. The average NDVI trend (0.007 yr^?1) corresponds to a leaf‐area index (LAI) increase of ~0.6 based on the regional relationship between LAI and NDVI from the Moderate Resolution Spectroradiometer. Across the entire transect, the area‐averaged LAI increase was ~0.2 during 1986–2010. A higher area‐averaged LAI change (~0.3) within the shrub‐tundra portion of the transect represents a 20–60% relative increase in LAI during the last two decades. Our Landsat‐based analysis subdivides the overall high‐latitude greening trend into changes in peak‐summer greenness by cover type. Different responses within and among shrub, graminoid, and tree‐dominated cover types in this study indicate important fine‐scale heterogeneity in vegetation growth. Although our findings are consistent with community shifts in low‐biomass vegetation types over multi‐decadal time scales, the response in tundra and forest ecosystems to recent warming was not uniform.     

The greening and browning of Alaska based on 1982–2003 satellite data

Aim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km² pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.     

Short‐term propagation of rainfall perturbations on terrestrial ecosystems in central California

Question: Does vegetation buffer or amplify rainfall perturbations, and is it possible to forecast rainfall using mesoscale climatic signals? Location: Central California (USA). Methods: The risk of dry or wet rainfall events was evaluated using conditional probabilities of rainfall depending on El Niño Southern Oscillation (ENSO) events. The propagation of rainfall perturbations on vegetation was calculated using cross‐correlations between monthly seasonally adjusted (SA) normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR), and SA antecedent rainfall at different time‐scales. Results: In this region, El Niño events are associated with higher than normal winter precipitation (probability of 73%). Opposite but more predictable effects are found for La Niña events (89% probability of dry events). Chaparral and evergreen forests showed the longest persistence of rainfall effects (0‐8 months). Grasslands and wetlands showed low persistence (0‐2 months), with wetlands dominated by non‐stationary patterns. Within the region, the NDVI spatial patterns associated with higher (lower) rainfall are homogeneous (heterogeneous), with the exception of evergreen forests. Conclusions: Knowledge of the time‐scale of lagged effects of the non‐seasonal component of rainfall on vegetation greenness, and the risk of winter rainfall anomalies lays the foundation for developing a forecasting model for vegetation greenness. Our results also suggest greater competitive advantage for perennial vegetation in response to potential rainfall increases in the region associated with climate change predictions, provided that the soil allows storing extra rainfall.     

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.     

Regeneration patterns and persistence of the fog-dependent Fray Jorge forest in semiarid Chile during the past two centuries

The persistence of rainforest patches at Fray Jorge National Park (FJNP) in semiarid Chile (30°40′S), a region receiving approximately 147 mm of annual rainfall, has been a source of concern among forest managers. These forests are likely dependent on water inputs from oceanic fog and their persistence seems uncertain in the face of climate change. Here, we assessed tree radial growth and establishment during the last two centuries and their relation to trends in climate and canopy disturbance. Such evaluation is critical to understanding the dynamics of these semiarid ecosystems in response to climate change. We analyzed forest structure of six forest patches (0.2–22 ha) in FJNP based on sampling within 0.1 ha permanent plots. For the main canopy species, the endemic Aextoxicon punctatum (Aextoxicaceae), we used tree‐ring analysis to assess establishment periods, tree ages, growing trends and their relation to El Niño Southern Oscillation (ENSO), rainfall, and disturbance. The population dynamics of A. punctatum can be described by a continuous regeneration mode. Regeneration of A. punctatum was sensitive to different canopy structures. Growth release patterns suggest the absence of large scale human impact. Radial growth and establishment of A. punctatum were weakly correlated with rainfall and ENSO. If water limits forests patch persistence, patches are likely dependent on the combination of fog and rain water inputs. Forest patches have regenerated continuously for at least 250 years, despite large fluctuations in rainfall driven by ENSO and a regional decline in rainfall during the last century. Because of the positive influence on fog interception, forest structure should be preserved under any future climate scenario. Future research in FJNP should prioritize quantifying the long‐term trends of fog water deposition on forests patches. Fog modeling is crucial for understanding the interplay among physical drivers of water inputs under climate change.     

Fruiting phenology of fig trees in Kalinzu Forest,Uganda

The study determined the abundance and species composition of fig trees that fruited in the different forest types of Kalinzu Forest Reserve (KFR), Uganda. It also assessed the seasonal variations in abundance and species composition of the fig trees, the relationships between the fruiting patterns and rainfall and the figs’ inter‐ and intraspecific patterns of fruiting episodes. Sixteen fig species represented by 515 individuals were monitored monthly from December 2007 to January 2010. Most individuals and species that fruited were in the secondary forest types (the Musanga‐ and Parinari‐dominated secondary forests) and abundances of individuals of the different species were significantly associated with particular forest types. One colonizing species (Ficus sur) was the most abundant species that fruited and was mostly recorded in the secondary forests. Species composition and abundances of trees that fruited varied seasonally, and only the abundances of two canopy species (Ficus lingua and Ficus sansibarica) were significantly related with monthly rainfall. Most species experienced at least four fruiting phases, and F. sur displayed the longest episode covering 22 months. The results suggest that the past intensive logging in KFR promoted the regeneration of a diversity of fig species, and most species generally experience community‐wide asynchronous fruiting.     

Mapping the biomass of Bornean tropical rain forest from remotely sensed data

The biomass and biomass dynamics of forests are major uncertainties in our understanding of tropical environments. Remote sensing is often the only practical means of acquiring information on forest biomass but has not always been used successfully. Here the conventional approaches to the estimation of forest biomass from remotely sensed data were evaluated relative to techniques based on the application of artificial neural networks. Together these approaches were used to estimate and map the biomass of tropical forests in north‐eastern Borneo from Landsat TM data. The neural networks were found to be particularly suited to the application. A basic multi‐layer perceptron network, for example, provided estimates of biomass that were strongly correlated with those measured in the field (r = 0.80). Moreover, these estimates were more strongly correlated with biomass than those derived from 230 conventional vegetation indices, including the widely used normalized difference vegetation index (NDVI).     

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.     

Enrichment of land-cover polygons with eco-climatic information derived from MODIS NDVI imagery

Aim The FAO land‐cover classification system (LCCS) represents an innovative approach to standardizing and harmonizing land‐cover classifications based on remote sensing data. The thematic information considered by the LCCS, however, is intrinsically related to vegetation physiognomy and does not report important eco‐climatic features. Our aim is to develop a methodology to enrich LCCS maps with information on vegetation productivity and phenology derived from Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data. Location The LCCS has recently been applied in East Africa by the Africover project. The proposed methodology is developed and tested in Tanzania using MODIS NDVI data for a 5‐year period (2001–05). Methods Annual NDVI profiles of Africover polygons were extracted from MODIS imagery. These profiles, composed of 23 NDVI values per year, were averaged over the study period, purified for possible land‐cover errors and converted into a more manageable format composed of 24 half‐month values. The resulting NDVI profiles were first analysed visually and then evaluated statistically against rainfall measurements taken at 12 Tanzanian stations. The steps involved were as follows: NDVI values were aggregated on a monthly basis and represented with a one‐digit integer to obtain an extended code; a subset of parameters describing vegetation development and phenology was identified, thus obtaining a restricted codification; and finally, the information loss resulting from both the extended and restricted codification was evaluated with respect to the original NDVI profiles. Results NDVI profiles of different Africover classes can differ in mean values but tend to have a similar shape, linked to the seasonality of local vegetation. Both NDVI annual averages and seasonal variations are strictly dependent on rainfall patterns, particularly in arid zones. The tested codifications effectively summarize the eco‐climatic information contained in the polygon NDVI profiles, with the extended and restricted codifications retaining > 90% and 80% of such information, respectively. Main conclusions The proposed methodology is capable of enriching LCCS polygons with eco‐climatic information derived from MODIS NDVI data. Such information is related to vegetation development and seasonality, and can be efficiently condensed at various levels of detail.     

祁连山不同植被类型的物候变化及其对气候的响应

基于1982—2006年GIMMS NDVI和2000—2014年MODIS NDVI遥感数据,利用double logistic拟合方法提取了1982—2014年祁连山区不同植被的生长季始期、生长季末期和生长季长度3个重要的物候参数,分析了不同植被物候期的时间变化趋势、空间分异特征及对气候因子的响应。结果表明:(1)祁连山区不同植被的生长季始期和生长季末期随年际变化表现出波动提前或推迟,其中沼泽植被的变化波动最大;草甸植被、灌丛植被、阔叶林植被和栽培植被生长季长度出现延长趋势;(2)祁连山区植被生长季始期集中在5月初,其中阔叶林植被生长季开始最早,荒漠植被生长季开始最晚,植被生长季末期集中在9月,栽培植被生长季结束较早,荒漠植被、沼泽植被生长季结束较晚,植被生长季长度集中在110—140 d,其中阔叶林植被、针叶林植被生长季长度较长,而荒漠植被、高山植被生长季长度较短;(3)祁连山植被物候期变化趋势的空间分布表明植被生长季始期、生长季末期主要表现为提前不明显和推迟不明显,生长季长度主要表现为缩短不明显和延长不明显;(4)物候要素与气候要素相关性表明前期温度的积累有利于植被的开始生长,但当年3月的降水量对植被生长季始期同样有重要作用,不同植被生长季末期与8月、9月温度相关性较大,而与10月、11月降水的相关性较大。     

陕北长城沿线风沙区植被指数变化及其与气候的关系

陕北长城沿线风沙区位于毛乌素沙漠东南部边沿,属毛乌素沙地向东南移动的最活跃地段,生态环境十分脆弱。使用1981～2003年23a长时间序列的NOAA/AHRR NDVI数据、气候资料,分析了陕北长城沿线风沙区植被覆盖的历史演变及其与气候因子的关系。结果表明:(1)陕北长城沿线风沙区植被覆盖状况23a来尽管有波动起伏,但是整体在持续转好,年平均NDVI增加了10.62%。低覆盖率植被面积在减少,高覆盖率植被面积在增加。夏季的NDVI值最高、波动起伏最大,其次是秋季;春、夏、秋三季的NDVI具有明显的上升趋势,季平均NDVI年增长率夏季最大,秋季次之;夏、秋季NDVI与年NDVI具有很高的相关性,这两个季节的植被状况基本决定了全年的植被分布状况。NDVI年变化曲线为单峰型,春季NDVI缓慢增加,秋季NDVI降低速度比较快。(2)年平均NDVI与温度的年际变化相关不明显,各季节NDVI与温度相关也不明显。近年来长城沿线风沙区的年降水量没有明显增加,而年平均NDVI线性增加趋势显著,降水量是引起NDVI年际波动的主要因子,非气候因素是年平均NDVI线性增加的主要原因。降水量与NDVI存在着明显的年相关和隔季相关。年降水量与年NDVI的相关,冬季降水量与春季NDVI的相关,春季降水量与夏季NDVI的相关,夏季降水量与秋季NDVI的相关性都非常高。(3)非气候因素中生态保护和环境建设等人为措施,如植树造林、草原围栏封育等是导致植被显著增加的重要原因。