Simulating the East African wildebeest migration patterns using GIS and remote sensing

The Serengeti–Mara ecosystem in East Africa is a spectacular natural heritage endowed with diverse fauna and flora. The presence of the seasonally migrating wildebeest (Connochaetes taurinus) is a major boost for tourism. This migration however has enormous impacts to the ecosystem. Consequently efforts at monitoring the herd's migration trends and patterns remain a challenge to wildlife managers and ecologists in the region. In this paper, the relative influence of vegetation (normalized difference vegetation index), landscape and relief on herds migration routes are investigated and the migration routes simulated using GIS and remote sensing techniques. The results are compared with the annual mean route taken by the herds, as determined by radio tracking over the 1995–1997 period. Green vegetation availability is shown to be the major criterion in route choice. It is also shown that during the dry season phases of the migration (western trek, western corridor), the herd endures complex relief (complexity quantified based on slope and inter‐visibility) in the search for greener grass. During the season of abundance (southern trek), relief becomes critical in making route choices, with herds avoiding difficult terrain, notwithstanding their relatively more abundant vegetation. The method proposed in this paper is viable for rapid prediction of approximate routes for the migrating wildebeest in different climatic conditions.     

NDVI‐based vegetation monitoring in Mau forest complex,Kenya

The normalized difference vegetation index (NDVI) measures vegetation health and density using plant reflectance characteristics recorded by satellite imagery. Dekadal NDVI data were obtained for January 1999–December 2009 from 1‐km resolution SPOT‐VEGETATION sensor for closed woody vegetation type in four blocks of the Mau forest complex. Vegetation response to yearly seasonal variations was plotted and used to compare deviations by specific years. Subnormal vegetation conditions were recorded by the standardized vegetation index (SVI) and persistently low SVI values indicated a drought season or degraded vegetation. The general linear trend of the vegetation was plotted for the study period to identify trends towards degradation or vegetation recovery. Analysis of variance was used to compare forest blocks and shows spatial vegetation variations and also among years to identify vegetation variations with time. Rainfall data recorded for 2002–2009 in east Mau were used to confirm rainfall‐related vegetation variations block. Results show that NDVI patterns within an year follow cyclic trends with a strong dependence on rainfall seasons. The forest vegetation indicated negligible changes over the study period but effects of extended dry periods in 2000 and 2009 were evident. There were significant differences (P < 0.05) in NDVI between forest blocks. East Mau had significantly inferior vegetation that can be attributed to forest type, level of human degradation prior to the study and the lower rainfall. There were significant variations (P < 0.05) of NDVI among years but the forests showed a natural resilience to disturbance and can retain original vegetation vigour once stress is removed. The study proposes further monitoring of the forests including other vegetation types that are more vulnerable to climatic variations and anthropogenic effects.     

马拉河流域植被生态需水特征及估算

生态需水是生态用水控制和区域生态环境恢复建设的基本依据。马拉河流域拥有世界著名的生态系统,植被生态需水占流域总需水量的很大一部分。基于1980—2020年ERA5气象数据、叶面积指数(LAI)与世界土壤数据库数据,采用Penman-Monteith法计算了马拉河流域四个季节(短旱季、长雨季、长旱季、短雨季)植被生态需水量的时空变化特征。在此基础上,使用支持向量机(SVM)、随机森林(RF)和卷积神经网络(CNN)3种机器学习方法与7个环境因子(气温、降水、10 m风速、LAI、太阳辐射、相对湿度、地形)建立了回归模型,分别估算了2011—2020年逐年不同季节的植被生态需水量,并与Penman-Monteith法计算结果进行时间序列拟合度和空间相似性的比较。结果表明：马拉河流域植被生态需水量在过去40年所有季节都呈现为波动变化,植被生态需水量长雨季>长旱季>短雨季>短旱季,长雨季的植被生态需水量约为短旱季的1.5倍。不同季节均呈现出上下游高、中游低的植被生态需水量空间分布格局。LAI为最大的正影响因子,风速为最大的负影响因子。就不同方法估算的植被生态需水量准确性而言,...     

Elephant spatial use in wet and dry savannas of southern Africa

The influence of elephants on woody vegetation cover varies from place to place. In part this may be due to the way elephants utilize space across landscapes and within their home ranges in response to the availability and distribution of food. We used location data from 18 cows at six study sites across an east to west rainfall gradient in southern Africa to test whether wet- and dry-season home-range sizes, evenness of space use within seasonal home ranges and range overlap between seasons and between years, differed between wet and dry savannas. We then tested whether the quantity, distribution and seasonal stability in vegetation productivity, a coarse measure of food for elephants, explained differences. Elephants in wet savannas had smaller wet- and dry-season home ranges and also returned to a higher proportion of previously visited grid cells between seasons and between years than elephants living in dry savannas. Wet-season home-range sizes were explained by seasonal vegetation productivity while dry-season home-range sizes were explained by heterogeneity in the distribution of vegetation productivity. The influence of the latter on dry-season home ranges differed among structural vegetation classes. Range overlap between seasons and between years was related to inter-seasonal and inter-annual stability in vegetation productivity, respectively. Evenness of elephant spatial use within home ranges did not differ between savanna types, but it was explained by seasonal vegetation productivity and heterogeneity in the distribution of vegetation productivity during the wet season. Differences in elephant spatial use patterns between wet and dry savannas according to vegetation structure and season may need to be included in the development of site-specific objectives and management approaches for African elephants.     

Environmental factors and population fluctuations of Akodon azarae (Muridae: Sigmodontinae) in central Argentina

The aim of this work was to explore the relationship between population density of Akodon azarae (Muridae: Sigmodontinae) and climatic and environmental variables, and determine which of them are associated to within and among‐year changes in rodent abundance in agro‐ecosystems from south Córdoba, Argentina. The study was carried out in a rural area of central Argentina, from 1983 to 2003. Density was estimated as a relative density index (RDI). Temperature, precipitation and humidity were obtained from records of the National University of Rio Cuarto. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature were recorded from National Oceanic and Atmospheric Administration (1983–1998) and Landsat (1998–2003) imagery data sets. We performed simple correlations, multiple regressions and distributed lag analysis. Direct association of climatic and environmental variables with RDI was in general, low. The amount of variability in seasonal changes in density explained by climatic and environmental variables altogether varied from 10% to 70%. Seasonal population fluctuations were influenced by NDVI and rainfall with one and two seasons of delay. Autumn maximum density of the species was also associated with vegetation and rainfall of previous seasons. There also seemed to be an indirect influence of rainfall through vegetation given that we found a positive correlation between them. Results were consistent with basic aspects of the ecology of the species, such as its strong preference for highly covered areas, which provide food and protection from predators, likely increasing its reproductive success. Therefore, in the rural area central Argentina, A. azarae showed seasonal fluctuations with delayed influence of rainfall and vegetation and indirect effects of rainfall.     

Resource heterogeneity and ungulate population dynamics

It has been suggested that climatic variation has the effect on the dynamics of arid and semi-arid grazing systems of reducing animal numbers below the level at which they have much impact on vegetation or soils, and that spatial heterogeneity in resource availability serves to buffer herbivores against climatic variation. Modelling was used to test these hypotheses and to examine the interacting effects of temporal and spatial variability in plant production on animal population dynamics and defoliation intensity. The model distinguishes areas of the range that are accessible during wet and dry seasons, and examines the effect of seasonal restrictions in foraging area. It was established that the animal population is in long-term equilibrium with dry-season resources, on which it depends for survival; that dry season resource areas and outlying areas thus operate in a source-sink manner; and that the ratio of these areas determines the strength of consumer-resource coupling outside the dry-season range. A high ratio of dry season to wet season resources may support a sufficiently large animal population to impose non-trivial defoliation impacts on the outlying range. Increasing degrees of variability in primary production on areas used by animals for surviving the dry season increased the annual variation in animal abundance and reduced the mean. By comparison with a stable environment, for which the model predicts virtually stable animal numbers and constant, low defoliation intensity, variation in annual rainfall causes wide fluctuations in animal numbers and defoliation intensity. Under climatic variation, animal numbers can build up enough to impose much higher defoliation intensities than under a constant regime. Periodic intense defoliation is a consequence of climatic variability which is likely to make these environments more, not less, prone to ecological change.     

Species richness, diversity and biomass production of desert annuals in an ungrazed Rhanterium epapposum community over three growth seasons in Kuwait

Two blocks, each consisting of twelve 0.25 m²permanent plots, were established in a community dominated by desert annuals inan area of Kuwait protected from grazing, and community attributes wereinvestigated over three growth seasons. A linear relationship was found betweenestimated desert annual cover and biomass production. Species frequency wasassessed by the number of 100 cm² subplots occupied byaspecies in a block (block incidence). Over the three seasons,vegetation features varied considerably. The first season (spring 1997) wascharacterised by very sparse vegetation cover, low vegetation block incidence(sum of individual block incidences of each species present in a block) and lowspecies richness. The second season (spring 1998) had high vegetation cover,relatively low vegetation block incidence, but high species richness. In thethird season (spring 2000), vegetation cover was very sparse (as in 1997), butboth blocks had the highest vegetation block incidence of the three years andspecies richness was moderately high, although individual plants were verysmall. The growth period was much shorter in the very productive andspecies-rich 1998 season than in 2000. Fluctuations in biomass and speciesincidence coincided with pronounced variation in key meteorological variables,in particular the onset of the first rains, the amount of rainfall during thegrowing season and its temporal distribution. Species composition, however,appears mainly to be determined by the amount and possibly the timing of thefirst rainfalls of the season to trigger germination. There was little evidenceto suggest that particularly favourable or unfavourable microsites existed inplots for more than one vegetation period, either for individual species or fordiversity in general. Despite substantial between-season fluctuations inincidence, the relative abundances of the more frequent species to each otherremained broadly similar over the three seasons, with Plantagoboissieri being the predominant species and accounting for thelargest proportion of biomass.     

Seasonality of insect abundance in an Australian upland tropical rainforest

Monthly light and Malaise trap catches, taken over 31 months, were used to examine seasonal and annual changes in the abundance of predominant orders of upland tropical rainforest insects. Insect numbers and biomass increased during the late dry season, reached a peak during the wetter months, and declined during the early dry period. Fluctuations in insect abundance appeared to relate to (1) climatic factors such as length and severity of the dry season, or amount and period of rainfall; and (2) food availability such as an increase in the production of new leaves, or flowering and fruiting periodicity.     

全球气候变暖胁迫下的雅鲁藏布江流域植被覆盖度变化驱动机制探讨

为了解雅鲁藏布江流域内植被变化对气候变化响应的时空差异性,引入重心模型,分析和探讨了2002-2014年雅鲁藏布江流域植被的变化特点与气候因子的相关性。结果表明,植被的NDVI(归一化植被指数,Normalized difference vegetation index)重心与降水重心年际迁移方向具有正相关性。雅鲁藏布江流域的月植被NDVI受前0-1月降水影响最大,而不同季节植被的NDVI对降水影响表现出一定的滞后性,其中春季和冬季的植被NDVI均与前一季的降水呈现正相关性。该流域中乔木、灌木对降水反应的滞后性比草本植物要大;生长季的温度变化与植被的生长具有相关性。植被NDVI与月均温的正相关性达到最大的时间段差异较大。因此,植被NDVI和气候因子间的时空异质性研究对于雅鲁藏布江流域的生态环境保护具有重要意义。     

Environmental controls of NDVI dynamics in Patagonia based on NOAA-AVHRR satellite data

Abstract. Variation in vegetation in extra-Andean Patagonia (Argentina) was analyzed using spectral data derived from AVHRR/NOAA satellite. The study of seasonal dynamics of the Normalized Difference Vegetation Index (NDVI, i.e. a combined index of the reflection in the red and infrared bands) highlighted similarities in functional aspects between regional vegetation units which are dissimilar in a geographical, physiognomical and/or floristical way, and also suggested that gross primary production is correlated with mean annual rainfall. The first axis in a Principal Component Analysis of NDVI data was correlated (r² = 0.90) with NDVI as integrated for the study period. The second axis was correlated (r² = 0.50) with the differences in NDVI during the growing season, reflecting seasonality. Mean annual rainfall accounted for 60% of integrated NDVI variability among vegetation units. Much of the residual variance (62%) was accounted for by the inverse of the distance to the Atlantic Ocean, which is interpreted as an ocean effect on vegetation functioning in the extra-Andean Patagonia.     

Rangeland vegetation dynamics and moisture availability in Tunisia: an investigation using satellite and meteorological data

Improved knowledge of the interactions between regional climatic patterns and vegetation dynamics are necessary for predicting the future impacts of climate change on vegetation and biogeochemical processes. This paper describes how Normalized Difference Vegetation Index (NDVI) images generated from Advanced Very High Resolution Radiometer (AVHRR) satellite data were used to investigate the dynamics of rangeland vegetation in Tunisia. The NDVI images provided information about intra- and inter-annual variations in vegetation over nine growing seasons (1983–1992). Comparison of the NDVI data with field-collected ecological parameters for nine individual field sites indicated a strong relationship between the NDVI and percentage vegetation cover. The relationship between biomass measurements and NDVI was, however, less strong. Rainfall and NDVI data for each field site were compared, and significant relationships were found between the two. These indicated that there was a delay in the vegetation response to rainfall. In addition, the NDVI data showed that the vegetation at some of the field sites remained active throughout the summer although there was no rainfall during this period. TuMERT (Tunisian Model to Estimate Rangeland Transpiration), a simple water-balance model, was developed to estimate the amount of rainfall available for use by the vegetation during transpiration. The estimates of actual transpiration derived from TuMERT were found to be more strongly correlated with the AVHRR-NDVI measurements than the rainfall data.     

An NDVI analysis of vegetation trends in an Andean watershed

We performed a Landsat 5-TM derived normalized difference vegetation index (NDVI) analysis in a semi-arid watershed (2700 km²) in the Andes of southern Peru from 1985 to 2010. There, pastoralists rely on wetlands (bofedales) particularly during dry season months and in drought. We calculated annual dry season NDVI for 20 of the 26 years from 1985 to 2010 and used the mean to delineate wetlands in the watershed. To investigate the trends in NDVI, a multiple regression model with the covariates precipitation, temperature, Julian day, and year of image acquisition was performed on each cell (three million individual regressions). Results indicate there is a modest increase in NDVI for the majority of cells (81 %) in the watershed. Approximately 30 % of wetland areas display a decrease in NDVI. Dry season NDVI is moderately correlated with wet season precipitation (R ² = 0.56, p < 0.05) but absent a trend in precipitation, NDVI trends are not explained by this variable. Changes in land management may result in more intensive use of wetlands, causing the decreasing vegetation trends in some locations.     

Divergent response of seasonally dry tropical vegetation to climatic variations in dry and wet seasons

Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO₂ growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index (NDVI), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant (p < 0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature (γ^int) and to precipitation (δ^int). γ^int is ~1% °C^?1 more negative and δ^int is ~8% 100 mm^?1 more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in γ^int can be explained by background moisture and temperature conditions. Positive γ^int occurred in wet season where mean temperature is lower than 27°C and precipitation is at least 60 mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity (GPP) estimates (empirical modeling by machine‐learning algorithm applied to flux tower measurements, and nine process‐based carbon cycle models) were examined for the GPP–climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of γ^int, while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis–climate relationship and thus the projection for impacts of climate change on tropical carbon cycle.     

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.     

Understanding and improving access to prompt and effective malaria treatment and care in rural Tanzania: the ACCESS Programme

Background

Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was subject to widespread malaria epidemics in 1997 and 1998. This study examined the relationship between climate and malaria incidence in Kagera with the aim of determining whether seasonal forecasts may assist in predicting malaria epidemics.

Methods

A regression analysis was performed on retrospective malaria and climatic data during each of the two annual malaria seasons to determine the climatic factors influencing malaria incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic anomalies associated with malaria epidemics was then assessed for each malaria season.

Results

It was found that malaria incidence is positively correlated with rainfall during the first season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria incidence was associated with increased rainfall, but also with high maximum temperature during the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical models was tested by excluding the two epidemic years from the regression analysis. DEMETER would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic. Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone. The 1997 epidemic could have been predicted from observed temperatures in the preceding season, but the consideration of the rainfall forecasts would have improved the temperature-only forecasts over the remaining years.

Conclusion

These results demonstrate the potential of a seasonal forecasting system in the development of a malaria early warning system in Kagera region.     

Periodicity and environmental drivers of apical and lateral growth in a Cerrado woody species

Key message

Apical and lateral growth are seasonal in a Cerrado species, and these events are related to each other and linked with climatic and environmental features.

Abstract

In the Cerrado, a tropical ecosystem with seasonal rainfall, we investigated the timing of leaf production and cambial activity, and checked whether these features are related to each other and with climatic and environmental factors. Between September 2011 and December 2012, sampling of main stem and vegetative phenological observations of Kielmeyera grandiflora (Wawra) Saddi (Calophyllaceae) were done monthly to assess seasonality in leaf production and cambial activity, and to compare these features with each other. To check the relationship of bud opening and the onset of cambial activity with climatic and environmental features, the average temperature and day length, and the precipitation sum in a time window ranging from 1 to 30 days before the occurrence of these events were recorded, and the coefficient of variation was calculated. Leaf production and cambial activity were seasonal. Bud opening occurred in September 2011 and August 2012, during the dry season. The onset of cambial activity occurred in October both in 2011 and 2012, 1–2 months after bud opening, at the beginning of the rainy season. The cambium was dormant in May, during the rainy season. Photoperiod and temperature showed low coefficients of variation in the time window before bud opening and onset of cambial activity, while rainfall presented a high coefficient of variation. Thus, both apical and lateral growth are seasonal events in Cerrado species, and are related to each other. A set of climatic and environmental features is related with seasonal growth, among which photoperiod and temperature may be important in the regulation of these events.

     

Can Saturniidae moths be bioindicators? Spatial and temporal distribution in the Brazilian savannah

Some moths species are considered good indicators of habitat quality because they are very responsive to human disturbance, vegetation type, and successional processes. However, Saturniidae moths have not yet been considered as indicators of environmental quality. Little is known on the distribution of moth species in different vegetation types and the moths’ seasonal variations in the Brazilian savannah. Therefore, this study aims to describe the spatial distribution and temporal patterns of moths belonging to the Saturniidae family in two vegetation types—Cerrado sensu stricto on rocky outcrops and semi-deciduous forest—in both the rainy and dry seasons. It addresses the influence of the climatic seasons and vegetation types on abundance, richness, and species composition to describe the temporal and spatial distribution patterns and the relationship between the ecological aspects and the life history of these moths. This study was conducted in the Cerrado phytogeographical domain, in Pireneus State Park, Goiás, Brazil. The results revealed that most Saturniidae species sampled are present during the rainy season and typically found in forest habitats. Furthermore, a clear positive connection was found between the abundance pattern and rainfall seasonality and humid habitats; this is apparently related to the physiological tolerance of these moths, due to rudimentary mouthparts during their adulthood. Thus, rainfall and a forest habitat are important to and fundamental requirements for the persistence of the Saturniidae species in the Cerrado domain. Based on the results of this study, we suggest the use of saturniid species as indicators of changes in vegetation and climatic conditions.     

Climate change impact on Amazonian ant gardens

In Amazonia higher Atlantic sea surface temperatures, greenhouse gasses, deforestation and El Niño events result in the greater frequency of severe droughts, although total rainfall has increased due to wetter rainy seasons, something confirmed in French Guiana from available climatic data (1980–2017). Aiming to study the impact of rainfall on ant gardens (i.e., arboreal ant-epiphyte mutualisms that depend on the atmosphere for water; AGs) initiated by the ponerine ant Neoponera goeldii, we conducted surveys around the Petit Saut and Régina areas (mean annual rainfall: ≈3,000 mm and ≈4,000 mm, respectively). Each year, near the end of the dry season we recorded the number of these AGs in 10 × 5 m sections parallel to the roadsides. The Petit Saut survey (1993–2017) revealed that AG density along roadsides varied only slightly in "wet zones" situated along ditches, whereas in "dry zones" where the soil seasonally dries out it dropped sharply during the drastic 1997 dry season. Then, this density, low due to recurrent droughts, dropped again during the drastic successive 2015–2016 dry seasons. In the Régina survey (2006–2017), we had the opportunity to follow the establishment of AGs in a "dry zone". It was represented by a typical sigmoidal curve and then it stabilized with AG densities higher than at its peak in 1996 in dry zones of Petit Saut, showing the importance of rainfall. Here, too, the drastic 2016 dry season adversely affected the AGs. Finally, the epiphytic composition of the AGs was mainly represented by Aechmea mertensii (a tank bromeliad), Anthurium gracile (Araceae) and Codonanthe crassifolia (Gesneriaceae), but AGs with the tank bromeliad are more resistant to droughts. These AGs are at risk in dry zones if drastic successive dry seasons occur in the future as global warming intensifies while those developing in riparian areas might survive.     

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.     

Responses of Tree Transpiration and Growth to Seasonal Rainfall Redistribution in a Subtropical Evergreen Broad-Leaved Forest

Precipitation changes such as more frequent drought and altered precipitation seasonality may impose substantial impacts on the structure and functioning of forest ecosystems. A better understanding of tree responses to precipitation changes can provide fundamental information for the conservation and management of forests under future climate regimes. We conducted a 2-year seasonal rainfall redistribution experiment to assess the responses of tree transpiration and growth to manipulated precipitation changes in a subtropical evergreen broad-leaved forest. Three precipitation treatments were administered including a drier dry season and wetter wet season treatment (DD), an extended dry season and wetter wet season treatment (ED), and an ambient control treatment, with the total amount of annual rainfall being kept the same among the three treatments. Our results showed that the DD and ED treatments reduced daily transpiration of Schima superba by 8–16 and 13–25%, respectively. The ED treatment also reduced the DBH increment of larger S. superba individuals. In contrast, neither treatment showed obvious effects on the transpiration and DBH increment of another dominant species Michelia macclurei. However, the transpiration of both species showed clear inter-annual differences between the 2 years with contrasting annual rainfall (2094 vs 1582 mm). S. superba had a lower transpiration-to-precipitation ratio (T/P) compared to M. macclurei and showed decreased sensitivities to total solar radiation and vapor pressure deficit under the DD and ED treatments. These results indicate the deep-rooted S. superba may be suppressed with a lower ability to obtain water and assimilate carbon compared to the shallow-rooted M. macclurei under the precipitation seasonality changes, which could potentially cause shifts in species dominance within the forest community.