Phenological description of natural vegetation in southern Africa using remotely‐sensed vegetation data

Abstract. Various attempts have been made to describe and map the vegetation of southern Africa with recent efforts having an increasingly ecologi cal context. Vegetation classification is usually based on vegetation physiognomy and floristic composition, but phenology is useful source of information which is rarely used, although it can contribute functional information on ecosystems. The objectives of this study were to identify a suite of variables derived from time‐series NDVI data that best describe the phenological phenomena of vegetation in southern Africa and, secondly, to assess a classification of pixels of the study area based on NDVI variables using a preexisting map of the biomes that was delimited on the basis of life forms and climate. A number of variables were derived from the satellite data for describing phenological phenomena, which were analysed by multivariate techniques to determine which variables best explained the variation in the satellite data. This set of variables was used to produce a phenological classification of the vegetation of southern Africa, the results of which are discussed in relation to their concordance with the existing biome boundaries.     

Implementation of a hierarchical global vegetation classification in ecosystem function models

Abstract. We propose an alternative approach for the currently used biogeographic global vegetation classifications. A hierarchical vegetation classification system is proposed for consistent and routine monitoring of global vegetation. Global vegetation is first defined into six classes based on plant canopy structure and dynamics observable by remote sensing from satellites. Additional biome variability is then represented through a remote sensing derived leaf area index map, and direct climate data sets driving an ecosystem model to compute and map net primary production and evapotranspiration. Simulation results from an ecosystem function model suggest that the six canopy structure-based classes are sufficient to represent global variability in these parameters, provided the spatio-temporal variations in Leaf Area Index and climate are characterized accurately. If a bioclimatically based classification is needed for other purposes, our six class approach can be expanded to a possible 21 classes using archived climatic zones. For example, tropical, subtropical, temperate and boreal labels are defined by absolute minimum temperature. Further separation in each class is possible through changes in water availability defined by precipitation and/or soils. The resulting vegetation classes correspond to many of the existing, conventional global vegetation schemes, yet retain the measure of actual vegetation possible because remote sensing first defines the six biome classes in our classification. Vegetation classifications are no longer an end product but a source of initializing data for global ecosystem function models. Remote sensing with biosphere models directly calculates the ecological functions previously inferred from vegetation classifications, but with higher spatial and temporal accuracy.     

A Temporally Explicit Production Efficiency Model for Fuel Load Allocation in Southern Africa

Abstract We present a regional fuel load model (1 km² spatial resolution) applied in the southern African savanna region. The model is based on a patch-scale production efficiency model (PEM) scaled up to the regional level using empirical relationships between patch-scale behavior and multi-source remote sensing data (spatio-temporal variability of vegetation and climatic variables). The model requires the spatial distribution of woody vegetation cover, which is used to determine separate respiration rates for tree and grass. Net primary production, grass and tree leaf death, and herbivory are also taken into account in this mechanistic modeling approach. The fuel load model has been calibrated and validated from independent measurements taken from savanna vegetation in Africa southward from the equator. A sensitivity analysis on the effect of climate variables (incoming radiation, air temperature, and precipitation) has been conducted to demonstrate the strong role that water availability has in determining productivity and subsequent fuel load over the southern African region. The model performance has been tested in four different areas representative of a regional increasing rainfall gradient—Etosha National Park, Namibia, Mongu and Kasama, Zambia, as well as in Kruger National Park, South Africa. Within each area, we analyze model output from three different magnitudes of canopy coverage (<5, 30, and 50%). We find that fuel load ranges predicted by the model are globally in agreement with field measurements for the same year. High rainfall sustains green herbaceous production late in the dry season and delays tree leaf litter production. Effect of water on production varies across the rainfall gradient with delayed start of green material production in more arid regions.     

Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover

Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad‐scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape‐scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite‐measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time‐series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation–environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation‐ and community‐specific patterns of vegetation dynamics across the gradient. Main conclusions In addition to the environmental factors usually considered – climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance – woody plant cover, a broad‐scale proxy of many vegetation–environment interactions, represents an ecological dimension that provides additional process‐related understanding of landscape‐scale patterns of vegetation function.     

基于GIS和RS的广东陆地植被生产力及其时空格局

在GIS和RS工具支持下,利用多时相遥感数据NOAA-AVHRRNDVI和地面气象数据研究了广东陆地植被净第一性生产力及其时空分布.结果表明广东陆地植被净第一性生产力的遥感估算值与实测值接近,效果较好;广东陆地植被净第一性生产力介于0～1568.9gC/(m2*a)之间,年平均净第一性生产力约为753.2(±277.0)gC/(m2*a),全省陆地生态系统每年约固定碳1.34×1014g.广东陆地植被净第一性生产力的地区差异显著,反映了广东陆地植被因受人类活动影响而比较破碎的特点;同样,广东陆地植被净第一性生产力的年变化显著,夏半年约为冬半年的4倍以上,这主要与该地区气温和水分条件的季节变化有关;即使是常绿阔叶林,其年净第一性生产力也有明显差异,且年变化显著.     

First approximation to a phenology of the honeybees (Apis mellifera) and flora of Africa

Peak flowering by the total flora of Africa coincides with or immediately follows peak rainfall. Flowering intensity of the total flora decreases with distance from the equator, but that of the honeybee plant resource base (±2% of total flora) does not. Flowering in the latter is highly synchronous (months 1–5 north of and 9–11 south of the equator). Both total and honeybee flora are completely incongruent with either the biomes or phytochoria of Africa. There is no significant correspondence between honeybee phenology and the total flora but significant correspondence occurs between honeybees and flowering in honeybee plant genera. A logistic regression model reveals that honeybee plant flowering predicts major honeybee colony events with a probability of 0.81 south of the equator and 0.71 for the whole continent. It is postulated that promiscuity in the bee plant genera and honeybees of Africa have contributed to their continental ubiquity.     

Univariate analysis of tsetse habitat in the common fly belt of Southern Africa using climate and remotely sensed vegetation data

Abstract Tsetse are vectors of trypanosomes that cause diseases both in humans and livestock. Traditional tsetse surveys, using sampling methods such as Epsilon traps and black screen fly rounds, are often logistically difficult, costly and time-consuming. The distribution of tsetse, as revealed by such survey methods, is strongly influenced by environmental conditions, such as climate and vegetation cover, which may be readily mapped using satellite data. These data may be used to make predictions of the probable distribution of tsetse in unsurveyed areas by determining the environmental characteristics of areas of tsetse presence and absence in surveyed areas. The same methods may also be used to characterize differences between tsetse species and subspecies. In this paper we analyse the distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes in southern Africa with respect to single environmental variables. For G.m.centralis the best predictions were made using the average NDVI (75% correct predictions; range > 0.37) and the average of the maximum temperature (70% correct predictions; 27.0–29.2°C). For G.m.morsitans the best prediction was given by the maximum of the minimum temperature (84% correct predictions; range > 18.8°C), and for G.pallidipes , also by the maximum of the minimum temperature (86% correct predictions; range > 19.6 °C). The following paper compares a range of multivariate techniques for making predictions about the distribution of these species in the same region.     

利用GIS和RS估算广东植被光利用率

在ＧＩＳ和ＲＳ工具的支持下,利用地面气象数据和卫星遥感数据研究了广东植被的光利用率及其时空分布。结果表明：Ｐｏｔｔｅｒ和Ｆｉｅｌｄ等提出和使用的全球植被月最大光利用率０．３８９ｇＣ Ｍｊ＾－１,对于 广东植被来讲,此值偏低;广东植被的年来均光利用度介于０．６９～１．０５ｇＣ Ｍｊ＾－１之间,预测值与实测值一致,效果较好;广东植被光利用率的年变化显著,冬半年的平均值约为夏半年的一半,这主要是因为该区     

南非Hluhluwe-Umfolozi公园植被对非洲狮群大小的影响

非洲狮(Pantheraleo)群处于不断的分裂-聚合过程,其亚群大小与原狮群大小以及诸如狮群捕食成功度、协作幼仔保护及狮群领域防卫等社会性因素有关。我们分析了南非一个保护区(Hluhluwe-Umfolozi公园)15年间的狮群大小,其成年雌狮和成年雄狮群的大小在保护区内呈显著性变化。在开放生境中雌狮结大群,而茂密植被生境中则结小群。雄狮群大小与植被类型无关,但在大的雌狮群分布区域发现大雄狮群。令人惊奇的是,作为幼狮成活率指标的幼狮群大小和雌狮平均幼仔数在保护区内没有显著性差异。我们认为,雌狮群大小的不同是对植被结构的适应,即在开放生境中大群有利于协作狩猎、育幼、共同保护幼仔、应对高强度群间领域防卫竞争。相反,茂密植被中,群间竞争很低,高密度植被覆盖有利于狩猎成功及补偿小狮群对幼仔保护的不足。雌狮平均幼仔数在整个保护区内没有变化,我们认为是由于开放生境和茂密植被对狮群大小起到相似的调节作用     

2001年以来宝鸡地区植被覆盖时空演变及驱动力分析

植被在全球变化中影响着地-气系统的能量平衡,是自然和人文因素对环境影响的敏感指标。分析地表植被的覆盖现状并探究影响植被变化的驱动力因素对区域生态恢复以及区域经济发展和区域生态文明建设都有促进作用。本研究基于中分辨率成像光谱仪-归一化植被指数（MODIS-NDVI）数据,结合宝鸡11个气象站的气温和降水量实测数据、净初级生产力（NPP）以及宝鸡统计年鉴数据,采用趋势分析方法、Pearson相关分析法、主成分分析方法对2001-2013年宝鸡地区植被覆盖的时空演化特征进行了分析,并对自然驱动因子和人为驱动因子双重影响下的宝鸡地区植被覆盖演化状况进行了综合评价。结果显示：（1）2001-2013年宝鸡地区年均NDVI以0.025/10a的速度上升,比三北防护林工程区1982-2006年植被覆盖的增速（0.007/10a）快,且2001-2002年、2003-2004年两个年份段为年均NDVI值的两次高恢复期;（2）植被覆盖以轻度改善为主,基本不变和中度改善次之,严重退化和中度退化最弱。植被覆盖恢复状况整体上呈稳中上升的趋势（个别地区除外）;（3）自然因素中的降水量和NPP是制约植被生长的主要因素。整体来看,人为因素相对于自然因素对宝鸡全区的植被覆盖影响较大,贡献率在90%左右,呈先减小后增加的趋势。     

Cambial activity and annual rhythm of xylem production of Pinus kesiya Royle ex. Gordon (Pinaceae) in relation to phenology and climatic factors growing in sub-tropical wet forest of North East India

The interrelationship between phenological events, climatic factors, periodicity of cambial activity and seasonal production of xylem was examined in Pinus kesiya Royle ex. Gordon growing in sub-tropical wet forest of Meghalaya state, India. Reactivation of dormant cambium occurs after sprouting of new needles during the middle of February. Since the formation of reproductive cones takes place simultaneously with vegetative bud break and needle formation, cone formation could also lead to the enhancement of cambial activity. The activity of cambium and xylem production decline gradually towards November and cease from end of December to end of January. There was no correlation between needle fall and cambial activity. Due to the production of three flushes of new needles and branches in a year the tree never becomes completely leafless. It was evident from correlation and regression analysis that the annual course of average temperature plays an important role for the reactivation of vascular cambium after dormancy. The differentiation of xylem elements correlated with mean temperature in the first place and secondly with precipitation. Increase in length of fusiform initials and their derivatives could be correlated with relative humidity, precipitation and mean maximum temperature. Dormancy was imposed by low temperature and less precipitation. The data are discussed in the light of cambial activity, xylem production and phenological events.     

Mapping tsetse habitat suitability in the common fly belt of Southern Africa using multivariate analysis of climate and remotely sensed vegetation data

Abstract The distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes are described in part of southern Africa, using a range of multivariate techniques applied to climate and remotely sensed vegetation data. Linear discriminant analysis is limited in its predictive power by the assumption of common co-variances in the classes within multivariate environment space. Maximum likelihood classification is one of a variety of alternative methods that do not have this constraint, and produce a better prediction, particularly when a priori probabilities of presence and absence are taken into account. The best predictions are obtained when the habitat is subdivided, prior to classification, on the basis of a bimodality detected on the third component axis of a principal component analysis. The results of the predictions were good, particularly for G.m.centralis and G.m.morsitans , which gave overall correct predictions of 92.8% and 85.1 %, with a Kappa index of agreement between the predion and the training data of 0.7305 and 0.641 respectively. For G.pallidipes , 91.7% of predictions were correct but the value of Kappa was only 0.549. Very clear differences are demonstrated between the habitats of the two subspecies Gmxentralis and G.m.morsitans.     

Woody vegetation of a mosaic of protected areas adjacent to the Kruger National Park,South Africa

Question: How is pattern detected and spatial scale defined in a manner that is meaningful to management? Location: Protected areas to the west of the Kruger National Park, South Africa. Methods: A Two‐Way Indicator Species Analysis (TWIN‐SPAN) based on composition and structure was applied to woody survey data. The resulting TWINSPAN classes for individual monitoring sites were used in a supervised classification of Landsat ETM⁺ imagery across the study area. The training sample's co‐ordinates were fed into a GIS and the resulting TWINSPAN point‐feature shape file was processed using a 1 km theme‐buffer function. Results: The supervised classification using the theme‐buffer signatures yielded a satisfactory overall accuracy (κ= 0.75; r²= 0.80; p= 0.05) using a test sample compiled by reserve wardens throughout the study area. The derived vegetation map was smoothed using a majority filter and after on‐screen digitizing a small gabbro intrusion, it was accepted as the best representation of the woody vegetation of the study area at a scale of 1:250 000. Seven plant communities were identified in the current study and satisfactorily accommodated within various topographical units of four extrapolated Landscapes of the Kruger National Park. Conclusions: Vegetation patterns are described of the areas under conservation management to the west of the KNP at a spatial scale that allows for the meaningful examination and comparison of the structure, functioning, and ultimately effective management, of these savannas. This contribution thus links to the co‐ordinated effort extending into the Trans‐Frontier National Park in Mocambique. A key objective is to better understand the functioning of these savanna systems for effective management and we discuss some of the key ecological issues within the plant communities of each landscape. The latter illustrate the usefulness of the technique in practice.     

Long-term landscape changes in vegetation structure: fire management in the wetlands of KwaMbonambi,South Africa

In wetlands the effects of fire on vegetation dynamics are somewhat uncertain. A change detection analysis in the herbaceous wetlands of KwaMbonambi, South Africa, which were subject to frequent fires, revealed that in 1937 the study area comprised grassland (69%), herbaceous wetland (25%), indigenous swamp forest (4%) and tree plantations (1%). However, by 1970, tree plantations occupied 78% of the landscape and grasslands and herbaceous wetlands had declined to 9% and 6%, respectively, whereas indigenous swamp forest had increased to 6%. By 2009 tree plantations had been removed from the wetland areas. Despite this opportunity for herbaceous wetlands to recover their historical extent, they decreased to only 2%, mostly changing to indigenous swamp forest or to an herbaceous/fern (Stenochlaena tenuifolia)/woodland mosaic. Fire records showed suppression of fire to be an important contributing factor, particularly in wetlands that had been disturbed by tree plantations, although subsequently removed. A pilot burning experiment revealed that S. tenuifolia did not inhibit fire. It is therefore practicable to increase fire frequency to prevent the mosaic developing into forest. A conceptual model of the influence of fire regime on wetland vegetation type is presented and priorities for further research on wetlands and fire are recommended.     

Interannual Variability in Terrestrial Net Primary Production: Exploration of Trends and Controls on Regional to Global Scales

Climate and biophysical regulation of terrestrial plant production and interannual responses to anomalous events were investigated using the NASA Ames model version of CASA (Carnegie–Ames–Stanford Approach) in a transient simulation mode. This ecosystem model has been calibrated for simulations driven by satellite vegetation index data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. Relatively large net source fluxes of carbon were estimated from terrestrial vegetation about 6 months to 1 year following El Niño events of 1983 and 1987, whereas the years 1984 and 1988 showed a drop in net primary production (NPP) of 1–2 Pg (10¹⁵ g) C from their respective previous years. Zonal discrimination of model results implies that the northern hemisphere low latitudes could account for almost the entire 2 Pg C decrease in global terrestrial NPP predicted from 1983 to 1984. Model estimates further suggest that from 1985 to 1988, the northern middle-latitude zone (between 30° and 60°N) was the principal region driving progressive increases in NPP, mainly by an expanded growing season moving toward the zonal latitude extremes. Comparative regional analysis of model controls on NPP reveals that although Normalized Difference Vegetation Index “greenness” can alone account for 30%–90% of the variation in NPP interannual anomalies, temperature or radiation loading can have a fairly significant 1-year lag effect on annual NPP at middle- to high-latitude zones, whereas rainfall amount and temperature drying effects may carry over with at least a 2-year lag time to influence NPP in semiarid tropical zones.     

Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China

The objectives of this study are to explore the relationships between plant phenology and satellite-sensor-derived measures of greenness, and to advance a new procedure for determining the growing season of land vegetation at the regional scale. Three phenological stations were selected as sample sites to represent different climatic zones and vegetation types in northern China. The mixed data set consists of occurrence dates of all observed phenophases for 50–70 kinds of trees and shrubs from 1983 to 1988. Using these data, we calculated the cumulative frequency of phenophases in every 5-day period (pentad) throughout each year, and also drew the cumulative frequency distribution curve for all station-years, in order to reveal the typical seasonal characteristics of these plant communities. The growing season was set as the time interval between 5% and 95% of the phenological cumulative frequency. Average lengths of the growing season varied between 188 days in the northern, to 259 days in the southern part of the research region. The beginning and end dates of the surface growing season were then applied each year as time thresholds, to determine the corresponding 10-day peak greenness values from normalized difference vegetation index curves for 8-km² pixels overlying the phenological stations. Our results show that, at the beginning of the growing season, the largest average greenness value occurs in the southern part, then in the northern, and finally the middle part of the research region. In contrast, at the end of the growing season, the largest average greenness value is measured in the northern part, next in the middle and lastly the southern part of the research region. In future studies, these derived NDVI thresholds can be applied to determine the growing season of similar plant communities at other sites, which lack surface phenological data. Received: 29 November 1999 / Revised: 14 March 2000 / Accepted: 15 March 2000     

Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes

1. A Dynamic Global Vegetation Model (DGVM) has been developed as a new feature of the NASA-CASA (Carnegie Ames Stanford Approach) ecosystem production and trace gas model. This DGVM includes seasonal phenology algorithms calibrated using historical interannual data sets derived from the Advanced Very High Resolution (AVHRR) satellite ‘greenness’ index. 2. The coupled CASA-DGVM design is based conceptually on two main elements of Tilman's resource-ratio hypothesis of vegetation change, namely: 1) plant competition for resources (water and light) over relatively short time periods of months and seasons; and 2) the long-term pattern in the supply of growth-limiting resources such as water and nutrients, i.e. the resource-supply trajectory. This simulation model generates global gridded estimates of primary production, above and below ground biomass, leaf area index (LAI), and trace gas fluxes from soil. 3. Eight distributed test locations for the DGVM were evaluated initially to represent a variety of climate conditions ranging from Arctic (64°N Alaska) to tropical and subtropical (24°S southern Africa) latitude zones. At all test locations, the predicted plant functional type (PFT) matched closely with the actual reported PFT. 4. In the process of running the model to steady state PFTs, most forest locations showed a rapid progression of transient states, from bare ground to grassland, to grasses with shrub cover, and finally to the forest PFT. From this first global application, the DGVM correctly predicts the presence of forest classes in approximately 75–95% of all cases worldwide, and grasslands in approximately 58% of all cases. 5. The effects of two hypothetical climate change scenarios were evaluated. Scenario I was set by warming air surface temperatures linearly to 4 °C above average over a 25-year simulation period. Scenario II was set by decreasing annual rainfall amounts linearly to 50% below average over a 25-year simulation period. 6. The warming scenario I resulted in PFT at high-latitude forest and boreal forest sites changing to mixed coniferous forest, accompanied by increase in canopy LAI. The drought scenario II resulted in PFT at the boreal forest and savanna sites changing to grasslands. At locations where PFT did not change with climate, however, soil water and canopy LAI were predicted to decline progressively under the warming scenario, beginning from steady-state temperate and tropical zone PFTs. They also declined under the drought scenario beginning from practically any steady state PFT.     

Above-ground biomass and vegetation attributes in the forest-savannah mosaic of Togo,West Africa

Despite the increasing interest in the role of African savannah and woodlands on the global carbon cycle, little is known about the above-ground biomass (AGB) and the factors affecting it in these ecosystems in West Africa. We estimated AGB in different vegetation types of a forest–savannah mosaic in Togo, and we investigated the relationship between AGB, structural and diversity attributes. We also assessed the effects of using the ≥5 or ≥10 cm diameter threshold on AGB estimates. We sampled tree diameter, height and species of all trees ≥5 cm diameter following standardised protocols in 160 plots of 50 × 20 m (50 × 10 m for riparian). Above-ground biomass (AGB) (all trees ≥5 cm diameter) ranged from 6.2 Mg/ha in shrub savannah to 292 Mg/ha in riparian forest and showed significant differences between vegetation types. Differences in AGB were related to structural attributes, with little influence of diversity attributes. The effects of minimum tree diameter size (5 or 10 cm) on AGB estimates were negligible. At a landscape level, closed-canopy and open forests stored important quantities of carbon. We highlight the importance of the forest–savannah mosaic as a large carbon pool, which could be released if converted to another land cover type.