Future Vegetation Changes Research Articles

Effects of ?realistic? land-cover change on a greenhouse-warmed African climate

The primary goal of this investigation is to focus on a “realistic” scenario for simulating impacts on regional African climate of future deforestation in a greenhouse-warmed world. Combined effects of plausible land-cover change and greenhouse warming are assessed by ‘time-slice’ simulations with an atmospheric general circulation model (AGCM) for the middle of the twenty first century. Three “time-slice” integrations have been performed with the ARPEGE-Climat AGCM incorporating a zooming technique to achieve a resolution of about 100 km over Africa. A control run for the current climate is forced by observed climatological sea surface temperatures (SSTs) and the observed vegetation distribution is specified from a new vegetation database, in order to improve the geographical distribution and properties of the vegetation cover. Future SST changes are derived from a transient coupled atmosphere–ocean simulation for scenario B2 of the International Panel on Climate Change (IPCC). Future vegetation changes are specified from a simulation of scenario B2 with the Integrated Model to Assess the Global Environment (IMAGE) developed at the National Institute of Public Health and the Environment in the Netherlands (RIVM). The results show that land surface processes can locally modulate greenhouse warming effects for African climate, with reductions of surface transpiration and small increases of surface temperature. Deforestation of tropical Africa has overall only a marginal effect on precipitation because of a compensatory increase in moisture convergence. Energy budget analyses show that increases in surface temperature are produced both by increases of greenhouse gases (GHG) concentration from the increase in downward atmospheric longwave radiation, and by African tropical deforestation from the resulting reduction in transpiration. This study indicates that realistic land-use changes, though of smaller amplitude than greenhouse gas forcing, may have a small regional effect in projections of future climate.

Climate- and human-induced woody vegetation changes in Botswana and their implications for human adaptation.

For purposes of suggesting adaptive and policy options regarding the sustained use of forestry resources in Botswana, an analysis of the whole countrywide satellite data (showing the mean present distribution of vegetation in terms of species abundance and over all density) and the projection of vegetation cover changes using a simulation approach under different climatic scenarios were undertaken. The analysis revealed that changes in vegetation cover types due to human and natural causes have taken place since the first vegetation map was produced in 1971. In the southwest, the changes appear to be more towards an increasing prevalence of thorn trees; in the eastern part of the country where widespread bush encroachment is taking place, the higher population density suggests more human induced (agrarian-degradation) effects, while in the sparsely settled central Kalahari region, changes from tree savanna to shrubs may be indicative of the possible influence of climate with the associated effects of fires and local adaptations. Projection of future vegetation changes to about 2050 indicates degeneration of the major vegetation types due to the expected drying. Based on the projected changes in vegetation, current adaptive and policy arrangements are not adequate and as such a shift from the traditional adaptive approaches to community-based types is suggested. Defining forestry management units and adopting different management plans for the main vegetation stands that are found in Botswana are the major policy options.

Soil seed banks and the effects of meadow management on vegetation change in a 10‐year meadow field trial

Summary Enhancement of plant species diversity is often an objective in grassland management for wildlife conservation. Such management regimes may also change the species composition of soil seed banks, which may themselves affect future vegetation change. We compared soil seed banks and vegetation from a long‐term meadow management trial and from a series of traditionally managed species‐rich meadows in northern England, UK. The management trial used three hay‐cut date treatments (14 June, 21 July and 1 September), two fertilizer treatments [no fertilizer or 25 kg nitrogen ha−1 plus 12·5 kg ha−1 phosphate (P2O5) and potash (K2O)] and two seed‐addition treatments (no seed, seed of many species sown 1990–92). Soil seed banks were assessed in 1998. Subsequent vegetation development under these treatments, and under an additional farmyard manure treatment, was assessed in 2000. Most seed was in the 0–5‐cm soil layer and most of the frequent species germinated in the autumn. Short‐ and long‐term persistent seed banks were most abundant. The species composition of the seed banks and the vegetation in the trial, and in the traditionally managed meadows used as a control, were distinctly different, the meadow trial seed bank being the most uniform. An ordination of simulated plant communities based on the UK National Vegetation Classification provided a wider framework for comparing vegetation and seed banks with the species composition of British meadow communities, some of which are also found in Europe. The soil seed banks throughout the meadow trial plots and the control fields were very similar in species composition to that of the vegetation in agriculturally improved meadows. However, there were many more species in the soil seed bank of the traditionally managed control meadows. In 2000, only the seed‐addition treatment increased the species richness of the vegetation. Farmyard manure and mineral fertilizer had similar effects, increasing the cover of Poa trivialis and Rumex acetosa and decreasing the cover of Rhinanthus minor and Anthoxanthum odoratum. It was concluded that the development of the soil seed bank probably lags behind increases in vegetation diversity initiated by seed sowing. This emphasizes the need to introduce additional species as seed when increased diversity is a target for the restoration management of previously intensively managed grasslands.

Assessing vegetation change over a century using repeat photography

Repeat photography is a technique of detecting changes in the landscape by comparing old and more recent photographs taken at the same place. Information gained is used to detect landscape change as one component of historical ecology. Understanding the causes of any change detected requires additional information. The technique was pioneered in vegetation ecology in Arizona and has since been applied in many other parts of the United States. After a description of the technique, the American experience is reviewed and the problems of detecting change and assigning cause are discussed. The relatively few Australian examples are briefly summarised. There are many limitations of repeat photography, but these can be controlled through a careful approach. Although repeat photography has rarely been used in Australia, it has significant applications in education, in understanding past changes and in helping to help predict future changes in vegetation.

Exploring spatial vegetation dynamics using logistic regression and a multinomial logit model

SummaryThis study presents statistical methodology that uses spatial explanatory variables to improve simpler estimates of transition probabilities from categorical data, such as vegetation type, that have been recorded as classified cells (pixels) in a grid or lattice at different times.A specific application is to examine successions in semi‐natural vegetation in north‐east Scotland. Questions related to these data include: Do transition probabilities of a pixel depend on the size of a patch of vegetation (polygon) and pixel location within the polygon? Do stable areas remain stable? Does the proximity of certain vegetation types influence transitions?We selected spatial variables that were likely to be important in this application, where short‐range vegetative spread was thought to be an important factor.The multinomial logit model is used to estimate the transition probabilities as a function of explanatory variables, including location, neighbourhood information and other factors recorded at the start of the transition period. This model allowed the testing of different assumptions about the dynamics of underlying processes leading to transitions.When the number of categories, for example vegetation types, observed is large in comparison to the sample size, estimates of transition probabilities can be unreliable. We show that using change of category within the time period as the response in a logistic regression can still provide insight to the underlying dynamics of change in such a case.The methods are illustrated with some Scottish vegetation classification data with pixels of size 5 × 5 m covering a square of area 0·25 km2. Two contrasting squares were investigated: the first was upland moorland grazed by sheep and the second was a lowland area with more varied vegetation and low intensity grazing by cattle.In both squares there are strong spatial trends, and the neighbourhood of a pixel affected its transition. Prediction misclassification rates estimated from different models were compared using K‐fold cross‐validation. The multinomial model, including position in the square and number of neighbouring pixels in the same category as the pixel modelled, reduced the misclassification rate compared with the model without spatial explanatory variables.The improved estimates of transition probabilities could be incorporated into Markov models used in simulation studies to predict future vegetation changes under different management strategies.

The Mediterranean vegetation: what if the atmospheric CO2 increased?

The atmospheric CO2 content is expected to continue to increase and probably induce warming at the global scale during the next century. The impact of such an increase will affect the composition and distribution of ecosystems on the same scale. To predict the integrated whole-ecosystem response to the CO2 increase in the Mediterranean region we used a vegetation biogeochemical model. This model (BIOME3) integrates monthly temperature and precipitation, some soil characteristics, cloudiness and CO2 concentration as inputs to simulate the vegetation in terms of biomes. First we demonstrate the ability of the model to simulate past vegetation when tested versus pollen data. Second we use the vegetation model for different climate scenarios and report results of future changes in the Mediterranean vegetation. These simulations indicate that an increase of the atmospheric CO2 to 500 ppmv, jointly with an increase of about 2 °C of the mean annual temperature, as simulated by several atmospheric general circulation models, should be accompanied by a severe reduction (more than 30%) of the present annual precipitation to change significantly the present vegetation surrounding the Mediterranean. When precipitation is maintained at its present-day level, an evergreen forest spreads in the eastern Mediterranean and a conifer forest in Turkey. In NW Africa, a woody xerophytic vegetation occupies a more extensive territory than today and replaces part of the present steppe area.

Future Climate in the Yellowstone National Park Region and Its Potential Impact on Vegetation. Clima Futuro en la Region del Parque Nacional de Yellowstone y su Potencial Impacto Sobre la Vegetacion

Biotic responses to future changes in global climate are difficult to project for a particular region because the responses involve processes that operate at many spatial scales. This difficulty is exacerbated in mountainous regions, where future vegetation changes are often portrayed as simple upward displacements of vegetation zones in response to warming. We examine the scope of future responses that may occur in a mountainous area by illustrating the potential distributions of selected tree taxa in the region of Yellowstone National Park. The output of a coarse-resolution climate model that incorporated a doubling of carbon diox- ide concentration in the atmosphere was interpolated onto a 5-minute grid of topographically adjusted cli- mate data. The output was also used as input into statistical relationships between the occurrence of individ- ual taxa and climate. The simulated vegetation changes include a combination of elevational and directional range adjustments. The range of high-elevation species decreases, and some species become regionally extir- pated. The new communities have no analogue in the present-day vegetation because they mix low-elevation montane species currently in the region with extralocal species from the northern and central Rocky Moun- tains and Pacific Northwest. The projected climate changes within the Yellowstone region and the individual- ism displayed by species in their potential range adjustments are equal or greater than the changes seen in the paleoecologic record during previous warming intervals. Although the results support conservation strate- gies that include habitat connectivity, the magnitude of the changes may exceed the ability of species to adjust their ranges. The predicted patterns call into question the adequacy of current management objectives to cope with the scope of future changes.

Fire, succession and reserve management in a New Zealand snow tussock grassland

The aftermath of fire was examined in a New Zealand grassland reserve, dominated by the tall tussock Chionochloa rigida. Deliberate fire has not previously been used in reserve management in New Zealand. Following an accidental fire in part of the reserve in autumn 1976, part of the remainder was deliberately burnt in the following spring for an experimental comparison. Vegetation changes were monitored until 1988. After both fires, the exotic grass Agrostis capillaris was abundant. Shoot frequency of Chionochloa rigida was low after fire due to the loss of the canopy, but generally increased. Twelve years after the fire, the vegetation was still different between areas of different burning history. In the unburnt area, the shrub Leptospermum scoparium was replacing Chionochloa. Species frequencies were used to classify the vegetation by Cluster Analysis. A transition matrix was calculated for the communities so derived, and a Markovian model used to predict future vegetation changes. Medium-term replacement of exotic grassland by native tussock grassland was predicted, with replacement by native Leptospermum scrub after several decades. Native forest species, some now present in small amounts, could eventually replace the Leptospermum. It is recommended that Chionochloa grassland at this altitude should be burnt every 15–40 years to maintain the community. Chionochloa rigida is expected to tolerate this regime. Burning would prevent loss of the tussock grassland by scrub invasion and consequential scrub fires. Such fires would probably result in the replacement of most native vegetation by aggressive exotic shrubs, or, if they were controlled, by exotic grassland.

Potential Magnitude of Future Vegetation Change in Eastern North America: Comparisons with the Past

Increases in atmospheric trace gas concentrations could warm the global average temperature 1.5 degrees to 4.5 degrees C by the end of the next century. Application of climate-pollen response surfaces to three climate model simulations of doubled preindustrial atmospheric CO(2) levels shows that the change in the equilibrium distribution of natural vegetation over eastern North America over the next 200 to 500 years could be larger than the overall change during the past 7,000 to 10,000 years and equivalent to the change that took place over the 1,000- to 3,000-year period of most rapid deglaciation. Some plant ranges and abundance maxima could shift as much as 500 to 1000 km during the next 200 to 500 years; such changes would have dramatic impacts on silvicultural and natural ecosystems. Although unprecedented vegetation change is likely if climate changes as predicted, forecasting the exact timing and patterns of change will be difficult.

Vegetational and ecological monitoring of boreal forests in Norway. I. Rausjømarka in Akershus county, SE Norway.

Abstract Vegetational and ecological monitoring of boreal forests in Norway was initiated in 1988, as a part of the programme “Countrywide monitoring of forest health” at Norwegian Institute of Land Invetory (NIJOS). Ten reference areas for monitoring will be established and analysed within five years; two new areas each year. Each of the monitoring areas is planned to be reanalysed every fifth year. In each monitoring area 10 macro sample plots, 50 m2 each, are selected. Within each macro sample plot 5 meso sample plots, 1 m2 each, are randomly placed and the vegetation is analysed by using frequency in subplots as measure of species abundance. Within each meso sample plot one micro sample plot (two in the first established monitoring area), 0.0625 m2 each, is analysed by the same method. In connection with each meso sample plot several environmental variables are recorded. In each ma cro sample plot several tree variables and variables describing the terrain are recorded. The variables are used for environmental interpretation as well as for monitoring, since known relations between vegetation and environmental gradients form the basis of vegetational and ecological monitoring. Any future changes in vegetation, soil and the health of trees have to be interpreted in relation to the analysis of vegetation-environment relationships in order to identify changes due to air pollution or climatic changes. The data from the first established monitoring area, Rausj0marka in Akershus county, are subjected to analysis in this paper. The most important vegetational and environmental gradients in the area are discussed, as well as the field methodology and the methods for data analysis to be used in integrated monitoring. The advantages of integrated monitoring of vegetation, soil and trees on the same sample plots are emphasized, including advantages for surveying and monitoring of species (bioindicators).

Food habits of giraffe in Tsavo National Park, Kenya

SummaryIn the context of a broader ecological investigation, food habits of giraffe were studied in Tsavo National Park (East). The only method employed was direct observation of feeding animals in the field. Each instance in which one animal fed on one individual plant was counted as one food record for this plant species; 4025 records are analysed.A total of sixty‐six plant species was found to be eaten, the great majority being trees and shrubs, with a few creepers and vines. There were marked seasonal differences in the diet of giraffe, deciduous trees, shrubs and vines being dominant in the green season, evergreen plants (partly in riverine forest) in the dry season. All the trees and larger shrubs common in the study area were eaten by giraffe, while few records for very small shrubs and none for herbs and grasses were obtained. An analysis of the available vegetation was made in part of the dry‐season habitat, and for twenty species the frequency in the habitat was compared with the frequency in the giraffe's diet, revealing selection for or against certain species. Giraffe utilized the upper vegetation layers, where available, but overall c. 50% of all browsing was below 2 m above ground, i.e. within reach of smaller browsers.Results of this study are compared with what is known on food habits of giraffe in other areas.Possible competition of giraffe with other browsers and the relationship between giraffe and their habitat are discussed. Continued survival of giraffe, and other browsers, in Tsavo National Park depends primarily on (1) adequate control of fire, and (2) the impact of future vegetation changes on the amount and variety of available browse plants.