Increased Rainfall Variability Research Articles

Climate induced changes in matrix suitability explain gene flow in a fragmented landscape – the effect of interannual rainfall variability

In fragmented landscapes, the survival of species and the maintenance of populations with healthy genetic structures will largely depend on movement/dispersal of organisms across matrix areas. In this article, we highlight that effects of fragmentation and climate change occur simultaneously and may enhance or mitigate each other. We systematically analyzed the effect of increasing interannual variation in rainfall on the genetic structure of two neighbouring small mammal subpopulations in a fragmented savanna landscape. The effect of interannual rainfall variation is analyzed for two contrasting scenarios that differ in mean annual rainfall and are both close to a dispersal threshold. Scenario 1 (low mean annual rainfall) lies slightly below this threshold and scenario 2 (high mean annual rainfall) slightly above, i.e. the amount of rainfall in an average rainfall year prevents dispersal in scenario 1, but promotes gene flow in scenario 2. We show that the temporal dynamics of the matrix was crucial for gene flow and the genetic structure of the neighbouring small mammal subpopulations. The most important result is that the increase in rainfall variability could both increase and decrease the genetic difference between the subpopulations in a complex pattern, depending on the scenario and on the amount of variation in rainfall. Finally, we discuss that the relevance of the matrix as temporarily suitable habitat may become a key aspect for biodiversity conservation. We conclude to incorporate temporal changes in matrix suitability in metapopulation theory since local extinctions, gene flow and re‐colonization are likely to be affected in fragmented landscapes with such dynamic matrix areas.

Relative effects of precipitation variability and warming on tallgrass prairie ecosystem function

Abstract. Precipitation and temperature drive many aspects of terrestrial ecosystem function. Climate change scenarios predict increasing precipitation variability and temperature, and long term experiments are required to evaluate the ecosystem consequences of interannual climate variation, increased growing season (intra-annual) rainfall variability, and warming. We present results from an experiment applying increased growing season rainfall variability and year round warming in native tallgrass prairie. During ten years of study, total growing season rainfall varied 2-fold, and we found ~50–200% interannual variability in plant growth and aboveground net primary productivity (ANPP), leaf carbon assimilation (ACO2), and soil CO2 efflux (JCO2) despite only ~40% variation in mean volumetric soil water content (0–15 cm, Θ15). Interannual variation in soil moisture was thus amplified in most measures of ecosystem response. Differences between years in Θ15 explained the greatest portion (14–52%) of the variation in these processes. Experimentally increased intra-annual season rainfall variability doubled the amplitude of intra-annual soil moisture variation and reduced Θ15 by 15%, causing most ecosystem processes to decrease 8–40% in some or all years with increased rainfall variability compared to ambient rainfall timing, suggesting reduced ecosystem rainfall use efficiency. Warming treatments increased soil temperature at 5 cm depth, particularly during spring, fall, and winter. Warming advanced canopy green up in spring, increased winter JCO2, and reduced summer JCO2 and forb ANPP, suggesting that the effects of warming differed in cooler versus warmer parts of the year. We conclude that (1) major ecosystem processes in this grassland may be substantially altered by predicted changes in interannual climate variability, intra-annual rainfall variability, and temperature, (2) interannual climate variation was a larger source of variation in ecosystem function than intra-annual rainfall variability and warming, and (3) effects of increased growing season rainfall variability and warming were small, but ecologically important. The relative effects of these climate drivers are likely to vary for different ecosystem processes and in wetter or drier ecosystems.

Integrating indigenous knowledge with conventional science: Enhancing localised climate and weather forecasts in Nessa, Mulanje, Malawi

Subsistence rain fed agriculture underpins rural livelihoods in the Sub Saharan Africa. The overdependence on rainfall suggests the need for more reliable climate and weather forecasts to guide farm level decision making. Traditionally, African farmers have used indigenous knowledge (IK) to understand weather and climate patterns and make decisions about crops and farming practices. However, increased rainfall variability in recent years associated with climate change has reduced their confidence in indigenous knowledge, hence reducing their adaptive capacity and increasing their vulnerability to climate change. To address this problem, researchers are advocating the integration of indigenous knowledge into scientific climate forecasts at the local level, where it can be used to enhance the resilience of communities vulnerable to climate change. A study was therefore conducted to establish commonly used IK indicators in weather and climate forecasting and people’s perceptions of climate change and variability in Nessa Village, Southern Malawi. We further compared the people’s perceptions on climate change and variability with empirical evidence from a nearby weather station during 1971–2003 and the major constraints that the people face to fully utilise conventional weather and climate forecasts. Our results show various forms of traditional indicators that have been used to predict weather and climate for generations. These include certain patterns and behaviour of flora and fauna as well as environmental conditions. We further established that the peoples documentation of major climatic events over the years in the area agreed with the empirical evidence from the temperature and rainfall data. Overall, rainfall in the area has reduced since 1971 with increasing temperatures. The people were however of the view that current scientific weather and climate predictions in Malawi were not that useful at village level because they do not incorporate IK.

Coping with Rainfall Variability: Dry Spell Mitigation and Implication on Landscape Water Balances in Small-scale Farming Systems in Semi-arid Niger

Rainfall variability and inherent dry spells are a reality with severe implications for smallholder agro-ecosystems in semi-arid Sahel. To increase both on- and off-farm biomass production and productivity is challenging with these climate-induced temporal and spatial variations of water. This paper tests the idea that increased vegetation through tree cover may impact water balance in a water-stressed landscape: South-east Niger. Local rainfall data, farming systems data and a landscape water-modelling tool (ArcSWAT) are used. Four production domains (conventional or fertilized combined with millet crop or millet crop plus trees) were assessed for long-term yield and landscape water balance impacts. The dry-spell analysis shows a frequency of dry spells less than 14 days is in the order of one to two dry-spell events per season in 7 years out of 10 years. The occurrence has increased between 1960 and 2004, despite a slight recovery of total annual rainfall amounts since the severe droughts of the 1980s. Results of modelled millet yields and landscape water balances suggest that options exist to enhance landscape productivity. With marginal inputs of fertilizer, millet yields increased fivefold to 2.0–2.4 t ha− 1, and water productivity improved from 6,000 to 12,000 m3 actual evapotranspiration (ETa) t− 1 grain, to an improved 1,700–3,000 m3 ETa t− 1 grain. In addition, 10% tree cover in combination with fertilized millet increased yield with marginal or no impact on water partitioning and flows in the landscape. The policy opportunities are complex and urgently needed in view of increased rainfall variability due to expected climate change. To develop sustainable pathways in these landscapes dominated by poor smallholder framers requires water managers to be more innovative and go beyond water resources alone.

토지이용이 다변화된 산림 유역의 수질에 미치는 몬순 강우의 영향

토지 이용이 다변화된 산지 유역에서 몬순 강우에 의한 환경 영향을 평가하는데 필수적인 기초 자료를 확보하기 위해 수질의 계절간 비교와 강우사상 집중샘플링의 방법을 활용하여 지표수 수질의 시공간적 변이 특성을 조사하였다. 유역 내 토지 이용을 반영하는 지표수 9개 지점을 대상으로 건 우기 수질의 계절적 차이를 비교하고, 2회의 강우사상에 대해 산림과 농경지 하천 2개 지점에서 집중 샘플링을 실시하였다. 대부분의 지점에서 건기보다 우기에 전기전도도와 <TEX>$Cl^-$</TEX> 농도는 더 낮았으나, 총 금속 농도는 우기에 훨씬 더 높았다. 이는 우기에 늘어난 유량에 의해 용존 이온은 희석되고, 토양 침식량은 증가됐기 때문인 것으로 보인다. 한편 18mm의 적은 강우 시에 산림 하천의 수질에서는 거의 변화가 보이지 않은 데 반해, 농경지 하천에서는 부유토사와 용존 물질 농도가 모두 가파른 변화를 보였으며, 452mm의 많은 강우에 대해서는 농경지 하천은 물론 산림 하천에서도 큰 수질 변화를 관찰할 수 있었다. 농경지 하천의 Pb 농도는 부유토사 농도와 높은 양의 상관관계를 보였다. 제한된 샘플링 횟수와 조사지점으로 인해 결과 해석에 신중을 기해야 하겠지만, 전체 결과는 가파른 산지 유역에 농경지가 무분별하게 확장되면 강우의 변동폭과 극단화가 심해질 경우 토양 침식과 그에 따른 환경 영향의 취약도가 증가할 것임을 시사한다. To provide baseline information essential for assessing environmental impacts of monsoon rainfalls in a mountainous watershed under mixed land use, we investigated spatiotemporal variations in water quality using a combined approach of seasonal water quality survey and intensive storm samplings. Biannual water sampling at nine locations encompassing major land use types showed generally lower electrical conductivity and Cl- concentrations during the typical wet period compared to the dry period, indicating rainfall-induced dilution of dissolved ions. Total metal concentrations, however, were significantly higher during the monsoon period, probably associated with rainfall-induced increases in suspended sediments. Intensive storm sampling during a small monsoon rainfall event (18 mm) and an extreme event (452 mm) showed rapid changes in both suspended sediments and dissolved solutes in an agricultural stream draining the Haean Basin where arable lands have expanded rapidly over the recent decades. By contrast, a nearby forest stream derived from North Korea showed little responses to the small event compared to larges changes during the extreme event. In the agricultural stream total Pb concentrations showed significant positive relationships with suspended sediments. Although limited sampling frequency and locations require a cautious interpretation, the overall results suggest that expansion of agricultural fields in steep mountainous watersheds can increase the susceptibility of soil erosion and its off-site environmental impacts under increasing rainfall variability and extremes.

Nitrogen availability in a grazed semi-arid grassland is dominated by seasonal rainfall

In semi-arid grassland ecosystems, soil biogeochemical processes are controlled by seasonal and inter-annual rainfall variation and temperature, which may override the long-term impact of grazers on N availability and N dynamics. In a three-year (2004-2006) case study of an Inner Mongolian grassland, we analysed time-integrated (ion-exchange resins) and instantaneous (soil mineral N extractions) inorganic N availability at three sites of varying grazing intensities and combined these data with information on soil water content (SWC), aboveground net primary productivity (ANPP) and plant N uptake. Additionally, the effects of rainfall and grazing on N-form availability (NO(3)(-)-N, NH(4)(+)-N) were considered. Grazing had less impact on N availability compared to seasonal and annual rainfall distribution. One of the three study years (2004) showed a grazing effect with higher resin-N availability at the ungrazed site compared to the heavily grazed site. Inorganic N availability was low in the driest year (2005) and highest in a year of average rainfall amount and favourable distribution (2004). In general, we found a positive relationship between inorganic N availability and both plant productivity and plant N uptake. Rainfall also controlled the plant available NO(3)(-)-N and NH(4)(+)-N pools; NH(4)(+)-N dominated the available inorganic N-form in times of low SWC, while the available NO(3)(-)-N increased with SWC. We observed N availability and plant productivity in a temporal synchronized pattern. Increased rainfall variability and land-use practices affecting SWC will likely alter N availability dynamics (and the relation of N-forms) and, therefore, important processes of semi-arid natural grassland carbon and N cycling.

The expected impact of climate change on nitrogen losses from wet tropical sugarcane production in the Great Barrier Reef region

The Great Barrier Reef is under threat from diffuse agricultural pollutants and potential climate change. Nitrogen loads are examined using the nitrogen surplus of simulated sugarcane production systems in the Tully–Murray catchment, comparing current management practice regimes with best management practice regimes under present day and future climate scenarios – nominally 2030 and 2070. These future scenarios are represented by increased carbon dioxide, increased temperature and increased rainfall variability. Simulation results suggest that the impact of potential climate change on diffuse agricultural nitrogen loads from sugarcane production in the Tully–Murray catchment to the Great Barrier Reef is likely to be small and negligible in comparison to the impacts of management practice change. Partial gross margin analysis suggests climate change will not noticeably alter the profitability of sugarcane production and, hence, is unlikely to be a driver of change for this land use in the Tully–Murray catchment. Improvements in water quality from sugarcane production are more likely to come from identification and adoption of best management practices.

The local impacts of climate change in the Ferlo, Western Sahel

Recent increases in the accuracy of climate models have enhanced the pos- sibilities for analyzing the impacts of climate change on society. This paper explores how the local, economic impacts of climate change can be modeled for a specific eco- region, the Western Sahel. The people in the Sahel are highly dependent on their natural resource base, and these resources are highly vulnerable to climate change, in particular to changes in rainfall. Climate models project substantial changes in rainfall in the Sahel in the coming 50 years, with most models predicting a reduction in rainfall. To connect climate change to changes in ecosystem productivity and local income, we construct an ecological-economic model that incorporates rangeland dynamics, grazing and livestock prices. The model shows that decreased rainfall in the Sahel will considerably reduce local incomes, in particular if combined with increases in rainfall variability. Adaptation to these climate change projections is possible if reductions in rainfall are followed by destocking to reach efficient grazing levels. However, while such a strategy is optimal from the perspective of society, the stocking rate is determined by individual pastoralists that face few incentives to destock.

Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: An essential first step in adapting to future climate change?

Rain-fed agriculture will remain the dominant source of staple food production and the livelihood foundation of the majority of the rural poor in sub-Saharan Africa (SSA). Greatly enhanced investment in agriculture by a broad range of stakeholders will be required if this sector is to meet the food security requirements of tomorrow's Africa. However, production uncertainty associated with between and within season rainfall variability remains a fundamental constraint to many investors who often over estimate the negative impacts of climate induced uncertainty. Climate change is likely to make matters worse with increases in rainfall variability being predicted. The ability of agricultural communities and agricultural stakeholders in SSA to cope better with the constraints and opportunities of current climate variability must first be enhanced for them to be able to adapt to climate change and the predicted future increase in climate variability. Tools and approaches are now available that allow for a better understanding, characterization and mapping of the agricultural implications of climate variability and the development of climate risk management strategies specifically tailored to stakeholders needs . Application of these tools allows the development and dissemination of targeted investment innovations that have a high probability of biophysical and economic success in the context of climate variability.

Data based mechanistic model for low flows: Implications for the effects of climate change

Analysis of climate change scenarios indicates an increased probability of high rainfalls and related flooding. Climate change may also lead to an increase in rainfall variability and the increased probability of otherwise extreme events. This forces researchers to focus on both high and low flow models. In addition, changes in soil management and an increase in water demand due to growing industrial and domestic requirements are adding to water scarcity. Sustainable water management is not possible without a better understanding of water balance in the catchment and better modelling tools for low flows. Moreover, application to climate change requires the development of a simulation model. This paper aims to present a Data Based Mechanistic approach to flow modelling, with special emphasis on low flows. The model applies a Stochastic Transfer Function approach to log-transformed flow. In this respect, the new model has certain interesting similarities with TOPMODEL which assumes an exponential relationship between soil moisture storage and flow. The paper explores these similarities, gives a physical explanation of the model structure and estimates model predictive uncertainty. A physical interpretation of the model allows the ranges of its applicability to be stated. The approach is tested on two catchments in the UK.

Dynamical effects of the statistical structure of annual rainfall on dryland vegetation

AbstractIn this study, we extend a model of daily dryland dynamics by parameterizing a modified version of a minimalistic annual model to examine how the statistical structure of annual rainfall and grazing intensity interact to influence dryland vegetation. With a Monte Carlo approach, an ensemble outcome provides a statistical description of likely dryland vegetation dynamics responding to variations in rainfall structure and grazing intensity. Results suggest that increased rainfall variability decreases the average and increases the variability of grass cover leading to more frequent degradation of the grass resource. Vegetation of drier regions is found to be more sensitive to interannual variability in rainfall. Concentrating this variability into an organized periodic mode further decreases the mean and increases the variability of grass cover. Hence, a shift toward lower, more variable, or more inter‐annually correlated annual rainfall will likely lead to a general decrease in the grass resource and increased dryland vulnerability to degradation.Higher grazing intensity or lower annual rainfall both lead to more frequent and longer duration degradation of the grass condition. We note an interesting interaction in the response of grass biomass to grazing intensity and rainfall variability, where increased rainfall variability leads to longer duration degradation for low grazing, but shorter periods of degradation for high grazing. Once grass reaches a degraded condition, we find that woody vegetation strongly suppresses recovery even if successive rainfall is high. Overall, these findings suggest that the projected increase in interannual rainfall variability will likely decrease grass cover and potentially lead to more frequent, longer lasting degradation of dryland vegetation, particularly if enhanced rainfall variability is concentrated in long period (e.g. decadal) modes.

Increased rainfall variability and reduced rainfall amount decreases soil CO2flux in a grassland ecosystem

AbstractPredicted climate changes in the US Central Plains include altered precipitation regimes with increased occurrence of growing season droughts and higher frequencies of extreme rainfall events. Changes in the amounts and timing of rainfall events will likely affect ecosystem processes, including those that control C cycling and storage. Soil carbon dioxide (CO2) flux is an important component of C cycling in terrestrial ecosystems, and is strongly influenced by climate. While many studies have assessed the influence of soil water content on soil CO2flux, few have included experimental manipulation of rainfall amounts in intact ecosystems, and we know of no studies that have explicitly addressed the influence of the timing of rainfall events. In order to determine the responses of soil CO2flux to altered rainfall timing and amounts, we manipulated rainfall inputs to plots of native tallgrass prairie (Konza Prairie, Kansas, USA) over four growing seasons (1998–2001). Specifically, we altered the amounts and/or timing of growing season rainfall in a factorial combination that included two levels of rainfall amount (100% or 70% of naturally occurring rainfall quantity) and two temporal patterns of rain events (ambient timing or a 50% increase in length of dry intervals between events). The size of individual rain events in the altered timing treatment was adjusted so that the quantity of total growing season rainfall in the ambient and altered timing treatments was the same (i.e. fewer, but larger rainfall events characterized the altered timing treatment). Seasonal mean soil CO2flux decreased by 8% under reduced rainfall amounts, by 13% under altered rainfall timing, and by 20% when both were combined (P&lt;0.01). These changes in soil CO2flux were consistent with observed changes in plant productivity, which was also reduced by both reduced rainfall quantity and altered rainfall timing. Soil CO2flux was related to both soil temperature and soil water content in regression analyses; together they explained as much as 64% of the variability in CO2flux across dates under ambient rainfall timing, but only 38–48% of the variability under altered rainfall timing, suggesting that other factors (e.g. substrate availability, plant or microbial stress) may limit CO2flux under a climate regime that includes fewer, larger rainfall events. An analysis of the temperature sensitivity of soil CO2flux indicated that temperature had a reduced effect (lower correlation and lowerQ10values) under the reduced quantity and altered timing treatments. Recognition that changes in the timing of rainfall events may be as, or more, important than changes in rainfall amount in affecting soil CO2flux and other components of the carbon cycle highlights the complex nature of ecosystem responses to climate change in North American grasslands.

Productivity responses to altered rainfall patterns in a C4-dominated grassland.

Rainfall variability is a key driver of ecosystem structure and function in grasslands worldwide. Changes in rainfall patterns predicted by global climate models for the central United States are expected to cause lower and increasingly variable soil water availability, which may impact net primary production and plant species composition in native Great Plains grasslands. We experimentally altered the timing and quantity of growing season rainfall inputs by lengthening inter-rainfall dry intervals by 50%, reducing rainfall quantities by 30%, or both, compared to the ambient rainfall regime in a native tallgrass prairie ecosystem in northeastern Kansas. Over three growing seasons, increased rainfall variability caused by altered rainfall timing with no change in total rainfall quantity led to lower and more variable soil water content (0-30 cm depth), an approximately 10% reduction in aboveground net primary productivity (ANPP), increased root to shoot ratios, and greater canopy photon flux density at 30 cm above the soil surface. Lower total ANPP primarily resulted from reduced growth, biomass and flowering of subdominant warm-season C4 grasses while productivity of the dominant C4 grass Andropogon gerardii was relatively unresponsive. In general, vegetation responses to increased soil water content variability were at least equal to those caused by imposing a 30% reduction in rainfall quantity without altering the timing of rainfall inputs. Reduced ANPP most likely resulted from direct effects of soil moisture deficits on root activity, plant water status, and photosynthesis. Altered rainfall regimes are likely to be an important element of climate change scenarios in this grassland, and the nature of interactions with other climate change elements remains a significant challenge for predicting ecosystem responses to climate change.

Comparing modern and Pleistocene ENSO-like influences in NW Argentina using nonlinear time series analysis methods

Higher variability in rainfall and river discharge could be of major importance in landslide generation in the north-western Argentine Andes. Annual layered (varved) deposits of a landslide dammed lake in the Santa Maria Basin (26 deg S, 66 deg W) with an age of 30,000 14C years provide an archive of precipitation variability during this time. The comparison of these data with present-day rainfall observations tests the hypothesis that increased rainfall variability played a major role in landslide generation. A potential cause of such variability is the El Nino/Southern Oscillation (ENSO). The causal link between ENSO and local rainfall is quantified by using a new method of nonlinear data analysis, the quantitative analysis of cross recurrence plots (CRP). This method seeks similarities in the dynamics of two different processes, such as an ocean-atmosphere oscillation and local rainfall. Our analysis reveals significant similarities in the statistics of both modern and palaeo-precipitation data. The similarities in the data suggest that an ENSO-like influence on local rainfall was present at around 30,000 14C years ago. Increased rainfall, which was inferred from a lake balance modeling in a previous study, together with ENSO-like cyclicities could help to explain the clustering of landslides at around 30,000 14C years ago.

Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland.

Ecosystem responses to increased variability in rainfall, a prediction of general circulation models, were assessed in native grassland by reducing storm frequency and increasing rainfall quantity per storm during a 4-year experiment. More extreme rainfall patterns, without concurrent changes in total rainfall quantity, increased temporal variability in soil moisture and plant species diversity. However, carbon cycling processes such as soil CO2 flux, CO2 uptake by the dominant grasses, and aboveground net primary productivity (ANPP) were reduced, and ANPP was more responsive to soil moisture variability than to mean soil water content. Our results show that projected increases in rainfall variability can rapidly alter key carbon cycling processes and plant community composition, independent of changes in total precipitation.

A stochastic approach to modeling the role of rainfall variability in drainage basin evolution

We develop a simple stochastic theory for erosion and sediment transport, based on the Poisson pulse rainfall model, in order to analyze how variability in rainfall and runoff influences drainage basin evolution. Two cases are considered: sediment transport by runoff in rills and channels and particle detachment from bedrock or cohesive soils. Analytical and numerical results show that under some circumstances, rainfall variability can have an impact equal to or greater than that of mean rainfall amount. The predicted sensitivity to rainfall variability is greatest when (1) thresholds for runoff generation and/or particle detachment are significant and/or (2) erosion and transport are strong nonlinear functions of discharge. In general, sediment transport capacity is predicted to increase with increasing rainfall variability. Depending on the degree of nonlinearity, particle detachment capacity may either increase or decrease with increasing rainfall variability. These findings underscore the critical importance of hydrogeomorphic thresholds and other sources of nonlinearity in process dynamics. The morphologic consequences of rainfall variability are illustrated by incorporating the pulse rainfall theory into a landscape simulation model. The simulation results imply that, all else being equal, catchments experiencing a shift toward greater climate variability will tend to have (1) higher erosion rates, (2) higher drainage density (because of increased runoff erosion efficiency), and ultimately (3) reduced relief. The stochastic approach provides a useful method for incorporating physically meaningful climate data within the current generation of landscape evolution models.

Late Quaternary Alluviation Along Intermittent Streams in Kakadu National Park, Northern Territory

Sedimentation along small, intermittent streams on Kapalga Research Station in Kakadu National Park may have responded to increased base levels following post-glacial flooding of the valleys of the Alligator Rivers. Alternatively, regional climate changes may have controlled sedimentation. Using thermoluminescence dating, we determined that sediments from two streams at Kapalga date from 21.5 ± 4.0 ka. On a third stream, sediments dated from 7.6 ± 1.1 ka, with younger sediments occurring downstream. We interpreted the pre-Holocene dates and the lack of evidence of upstream progradation to indicate that climate variation was more important to sedimentation than base levels. Predicted increases in rainfall variability and in the frequency of high-intensity rainfall under enhanced greenhouse conditions may cause renewed sediment mobilisation. At the outflow of one stream on to the South Alligator flood plain, we found 15 m of sandy alluvia underlying 3-5 m of estuarine muds deposited as a result of sea-level rise. These sandy alluvia dated from about 77 ka at 4 m to more than 300 ka at 19 m depth. These ages are consistent with those recorded on the Magela Creek system, 50 km to the east.

Global change and root function

AbstractGlobal change includes land‐use change, elevated CO2 concentrations, increased temperature and increased rainfall variability. All four aspects by themselves and in combination will influence the role of roots in linking below‐ and above‐ground ecosystem function via organic and inorganic resource flows. Root‐mediated ecosystem functions which may be modified by global change include below‐ground resource (water, nutrients) capture, creation and exploitation of spatial heterogeneity, buffering of temporal variations in above‐ground factors, supply and storage of C and nutrients to the below‐ground ecosystem, mobilization of nutrients and C from stored soil reserves, and gas exchange between soil and atmosphere including the emission from soil of greenhouse gases.The theory of a functional equilibrium between root and shoot allocation is used to explore predicted responses to elevated CO2 in relation to water or nutrient supply as limiting root function. The theory predicts no change in root:shoot allocation where water uptake is the limiting root function, but substantial shifts where nutrient uptake is (or becomes) the limiting function. Root turnover will not likely be influenced by elevated CO2, but by changes in regularity of water supply. A number of possible mechanisms for root‐mediated N mineralization is discussed in the light of climate change factors. Rhizovory (root consumption) may increase under global change as the balance between plant chemical defense and adapted root consuming organisms may be modified during biome shifts in response to climate change. Root‐mediated gas exchange allows oxygen to penetrate into soils and methane (CH4) to escape from wetland soils of tundra ecosystems as well as tropical rice production systems. The effect on net greenhouse gas emissions of biome shifts (fens replacing bogs) as well as of agricultural land management will depend partly on aerenchyma in roots.

Climatic change over the Lowveld of South Africa

There has been a 38% decrease in expected annual rainfall totals over the Lowveld, in the eastern part of South Africa, during the last two decades. The downward trend in mean annual rainfall is not replicated in the rest of the summer rainfall region above the escarpment. Rainfall variability over the Lowveld has been increasing since about the 1950s, although the increase in variability appears to have been slowing down in more recent years. Changes in the frequency and intensity of El Niño/Southern Oscillation extreme events are only partly responsible for the observed desiccation and increase in rainfall variability. The CSIRO 9-level general circulation model simulates, for 2 × CO2 conditions, an insignificant decrease of 10% in the annual mean and a slight increase in the inter-annual variability of rainfall over the Lowveld. Other general circulation models likewise simulate only small changes in annual mean rainfall over the region. However, the simulated increase in rainfall variability by the CSIRO 9-level model is likely to be conservative since the model, being linked to a slab ocean, is unable to represent important features of ocean-atmosphere coupling in the region. Significant changes in the frequencies of extreme drought events and of heavy rains in the Lowveld are likely to occur even with only small changes in the rainfall climatology of the region.