Annual Climate Variability Research Articles

Changing Trends in Meteorological Elements and Reference Evapotranspiration in a Mega City: A Case Study in Shenzhen City, China

Shenzhen city was a farmland region before 1978, and it then developed to a mega city in China. This type of change in city can greatly affect the climatic conditions. In this study, the daily, monthly, and annual climatic variables and the reference crop evapotranspiration (ET0) for Shenzhen from 1954 to 2012 were computed using the FAO Penman-Monteith equation (PM), and these parameters were analyzed to study the temporal trends of ET0and meteorological factors. The trends and the time points of abrupt changes of ET0and meteorological factors were tested using Mann-Kendall methods. Results show that, in the past 59 years, the annual ET0first decreased from 1954 to 1978, then increased from 1979 to 1990, and now varied slightly after 1990. The mean air temperature rose gradually, and the relative humidity decreased as a whole. These trends finally resulted in an increasing trend in vapor pressure deficit (VPD). The wind speed showed a slightly decreasing trend. Both the annual total sunshine duration and net radiation showed trends of rapid decline. ET0change is sensitive to the hours of sunshine and VPD. The significant increase in ET0after 1979 was mainly due to the increased air temperature and decreased relative humidity.

Global patterns in fire leverage: the response of annual area burnt to previous fire

Prescribed fire is practiced around the world to reduce the effect of unplanned fire, but we hypothesise that its effectiveness is proportional to the mean annual area burnt by unplanned fire, which varies among biomes. Fire history mapping was obtained for six global case studies from a range of biomes: Portugal, Spain (both Mediterranean), Alberta (boreal Canada), Sequoia and Kings Canyon National Parks (montane USA), the Sandy Desert (arid Australia) and Kruger National Park (South African savanna). Leverage is the unit reduction in unplanned fire area resulting from one unit of previous fire as measured at a regional scale over a long period. We calculated leverage for each case study using statistical modelling of annual area burnt, controlling for annual climatic variation. We combined the six leverage values with those from four previously published cases to conduct a global test of our hypothesis. Leverage was high in Portugal (~0.9) and moderate in the Sandy Desert (~0.3). However, the other case studies showed no evidence of leverage: burnt area was not influenced by past fire. In all regions, climatic variation had more influence than past area burnt on annual area burnt. The global analysis revealed a positive relationship between mean area burnt and leverage but only when outlying cases were removed. In biomes with low fire activity, prescribed fire is unlikely to reduce unplanned fire area at all, while for many others, the return for effort is likely to be low. Lessons derived from one biome cannot necessarily be applied to another.

A Recent Study on the Relationship between Global Radiative Forcing and Global Annual Climatic Variability

The present paper investigates the relationship between the global radiative forcing (GRF) and global annual climatic variability. The relation between the GRF and global annual changes in the operational weather and climatic parameters is uncovered. There are several datasets which have been used to challenge this goal. The NCEP/NCAR Reanalysis dataset of several meteorological elements, such as air temperature, wind, surface pressure, outgoing long wave radiation, precipitation rate and geopotential height at level 500 hPa, etc. for the globe for the period (1948-2012), has been used. Furthermore, the GRF data for greenhouse gases through the period (1979-2010) has been used. Also, datasets of climatic indices NAO, SOI, El Nino 3.4 and SST during the period (1948-2012) have been used through this study. Time series analysis, anomaly and correlation coefficient technique methods have been used to analyze the datasets. The results reveal that there is an outstanding positive correlation coefficient (more than +0.80) between GRF and the global annual weather elements of surface air temperature, temperature and geopotential height at level 500 hPa, precipitation rate and sea surface temperature. CO2 has a significant correlation coefficient (+0.89) with the outcomes longwave radiation and sea surface temperature. There is a significant relationship between the global annual variability of weather and climatic elements and GHGs, global warming and climatic indices, NAO, SOI, El Nino 3.4 and SST.

Post-dispersal predation of Pinus pinaster Aiton seeds: key factors and effects on belowground seed bank

Seed bank dynamics constitute a pool of natural regeneration, a complex and key process for stand persistence. The present work analyzes post-dispersal predation on a Pinus pinaster Ait. (maritime pine) belowground seed bank. The study was carried out at the experimental site of Mata de Cuellar (Segovia, central Spain), where an integrated analysis of maritime pine regeneration has been underway since 2004. Seed predation was monitored every month from 2010 to 2013. A generalized linear model was fitted using “next spring seed density” as the response variable and seed rain, micro-site conditions and annual climate variability as explanatory variables. Seed rain, distance to the nearest stump, basal area and Walter’s drought index, along with percentage cover of herbaceous species, pine needle litter and shrub species, had significant positive effects. The number of neighboring trees had a significant negative effect on seed density. These results demonstrate how seed rain, summer drought and micro-site conditions are crucial to understand the effects of predation on the belowground seed bank. Though greater than null, the final seed bank might be insufficient for successful natural regeneration due to high mortality caused by difficult germination and establishment conditions.

Politics eclipses climate extremes for climate change perceptions

Whether or not actual shifts in climate influence public perceptions of climate change remains an open question, one with important implications for societal response to climate change. We use the most comprehensive public opinion survey data on climate change available for the US to examine effects of annual and seasonal climate variation. Our results show that political orientation has the most important effect in shaping public perceptions about the timing and seriousness of climate change. Objective climatic conditions do not influence Americans’ perceptions of the timing of climate change and only have a negligible effect on perceptions about the seriousness of climate change. These results suggest that further changes in climatic conditions are unlikely to produce noticeable shifts in Americans’ climate change perceptions.

The interactions between plant life form and fungal traits of arbuscular mycorrhizal fungi determine the symbiotic community.

Arbuscular mycorrhizal (AM) fungi have traditionally been considered generalist symbionts. However, an increasing number of studies are pointing out the selectivity potential of plant hosts. Plant life form, determined by plant life history traits, seems to drive the AM fungal community composition. The AM fungi also exhibit a wide diversity of functional traits known to be responsible for their distribution in natural ecosystems. However, little is known about the role of plant and fungal traits driving the resultant symbiotic assemblages. With the aim of testing the feedback relationship between plant and fungal traits on the resulting AM fungal community, we inoculated three different plant life forms, i.e. annual herbs, perennial herbs and perennial semi-woody plants, with AM fungal communities sampled in different seasons. We hypothesized that the annual climate variation will induce changes in the mean traits of the AM fungal communities present in the soil throughout the year. Furthermore, the association of plants with different life forms with AM fungi with contrasting life history traits will show certain preferences according to reciprocal traits of the plants and fungi. We found changes in the AM fungal community throughout the year, which were differentially disrupted by disturbance and altered by plant growth form and plant biomass. Both plant and fungal traits clearly contributed to the resultant AM fungal communities. The revealed process can have implications for the functioning of ecosystems since changes in dominant plant life forms or climatic variables could influence the traits of AM fungal communities in soil and hence ecosystem processes.

Reprint of “Nitrogen field balances and suction cup-measured N leaching in Danish catchments”

In Denmark suction cup-measured nitrate concentrations in soil water and N leaching have been used as a means for monitoring the impact of changes in the consumption of commercial fertilizer and improved utilisation of nitrogen in manure by agriculture. The measurements are a part of the Danish Agricultural Monitoring Programme (NOVANA) and are carried out in five small agricultural dominated catchments covering differences in climate, soil types and farming practices within the country. Statistical analyses allowing for annual variations in climate showed that nitrate concentrations in root zone water from loamy and sandy catchments decreased by, respectively, 23 and 48% during 1991–2003, after which no further decrease occurred until 2010/11. The aim of this study is to describe how the year to year variations in percolation and field balance characterise N leaching for 30 soil water stations in the period 1991–2010. A general linear model for annual observations of N leaching, N leaching=3479+0.140×percolation+0.080×surface N balance−1.737 year, explained 29% of the variation. When N leaching was calculated as a mean for each soil water station for the period 1991–2010, the field N balance explained about 44% of the variation in leaching between the 16 soil water stations located in loamy catchments. A lower proportion, 36%, was recorded for the 14 soil water stations located in sandy catchments, but the signature increased to 60% if an outlier field, having a large excess input of manure, was omitted. From these results for Danish catchments, we conclude that field N balances are able to predict the risks of leaching provided that measurements are integrated over 30 soil water stations or a relatively long monitoring period. However, the data showed that the leaching responses to the field balance are different for loamy and sandy soils and depend on farm type.

Region-specific sensitivity of anemophilous pollen deposition to temperature and precipitation.

Understanding relations between climate and pollen production is important for several societal and ecological challenges, importantly pollen forecasting for pollinosis treatment, forensic studies, global change biology, and high-resolution palaeoecological studies of past vegetation and climate fluctuations. For these purposes, we investigate the role of climate variables on annual-scale variations in pollen influx, test the regional consistency of observed patterns, and evaluate the potential to reconstruct high-frequency signals from sediment archives. A 43-year pollen-trap record from the Netherlands is used to investigate relations between annual pollen influx, climate variables (monthly and seasonal temperature and precipitation values), and the North Atlantic Oscillation climate index. Spearman rank correlation analysis shows that specifically in Alnus, Betula, Corylus, Fraxinus, Quercus and Plantago both temperature in the year prior to (T-1), as well as in the growing season (T), are highly significant factors (TApril rs between 0.30 [P<0.05[ and 0.58 [P<0.0001]; TJuli-1 rs between 0.32 [P<0.05[ and 0.56 [P<0.0001]) in the annual pollen influx of wind-pollinated plants. Total annual pollen prediction models based on multiple climate variables yield R2 between 0.38 and 0.62 (P<0.0001). The effect of precipitation is minimal. A second trapping station in the SE Netherlands, shows consistent trends and annual variability, suggesting the climate factors are regionally relevant. Summer temperature is thought to influence the formation of reproductive structures, while temperature during the flowering season influences pollen release. This study provides a first predictive model for seasonal pollen forecasting, and also aides forensic studies. Furthermore, variations in pollen accumulation rates from a sub-fossil peat deposit are comparable with the pollen trap data. This suggests that high frequency variability pollen records from natural archives reflect annual past climate variability, and can be used in palaeoecological and -climatological studies to bridge between population- and species-scale responses to climate forcing.

Leaf Area Index Variation for Crop, Pasture, and Tree in Response to Climatic Variation in the Goulburn–Broken Catchment, Australia

Abstract Previous studies have reported relationships between mean annual climatic variables and mean annual leaf area index (LAI), but the seasonal and spatial variability of this relationship for different vegetation cover types in different climate zones have rarely been explored in Australia. The authors developed simple models using remotely sensed LAI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and gridded climatic data from the Australian Water Availability Project. They were able to relate seasonal and annual LAI of three different land cover types (tree, pasture, and crop) with climatic variables for the period 2000–09 in the Goulburn–Broken catchment, Australia. Strong relationships were obtained between annual LAI of crop, pasture, and tree with annual precipitation (R2 = 0.70, 0.65, and 0.82, respectively). Monthly LAI of each land cover type also showed a strong relationship (R2 = 0.92, 0.95, and 0.95) with the difference between precipitation P and reference crop evapotranspiration (PET; P − PET) for crop, pasture, and tree. Independent model calibration and validation showed good agreement with remotely sensed MODIS LAI. The results from the application of the developed model on the future impact of climate change suggest that under all climate scenarios crop, pasture, and tree showed consistent decreases in mean annual LAI. For the future climate change scenarios considered, crop showed a decline of 7%–38%, pasture showed a decline of 5%–24%, and tree showed a decline of 2%–11% from the historical mean annual. These results can be used to assess the impacts of future climatic and land cover changes on water resources by coupling them with hydrological models.

Nitrogen field balances and suction cup-measured N leaching in Danish catchments

In Denmark suction cup-measured nitrate concentrations in soil water and N leaching has been used as a means for monitoring the impact of changes in consumption of commercial fertilizer and improved utilisation of nitrogen in manure by agriculture. The measurements are a part of the Danish Agricultural Monitoring Programme (NOVANA) and are carried out in five small agricultural dominated catchments covering differences in climate, soil types and farming practices within the country. Statistical analyses allowing for annual variations in climate showed that nitrate concentrations in root zone water from loamy and sandy catchments decreased by, respectively, 23 and 48% during 1991–2003, after which no further decrease occurred until 2010/11. The aim of this study is to describe how the year to year variations in percolation and field balance characterise N leaching for 30 soil water stations in the period 1991–2010. A general linear model for annual observations of N leaching, N leaching=3479+0.140×percolation+0.080×surface N balance−1.737 year, explained 29% of the variation. When N leaching was calculated as a mean for each soil water station for the period 1991–2010, the field N balance explained about 44% of the variation in leaching between the 16 soil water stations located in loamy catchments. A lower proportion, 36%, was recorded for the 14 soil water stations located in sandy catchments, but the signature increased to 60% if an outlier field, having a large excess input of manure, was omitted. From these results for Danish catchments, we conclude that field N balances are able to predict the risks of leaching provided that measurements are integrated over 30 soil water stations or a relatively long monitoring period. However the data showed that the leaching responses to the field balance are different for loamy and sandy soils and depend on farm type.

Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and Vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production.

Identification and dendrochronology of wood found at the Ziegler Reservoir fossil site, Colorado, USA

Over 300 wood fossils were collected from the Ziegler Reservoir fossil site near Snowmass Village in central Colorado, USA. Wood fossils range from fragments of stems and branches only a few centimeters in diameter and length to whole logs >50cm diameter and >10m length. Many of the fossils were collected from a “beach” horizon, where they appear to have been washed up on the side of the interglacial lake and buried. The wood is mainly fir (Abies sp.) or Douglas-fir (Pseudotsuga menziesii), with some spruce (Picea sp.), pine (Pinus sp.), and at least one other unidentified conifer species. Douglas-fir and species of fir, spruce, and pine are common in the area today. Dendrochronological analyses compared annual growth rings in fossil wood to similar data from modern trees. Results suggest that fossil trees from the beach horizon grew under similar environmental conditions and annual climate variability as today. Three Douglas-firs and several fir logs also appear to have been alive at the same time based on crossdating of ring widths and other ring characteristics. These trees may have died at the same time, suggesting a stand mortality event in the surrounding forest that resulted in numerous logs being buried synchronously in the beach horizon.

Climatic variations explain annual fluctuations in French Périgord black truffle wholesale markets but do not explain the decrease in black truffle production over the last 48 years

Production of the black truffle (Tuber melanosporum Vittad.) has experienced a decline in France over the last century. Different sociological factors as well as climate change have been suggested as possible explanations for this decline. The aims of this study were to assess the effects of annual climatic variations on black truffle sales by analysing reliable data. Over the past 25 years, almost 90% of French truffle sales occurred in the southeastern region of France and, despite a decrease in southwestern France, for the last 25 years, sales were stable for France as a whole. An analysis of the two main southeastern wholesale markets (Richerenches and Carpentras) revealed that the main factor explaining the huge annual variations was the cumulative hydric balance from May to August of the year n. For the first time, frost days were also identified as an important factor in Richerenches. Using the model established for the past 25 years and the climatic data for the Richerenches and Carpentras basins, the truffle sales would have been stable from 1965 to nowadays. This simulation suggested that the production decline observed since 48 years could be attributed more to the change of rural world than to the climatic changes. The stability of production or the slight increase observed during the last 25 years could reflect the input of truffle orchards recently planted.

Temperature and rainfall strongly drive temporal growth variation in Asian tropical forest trees

Climate change effects on growth rates of tropical trees may lead to alterations in carbon cycling of carbon-rich tropical forests. However, climate sensitivity of broad-leaved lowland tropical trees is poorly understood. Dendrochronology (tree-ring analysis) provides a powerful tool to study the relationship between tropical tree growth and annual climate variability. We aimed to establish climate-growth relationships for five annual-ring forming tree species, using ring-width data from 459 canopy and understory trees from a seasonal tropical forest in western Thailand. Based on 183/459 trees, chronologies with total lengths between 29 and 62 years were produced for four out of five species. Bootstrapped correlation analysis revealed that climate-growth responses were similar among these four species. Growth was significantly negatively correlated with current-year maximum and minimum temperatures, and positively correlated with dry-season precipitation levels. Negative correlations between growth and temperature may be attributed to a positive relationship between temperature and autotrophic respiration rates. The positive relationship between growth and dry-season precipitation levels likely reflects the strong water demand during leaf flush. Mixed-effect models yielded results that were consistent across species: a negative effect of current wet-season maximum temperatures on growth, but also additive positive effects of, for example, prior dry-season maximum temperatures. Our analyses showed that annual growth variability in tropical trees is determined by a combination of both temperature and precipitation variability. With rising temperature, the predominantly negative relationship between temperature and growth may imply decreasing growth rates of tropical trees as a result of global warming.

Evaluation of Linear and Non-Linear Downscaling Methods in Terms of Daily Variability and Climate Indices: Surface Temperature in Southern Ontario and Quebec, Canada

We downscaled atmospheric reanalysis data using linear regression and Bayesian neural network (BNN) ensembles to obtain daily maximum and minimum temperatures at ten weather stations in southern Quebec and Ontario, Canada. Performance of the linear and non-linear downscaling models was evaluated using four different sets of predictors, not only in terms of their ability to reproduce the magnitude of day-to-day variability (i.e., “weather,” mean absolute error between the daily values of the predictand(s) and the downscaled data) but also in terms of their ability to reproduce longer time scale variability (i.e., “climate,” indices of agreement between the predictand's observed annual climate indices and the corresponding downscaled values). The climate indices used were the 90th percentile of the daily maximum temperature, 10th percentile of the daily minimum temperature, number of frost days, heat wave duration, growing season length, and intra-annual temperature range.Our results show that the non-linear models usually outperform their linear counterparts in the magnitude of daily variability and, to a greater extent, in annual climate variability. In particular, the best model simulating weather and climate was a BNN ensemble using stepwise selection from 20 reanalysis predictors, followed by a BNN ensemble using the three leading principal components from the aforementioned predictors. Finally, we showed that, on average, the first three indices presented higher skills than the growing season length, number of frost days, and the heat wave duration.

Pacific and Atlantic sea surface temperature influences on streamflow in the Apalachicola–Chattahoochee–Flint river basin

• The coupled impacts of ENSO, AMO and PDO were greater and had a wider impact than the individual impacts. • The AMO modulates the impact of La Niña in the ACF basin. • Differences in streamflow by phase of the AMO were largest during the negative phase of the PDO. Large scale climate phenomena can provide valuable information for regional climate and streamflow in many parts of the world. Several climate phenomena may impact a given area and their value for providing information on streamflow is dependent on first establishing the local relationship. This study was conducted to establish the individual and coupled impacts of the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) on streamflow in the Apalachicola–Chattahoochee–Flint (ACF) river basin. Differences in annual and seasonal streamflow using two unimpaired streamflow datasets based on the phase(s) of ENSO, the PDO, and the AMO were evaluated using the nonparametric rank-sum test. Few statistical differences were found for the individual impacts of ENSO and the PDO on annual and seasonal streamflow; differences based on ENSO were largely confined to the southern portion of the basin. Significant differences in annual streamflow based on the AMO were largely confined to the northern half of the basin. Differences in seasonal streamflow based on the AMO were found for much of the year in the northern portion of the basin but were confined to the winter season in the southern portion. Significant differences in annual and seasonal streamflow were found between the La Niña/positive AMO phase and the El Niño/negative AMO phase, between the positive AMO/negative PDO phase and the negative AMO/negative PDO phase, and there appears to be a modulation of the impacts of La Niña by the phase of the AMO. A greater number of stations and a greater magnitude of significant differences were found for the coupled impacts than for the individual impacts of ENSO, the PDO, and the AMO; indicating the importance of the coupled impacts on regional streamflow when establishing the role of annual, decadal, and multidecadal climate variability.

Planning for climate change across the US Great Plains: concerns and insights from government decision-makers

While both international and national efforts are being made to assess climate change and mitigate effects, primary impacts will likely be regional. The US Great Plains region is home to a mosaic of unique ecosystems which are at risk from climate change. An exploratory survey of over 900 Great Plains government officials shows concerns for specific natural resources but not global climate change. Local government decision-makers are important sources of initiation for environmental policy; however, less than 20 % of jurisdictions surveyed have developed plans for adapting to or mitigating potential climate change impacts. The continental extremes of seasonal and annual climate variability of the Great Plains can mask the effects of global climate change and likely influences its’ residents lack of concern. The study findings indicate a need to reframe the discussion away from climate change skepticism, toward a focus on possible impacts within current resource management priorities such as drought, so that proactive planning can be addressed.

The effect of climate and climate change on ammonia emissions in Europe

Abstract. We present here a dynamical method for modelling temporal and geographical variations in ammonia emissions in regional-scale chemistry transport models (CTMs) and chemistry climate models (CCMs). The method is based on the meteorology in the models and gridded inventories. We use the dynamical method to investigate the spatiotemporal variability of ammonia emissions across part of Europe and study how these emissions are related to geographical and year-to-year variations in atmospheric temperature alone. For simplicity we focus on the emission from a storage facility related to a standard Danish pig stable with 1000 animals and display how emissions from this source would vary geographically throughout central and northern Europe and from year to year. In view of future climate changes, we also evaluate the potential future changes in emission by including temperature projections from an ensemble of climate models. The results point towards four overall issues. (1) Emissions can easily vary by 20% for different geographical locations within a country due to overall variations in climate. The largest uncertainties are seen for large countries such as the UK, Germany and France. (2) Annual variations in overall climate can at specific locations cause uncertainties in the range of 20%. (3) Climate change may increase emissions by 0–40% in central to northern Europe. (4) Gradients in existing emission inventories that are seen between neighbour countries (e.g. between the UK and France) can be reduced by using a dynamical methodology for calculating emissions. Acting together these four factors can cause substantial uncertainties in emission. Emissions are generally considered among the largest uncertainties in the model calculations made with CTM and CCM models. Efforts to reduce uncertainties are therefore highly relevant. It is therefore recommended that both CCMs and CTMs implement a dynamical methodology for simulating ammonia emissions in a similar way as for biogenic volatile organic compound (BVOCs) – a method that has been used for more than a decade in CTMs. Finally, the climate penalty on ammonia emissions should be taken into account at the policy level such as the NEC and IPPC directives.

Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model

Abstract. The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios – the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario – one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in shrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during December–January and March–May); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land – for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during June–August), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during December–February and March–May) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.

New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package

ANUCLIM (Xu and Hutchinson, 2011) is a unique software package used to support the spatial modelling and mapping of environmental and natural resources. It has been extensively employed for scientific research, teaching and policy making across study areas at various spatial scales. The package enables users to readily interrogate estimated values, in point and grid form, of monthly, seasonal and annual mean climate variables from supplied elevation dependent monthly mean climate surfaces and an underlying digital elevation model (DEM). The climate surfaces have been derived by the ANUSPLIN package (Hutchinson, 2004) and support interrogation at sub-kilometre scale. A key strength of the ANUCLIM package is its ability to generate bioclimatic profiles from known species locations to predict and map species distributions, in current, projected future and past climates. It can also generate a comprehensive set of climate parameters and growth indices for modelling growth of crops and plants. The package currently has four programs, MTHCLIM, BIOCLIM, BIOMAP and GROCLIM. MTHCLIM is used to obtain estimates of monthly mean climate variables from supplied climate surfaces at specified points or grids. BIOCLIM, in conjunction with BIOMAP, is a bioclimatic prediction system based on the bioclimatic envelope method devised by Nix (1986). GROCLIM is used to generate plant growth indices based on a simplified model of plant growth response to light, thermal and water regimes (Nix, 1981). The latest version of ANUCLIM, Version 6.1, incorporates substantial upgrades. In particular, the package now allows each of its four component programs to systematically incorporate the impacts of projected climate change. These projected climate changes can be provided either as simple constants, or more commonly, as grids of broad scale changes as obtained from outputs of General Circulation Models (GCMs) under various emission scenarios. For Australia, such grids can be obtained from the OzClim website of CSIRO (2007). This enables the systematic investigation of the impacts of projected climate change on socio-environmental systems.