Matthew J. Tallis

The transcriptome of Populus in elevated CO2 reveals increased anthocyanin biosynthesis during delayed autumnal senescence

*The delay in autumnal senescence that has occurred in recent decades has been linked to rising temperatures. Here, we suggest that increasing atmospheric CO2 may partly account for delayed autumnal senescence and for the first time, through transcriptome analysis, identify gene expression changes associated with this delay. *Using a plantation of Populus x euramericana grown in elevated [CO2] (e[CO2]) with free-air CO2 enrichment (FACE) technology, we investigated the molecular and biochemical basis of this response. A Populus cDNA microarray was used to identify genes representing multiple biochemical pathways influenced by e[CO2] during senescence. Gene expression changes were confirmed through real-time quantitative PCR, and leaf biochemical assays. *Pathways for secondary metabolism and glycolysis were significantly up-regulated by e[CO2] during senescence, in particular, those related to anthocyanin biosynthesis. Expressed sequence tags (ESTs) representing the two most significantly up-regulated transcripts in e[CO2], LDOX (leucoanthocyanidin dioxgenase) and DFR (dihydroflavonol reductase), gave (e[CO2]/ambient CO(2) (a[CO2])) expression ratios of 39.6 and 19.3, respectively. *We showed that in e[CO2] there was increased autumnal leaf sugar accumulation and up-regulation of genes determining anthocyanin biosynthesis which, we propose, prolongs leaf longevity during natural autumnal senescence.

Development and evaluation of ForestGrowth-SRC a process-based model for short rotation coppice yield and spatial supply reveals poplar uses water more efficiently than willow

Woody biomass produced from short rotation coppice (SRC) poplar (Populus spp.) and willow (Salix spp.) is a bioenergy feedstock that can be grown widely across temperate landscapes and its use is likely to increase in future. Process‐based models are therefore required to predict current and future yield potential that are spatially resolved and can consider new genotypes and climates that will influence future yield. The development of a process‐based model for SRC poplar and willow, ForestGrowth‐SRC, is described and the ability of the model to predict SRC yield and water use efficiency (WUE) was evaluated. ForestGrowth‐SRC was parameterized from a process‐based model, ForestGrowth for high forest. The new model predicted annual above ground yield well for poplar (r2 = 0.91, RMSE = 1.46 ODT ha−1 yr−1) and willow (r2 = 0.85, RMSE = 1.53 ODT ha−1 yr−1), when compared with measured data from seven sites in contrasting climatic zones across the United Kingdom. Average modelled yields for poplar and willow were 10.3 and 9.0 ODT ha−1 yr−1, respectively, and interestingly, the model predicted a higher WUE for poplar than for willow: 9.5 and 5.5 g kg−1 respectively. Using regional mapped climate and soil inputs, modelled and measured yields for willow compared well (r2 = 0.58, RMSE = 1.27 ODT ha−1 yr−1), providing the first UK map of SRC yield, from a process‐based model. We suggest that the model can be used for predicting current and future SRC yields at a regional scale, highlighting important species and genotype choices with respect to water use efficiency and yield potential.

The technical potential of Great Britain to produce ligno‐cellulosic biomass for bioenergy in current and future climates

Process and empirical‐based models that describe lignocellulosic biomass yield of the perennial energy grass Miscanthus (MiscanFor©), short rotation coppice (SRC) trees and shrubs, poplar and willow (ForestGrowth‐SRC) and a number of short rotation forest trees (ESC‐CARBINE), were used to estimate the yield potential for current and future climates across Great Britain (GB). In current climates, modelled yields for all feedstock crops varied between 8.1 and 10.6 Mg dry weight (DW) ha−1 yr−1 with willow SRC and poplar SRF producing the lowest and highest yields respectively. For the medium emissions scenario (UKCP09) in 2050, mean yield for all feedstock crops varied between 7.6 and 12.7 Mg DW ha−1 yr−1 with willow SRC and poplar SRF once again the lowest and the highest recorded yields. There were clear geographical trends within GB. Miscanthus yield was higher than all others in the south‐west (13.1 Mg DW ha−1 yr−1), SRC willow and SRC poplar in the north‐west (12.1–15.8 Mg DW ha−1 yr−1) and in the midlands and south‐east, SRF poplar was the highest yielding (10.5–11.6 Mg DW ha−1 yr−1). These geographical trends changed little with climate out to 2050, with mean yield of each ‘best feedstock’ increasing from 12.7 to 14.2 Mg DW ha−1 yr−1. Out to 2050, SRC declined slightly and Miscanthus and SRF poplar increased as the ‘best feedstock’ option. Except for a few localized examples, only SRF poplar had a higher yield than SRC or Miscanthus. These data suggest that in current and future climates, lignocellulosic biomass plantation species can be selected and optimized for best yield performance in different regions of GB. This modelling framework provides a valuable starting‐point for which to test the performance of new genetic material, as this becomes available and parameterized for the models and socio‐economic scenarios that may impact on the bioenergy industry.

Estimating UK perennial energy crop supply using farm-scale models with spatially disaggregated data

To achieve the UK Governments aim of expansion in the growth of perennial energy crops requires farmers to select these crops in preference to conventional rotations. Existing studies estimating the total potential resource have either only simplistically considered the farmer decision‐making and opportunity costs, for example using an estimate of annual land rental charge; or have not considered spatial variability, for example using representative farm types. This paper attempts to apply a farm‐scale modelling approach with spatially specific data to improve understanding of potential perennial energy crop supply. The model main inputs are yield maps for the perennial energy crops, Miscanthus and willow grown as short‐rotation coppice (SRC), and regional yields for conventional crops. These are used to configure location specific farm‐scale models, which optimize for profit maximization with risk aversion. Areas that are unsuitable or unavailable for energy crops, due to environmental or social factors, are constrained from selection. The results are maps of economic supply, assuming a homogenous farm‐gate price, allowing supply cost curves for the UK market to be derived. The results show a high degree of regional variation in supply, with different patterns for each energy crop. Using estimates of yields under climate change scenarios suggests that Miscanthus supply may increase under future climates while the opposite effect is suggested for SRC willow. The results suggest that SRC willow is only likely to able to supply a small proportion of the anticipated perennial energy crop target, without increases in market prices. Miscanthus appears to have greater scope for supply, and its dominance may be amplified over time by the effects of climate change. Finally, the relationship to the demand side of the market is discussed, and work is proposed to investigate the factors impacting how the market as a whole may develop.

Validating the MERIS Terrestrial Chlorophyll Index MTCI with ground chlorophyll content data at MERIS spatial resolution

The Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI), a standard level 2 European Space Agency (ESA) product, provides information on the chlorophyll content of vegetation (amount of chlorophyll per unit area of ground). This is a combination of information on Leaf Area Index (LAI, area of leaves per unit area of ground) and the chlorophyll concentration of those leaves. The MTCI correlates strongly with chlorophyll content when using model, laboratory and field spectrometry data. However, MTCI calculated with MERIS data has only been correlated with surrogate chlorophyll content data. This is because of the logistical difficulties of determining the chlorophyll content of the area covered by a MERIS pixel (9 × 104 m2). This paper reports the first attempt to determine the relationship between MTCI and chlorophyll content using actual MERIS data and actual chlorophyll content data. During the summer of 2006 LAI and chlorophyll concentration data were collected for eight large (> 25 ha) fields around Dorchester in southern England. The fields contained six crops (beans, linseed, wheat, grass, oats and maize) at different stages of maturity and with different canopy structures, LAIs and chlorophyll concentrations. A stratified sampling method was used in which each field contained sampling units in proportion to the spatial variability of the crop. Within each unit 25 random points were sampled. This approach captured the variability of the field and reduced the potential bias introduced by the planting pattern or later agricultural treatments (e.g. pesticides or herbicides). At each random point LAI was estimated using an LAI-2000 plant canopy analyser and chlorophyll concentration was estimated using a Minolta-SPAD chlorophyll meter. In addition, for each field a calibration set of 30 contiguous SPAD measurements and associated leaf samples were collected. The relationship between MTCI and chlorophyll content was positive. The coefficient of determination (R2) was 0.62, root mean square error (RMSE) was 244 g per MERIS pixel and accuracy of estimation (in relation to the mean) was 65%. However, one field included a high proportion of seed heads, which artificially increased the measured LAI and thus chlorophyll content. Removal of this field from the dataset resulted in a stronger relationship between MTCI and chlorophyll content with an R2 of 0.8, an RMSE of 192 g per MERIS pixel and accuracy of estimation (in relation to the mean) of 71%.

The potential for bioenergy crops to contribute to meeting GB heat and electricity demands

The paper presents a model system, which consists of a partial equilibrium model and process‐based terrestrial biogeochemistry models, to determine the optimal distributions of both Miscanthus (Miscanthus × giganteus) and short rotation coppice willow (SRC) (Salix. viminalis L. x S. viminalis var Joruun) in Great Britain (GB), as well as their potential contribution to meet heat and electricity demand in GB. Results show that the potential contribution of Miscanthus and SRC to heat and electricity demand is significant. Without considering farm‐scale economic constraints, Miscanthus and SRC could generate, in an economically competitive way compared with other energy generation costs, 224 800 GWh yr−1 heat and 112 500 GWh yr−1 electricity, with 8 Mha of available land under Miscanthus and SRC, accounting for 66% of total heat demand and 62% of total electricity demand respectively. Given the pattern of heat and electricity demand, and the relative yields of Miscanthus and SRC in different parts of GB, Miscanthus is mainly favoured in the Midlands and areas in the South of GB, whereas SRC is favoured in Scotland, the Midlands and areas in the South of GB.

High-resolution spatial modelling of greenhouse gas emissions from land-use change to energy crops in the United Kingdom

We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land‐use transitions from existing land use, rotational cropland, permanent grassland or woodland, to six bioenergy crops; three ‘first‐generation’ energy crops: oilseed rape, wheat and sugar beet, and three ‘second‐generation’ energy crops: Miscanthus, short rotation coppice willow (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest beneficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio‐physical factors (e.g. the energy density of the crop) and socio‐economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation.

Direct effects of elevated carbon dioxide on forest tree productivity

This paper provides an introduction to the book on forests and climatic change. A brief overview is given on the different sections included as well as the concepts covered in each: climate change, forestry and the science-policy interface; forestry options for contributing to climate change mitigation; adaptation regarding the impacts of climate change on forests; and policies within national and international frameworks

The impacts of green infrastructure on air quality and temperature

The temperatures and the amounts of air pollution experienced in urban environments are typically larger than in surrounding rural environments. Urban air pollution is associated with increased cardiovascular and respiratory diseases, some cancers, and increased temperatures with discomfort and in the vulnerable and elderly increased mortality. Managing urban air quality by reducing pollution exposure and maintaining equitable urban temperatures are priorities towards enhancing the health and well-being of the urban population. This chapter explores how, and to what extent, urban vegetation can influence the amounts of air pollutants and regulate urban air temperature. Urban vegetation generally has a positive influence, and under some circumstances, the capacity to make substantial gains in urban air quality and temperature regulation. Different species and forms of urban vegetation had different influences, as did the location of planting, but under some circumstances vegetation could negatively influence air-pollution and temperature. Approaches to maximise the benefits from planting urban vegetation are presented and it is acknowledged that more research is needed in order to optimise these benefits.