Regional climate change mitigation with crops: context and assessment

J. S. Singarayer, T. Davies-Barnard
Published 6 August 2012.DOI: 10.1098/rsta.2012.0010

Abstract

The intention of this review is to place crop albedo biogeoengineering in the wider picture of climate manipulation. Crop biogeoengineering is considered within the context of the long-term modification of the land surface for agriculture over several thousand years. Biogeoengineering is also critiqued in relation to other geoengineering schemes in terms of mitigation power and adherence to social principles for geoengineering. Although its impact is small and regional, crop biogeoengineering could be a useful and inexpensive component of an ensemble of geoengineering schemes to provide temperature mitigation. The method should not detrimentally affect food security and there may even be positive impacts on crop productivity, although more laboratory and field research is required in this area to understand the underlying mechanisms.

1. Introduction

While there is consensus that dangerous climate change should be avoided, it seems increasingly unlikely that international agreement will be obtained soon enough to sufficiently reduce greenhouse gas emissions to achieve this. This realization has initiated the consideration of additional or alternative methods of mitigating climate change in the short term. Geoengineering (the intentional manipulation of the climate to counteract global warming) is becoming seriously considered for its potential to reduce the impact of anthropogenic climate change [1,2]. Proposed geoengineering schemes fall into two categories: solar radiation management (SRM), in which the proportion of incoming solar radiation which is reflected by the atmosphere or land surface is increased, and carbon dioxide reduction (CDR), in which a fraction of the carbon dioxide (CO2) in the atmosphere is removed in order to manage the outgoing longwave radiation balance.

Crop albedo ‘biogeoengineering’, outlined in this study, falls into the category of SRM geoengineering. The suggestion is that the reflectance of incoming solar radiation by crops could be increased, thereby providing regional cooling over areas where cropland is extensive [3]. This could be achieved by modifying crop leaf surface waxes, trichomes (outgrowths such as hairs), leaf variegation, modifying chlorophyll levels or altering plant morphology to maximize reflectivity, through selective breeding or appropriate choice of existing cultivar [3], or using genetic modification (see also Freeman et al. [4] for an example where transgenics could be employed in a CDR scheme). The development of this idea firstly requires assessment of the likely level of mitigation achievable and whether it would be of sufficient magnitude to warrant implementation, and the investigation of any potentially detrimental impacts. Secondly, there is a requirement to characterize the current variation in albedo of existing crop varieties and the potential for breeding traits that could further increase albedo without reducing productivity. The initial studies to assess the potential of crop biogeoengineering have used coupled climate and vegetation models to quantify the degree of climate remediation achievable given estimated plausible increases in crop canopy albedo derived from related agricultural literature [3,5]. Other geoengineering proposals have been investigated within similar climate modelling frameworks [6–8]. Laboratory and field-scale work is currently in progress to systematically characterize the reflectance and transmittance of existing crop varieties.

In this communication, we review the idea of crop biogeoengineering with the aim of putting it into a wider context of historical land-use change (§2) and other geoengineering proposals (§5). We look at the level of mitigation biogeoengineering could provide, as estimated by previous climate model studies, and possible impacts on crop productivity (§4).

2. Historical land-use context

One of the largest changes to human society in prehistory which increased our impact on the environment was the Neolithic (agricultural) revolution approximately 10 000 years ago. The movement from hunter–gatherer to sedentary farming societies resulted in surplus food production and enabled higher population densities. Large-scale conversion of natural environments to land suitable for cultivation (mainly through deforestation and irrigation) occurred gradually over thousands of years. It has been estimated that cropland occupied roughly 1 per cent of global ice-free land area by AD 1000 [9,10], although the percentage was likely to be much higher in Europe by this time [11,12]. In the last few centuries, the rate of land conversion rapidly increased so that by AD 2000 global cropland occupied roughly 11 per cent of the land surface, and pastureland 24 per cent (figure 1).

Figure 1.
Figure 1.

Prehistoric and historical changes in agricultural land use. Cropland (blue line), pastureland (green line) and total (red line) (crop+pasture) calculated as a percentage of the global total ice-free area. Main plot data from BC 10 000 to AD 2005; inset from AD 1500 to AD 2005. Adapted from [9,10].

These historic and prehistoric changes in land use have had an impact on ground albedo and increased atmospheric carbon dioxide levels. For example, land-use change in recent decades (1990–2005) has, by one estimate, resulted in a net source of carbon dioxide of 1.5±0.7 Pg C yr−1 [13], contributing to global warming. However, grass and cropland has a higher albedo than forests and woodland [14]. The surface radiative forcing resulting from deforestation has been estimated to be −0.2±0.2 W m−2 [15], since forests and natural vegetation have typically low albedos in comparison with extensive grass and cropland. Experiments with climate models suggest that conversion of natural vegetation to agricultural land in the industrial era (since 1700) resulted in a cooling of 0.09–0.22°C [16], and has moderated greenhouse-gas forced temperature increases over the last century by about 0.1°C. Land-use change additionally modifies surface roughness, soil moisture and evapotranspiration; all of which influence local and global climates.

In the coming decade, it has been predicted that further land-use change will increase cropland area extent by 0.25 per cent per year (calculated using figures from the Food and Agriculture Organization of the United Nations [17]). While crop yields have also increased, these have only just managed to keep up with population growth [18] and wheat yields in many countries have plateaued since 2000 [19]. Food production systems are becoming increasingly vulnerable, and are likely to become further stressed owing to future climate change [20]. In considering the challenges of climate change and global food supply in future decades, it may be the case that through the careful choice of crop varieties one could mitigate a proportion of global warming and improve the security of food production. These two aspects of crop biogeoengineering have been examined using global climate models [3,5], the results of which are outlined in §4.

A final note related to historical context is that while crop albedo biogeoengineering is a relatively new idea, the modification of crops has occurred unintentionally and intentionally since the Neolithic origin of agriculture, so as to maximize food production. There is archaeological and genetic evidence of early selective breeding to optimize for various properties, such as to increase grain/fruit/vegetable size and/or improve taste (e.g. maize [21], brassicas [22]), indehiscence to aid harvesting [23], reduction of toxicity [24], or more recently to increase disease and pest resistance [25,26]. This has led to plants that are already far from ‘natural’. However, to date, the optimization of crops has not directly been concerned with climate remediation. Biogeoengineering would therefore be one further facet for consideration in the breeding and selection of crop cultivars, and may be thought of as an enhancement of a pre-existing practice.

3. Basis of crop biogeoengineering

The simple premise behind crop biogeoengineering is that different cultivars of the same species of crop can display very different albedos, and therefore the large-scale replacement of cultivars with ones that are more reflective could provide a significant seasonal cooling [3]. Crop canopy albedo is the sum of reflection, absorption, and transmission of leaves and stems. Within the leaves strong absorption takes place in the photosynthetically active region between 400 and 700 nm ([27]; figure 2b), which is also the portion of the incoming solar spectrum with the highest irradiance ([28]; figure 2a). In the near infrared (NIR) reflection is high and absorption is limited to cellulose, lignin and other structural compounds. There are strong absorption peaks by water in leaves in the middle infrared which can clearly be seen from the reflectance spectrum. The calculation of albedo is usually integrated from ultraviolet (UV) to infrared wavelengths of the spectrum [29,30].

Figure 2.
Figure 2.

(a) Incoming solar spectrum at the top of the atmosphere (light orange) and the surface (dark orange) [28], and (b) typical spectrally resolved leaf reflectance (adapted from [27]).

There are several plant characteristics that can vary to produce different albedos between crop varieties, mentioned in §1. Here, we discuss three in more detail. Firstly, canopy morphology (the arrangement and size of the leaves and stems) has been found to influence albedo and is particularly important for maize, previously measured to vary between 0.16 and 0.24 [31]. Secondly, leaf trichomes, such as hairs or papillae, affect reflectivity. Pubescence (i.e. hairiness) has been shown to increase the reflection of longer, photosynthetically active wavelengths [32]. Thirdly, crop albedo may be modified through leaf glaucousness or waxiness. Studies demonstrate that glaucous leaves are more reflective than non-glaucous ones [32,33]. Glaucousness is found in a number of plants and may confer different advantages for different environments, not all of which relate to reflectance properties. For example, as well as reducing UV-B damage, glaucousness has been suggested as reducing leaf temperature, increasing precipitation throughfall rates to improve water availability in water-stressed environments, or to improve frost resistance in colder environments [29].

The thickness, chemical composition and three-dimensional crystal structure of surface waxes are known to control reflectivity [34]. Stem and leaf wax loads have been found to vary by as much as a factor of 2 in certain crops [35,36], producing significant variation in reflectances at UV, visible and NIR wavelengths [29,36]. At the leaf level variation in reflectance has been found to be as large 0.16 (in varieties of sorghum wheat [34]), although at canopy level this decreases. Given the large difference in albedo-controlling characteristics of crop varieties, it is plausible that the replacement of current crop varieties with high-albedo ones would be feasible in the near term and achieved at relatively little expense. In particular, understanding of cuticular wax is relatively high and may make possible further increases in reflectivity by selective breeding or genetic modification of leaf wax properties [37].

Crop albedo is not dependent solely on the leaf properties, but also on latitude, season, harvest timing, orientation of crop rows and underlying soil characteristics, for example. However, the existing literature hints that further investigation of biogeoengineering is warranted. It is important to note that biogeoengineering does not involve the suggestion of replacing one crop with another (e.g. replacing wheat with cucumbers). The disruption to global food production would be too great [3], even though the albedo modification would be larger than by replacing cultivars of the same crop species. Therefore, the potential for increasing albedo is relatively modest (approx. 0.04–0.1) in comparison with those geoengineering schemes that change surface type (e.g. deserts replaced by white plastic [38]). However, the coverage of cropland is so extensive that the impacts on temperature would affect a large area. The most extensive agricultural land is in Europe, South Asia and North America (figure 3) and these regions are where the largest impacts of crop biogeoengineering would be seen [3,5].

Figure 3.
Figure 3.

(a) Fractional grid cell area prescribed as cropland in the Hadley Centre coupled ocean–atmosphere–vegetation model, HadCM3 [3]; (b) level of cooling in the global annual mean surface air temperature (SAT) when various levels of cropland albedo increase are prescribed [3]; (c) mean winter (December, January, February; DJF) SAT anomalies from a 20% increase in cropland albedo in HadCM3 [5]; (d) same as (c) but for mean summer (June, July, August; JJA) SAT anomalies in HadCM3 [5]; (e) same as (c) but using the atmosphere–vegetation model, HadAM3; (f) same as (d) but using HadAM3.

4. Assessment with climate models

Evaluating the potential of biogeoengineering requires complementary laboratory and field research to quantify crop albedo variability and potential for selective breeding, as well as computational efforts to simulate the impact of local- to global-scale implementation. Prior to the undertaking of empirical evaluation, general circulation models (GCMs) have proved a useful tool to assess the impacts of an idealized global application of biogeoengineering [3,5]. The benefit of using GCMs for this sort of research is that many complicating factors, such as the heterogeneity of cropland coverage (figure 3a), cloud cover feedbacks and latitudinal/seasonal variation in insolation, are accounted for within the model structure. This section reviews the simulated impacts of biogeoengineering on temperature, the hydrological cycle and vegetation productivity derived from GCM studies.

(a) Impacts on energy balance and temperature

Emissions of carbon dioxide have increased global radiative forcing (a measure of the impact a factor has in altering the balance of incoming and outgoing energy in the Earth–atmosphere system). The net effect of human activities since the industrial revolution (AD 1750), including increased carbon dioxide emissions and surface albedo modification due to changes in land use, has been a net radiative forcing increase of +1.66 (+0.6 to +2.4) W m−2 [15]. Several studies have estimated the reduction in radiative forcing due to various surface albedo increases. For example, Dong & Sutton [39] calculated a 0.59 W m−2 radiative forcing decrease by increasing grassland albedo by 25 per cent. Another study combined increases in grassland, cropland and urban albedos to estimate that a total reduction of 1 W m−2 may be possible [2]. By comparison, the change in net radiation flux at the top of the atmosphere given a 20 per cent (0.04) increase in cropland albedo calculated with a coupled ocean–atmosphere–vegetation GCM [5] is of a similar magnitude, 0.2–0.3 W m−2.

When various degrees of crop albedo increase have been prescribed in a GCM, from a conservative 10 per cent (0.02) to an unrealistic 100 per cent increase (0.2), the relationship between cropland albedo and global cooling is linear (figure 3b) over this range [3]. A 100 per cent increase would produce sufficient cooling (approx. 0.5 K) to roughly offset global warming during the twentieth century. A more realistic 20 per cent (0.04) increase in albedo produces only a small decrease in the global annual mean temperature (approx. 0.1 K). However, previous studies have found that the seasonal and regional mitigation has greater potential than considering the global average [3,5]. The impact would be largest over Northern Hemisphere mid-latitudes, where cropland is most widespread (figure 3a), during Boreal summer (figure 3d). The average summertime cooling over Europe due to a 20 per cent increase in crop albedo has been estimated to be 1–1.6 K [3,5]. One would also expect a concurrent reduction in frequency and severity of extreme high temperature events in summer.

Such levels of mitigation would not occur uniformly over all regions with high cropland densities. In South Asia (India and China), simulations produced no significant decrease in temperature during summer. In monsoon systems, feedbacks in the hydrological cycle, especially cloud cover, may negate the impacts of increasing the surface albedo (explained further in §4b). In these regions the majority of the cooling could be experienced in the winter months instead (figure 3c). In the Southern Hemisphere, the lack of large swathes of dedicated cropland would result in minimum temperature mitigation via this method. Here, implementation of similar albedo increases to the more extensive pasture and grasslands may be more effective [40].

One potentially difficult aspect to assessing the efficacy of such schemes, if implemented, would be obtaining evidence of statically significant changes at a regional level, when taking into consideration natural climate variability. The cooling described above is small and seasonal in comparison with variability caused by other natural and anthropogenic factors. Within a modelling framework, the effect of natural variability can be minimized by taking long averages over several decades, which would not be practical following real- world application. There are also strongly coupled ocean–atmosphere–sea-ice processes [39] in the North Atlantic region by which anomalies can be teleconnected and amplified, via storm tracks, the North Atlantic Oscillation and meridional planetary wave perturbations. In addition, the sensitivity of the climate system to biogeoengineering may depend on the background climate state. One modelling study found the sensitivity to biogeoengineering to be greater at doubled modern CO2 levels than modern or quadrupled levels [5]. Meridional teleconnections from mid-latitudes up to the Arctic (which can be seen in the temperature anomalies of atmosphere-only simulations in figure 3e) influence sea-ice extent to a greater extent in the double CO2 state, causing significant cooling over the Arctic in addition to that directly over cropland areas (figure 3c).

(b) Impacts on the hydrological cycle and vegetation

There are strong feedbacks between temperature and the hydrological cycle. Temperature anomalies can induce cloud cover changes, which then exert a secondary impact on surface temperatures through longwave and shortwave radiative flux changes or through latent heat flux changes. In previous modelling studies where surface albedo has been increased this has led to either overall heating [41] or negligible cooling [42]. The non-uniform nature of biogeoengineering may also lead to changes in atmospheric circulation and consequently to the hydrological cycle. One region that experiences these secondary effects in the modelling studies of biogeoengineering performed so far is South Asia [5]. As outlined in §4a, there is no significant temperature reduction in summer from specifying higher crop albedos in these areas. This is because in late spring land heating is reduced owing to higher surface albedos, particularly over India. As a result there are large reductions in convective cloud cover over land in spring and summer. The subsequent increase in downward shortwave radiation at the surface (up to 5 W m−2 higher) counteracts the initial cooling influence of the biogeoengineering. Following the decrease in convective cloud cover, there is also substantially decreased summer monsoon precipitation over India and China (figure 4b). Similar decreases in summer precipitation may occur over the East Sahel region, which does not have high land fractions dedicated to cropland, but sufficient to have some impact together with the monsoonal influence due to the changes over India.

Figure 4.
Figure 4.

(a) Mean winter (DJF) precipitation anomalies from a 20% increase in cropland albedo in HadCM3; (b) same as (a) but for summer (JJA) [5]; (c) same as (a) but for soil moisture and (d) same as (b) but for soil moisture.

Biogeoengineering in Western Europe, on the other hand, may produce both cooler temperatures and increases in precipitation [5] due to intensification of summer storm track activity. In this region, higher levels of precipitation drive higher evapotranspiration rates. However, the surface water balance becomes more positive overall, resulting in higher soil moisture levels throughout the year (figure 4c,d). Models suggest that the increased availability of water in Europe may produce higher rates of net primary productivity of crops [5]. By contrast, in tropical regions of South Asia and the Eastern Sahel decreases in annual soil moisture and decline in productivity may result. While the impacts for mid-latitude Europe present several potential benefits in terms of temperature mitigation and crop production, the benefits for those regions surrounding the tropical Indian Ocean seem to be negligible. These modelling studies demonstrate the need to consider not just the impact of such geoengineering proposals on global mean temperature, but also the disparate regional impacts on the hydrological cycle and the implications for such issues as food security.

5. Biogeoengineering in a geoengineering context

The comparison of different geoengineering proposals has generally been achieved by considering the costs, side-effects, risks and cooling potential [1,2,43]. To facilitate this, schemes tend to be grouped, by the process by which they influence the Earth's energy balance, into either CDR (impacts the longwave radiation balance) or SRM (impacts the shortwave radiation balance) schemes. Crop biogeoengineering falls into the latter category of SRM. Biogeoengineering is generally considered a low-risk but low-impact option compared with other geoengineering options [1]. The maximum radiative forcing effect of crop albedo bioengineering is around −0.2–0.3 W m−2 (§4a). This is approximately 10 per cent of the potential of a SRM space-based reflector [2]. However, biogeoengineering is comparable to afforestation in magnitude (−0.49 W m−2) and has a greater potential than urban albedo modification schemes (−0.05 W m−2) and iron fertilization (−0.11 W m−2) [2]. Clearly crop albedo climate engineering would need to be used in conjunction with other techniques, including conventional mitigation, in order to produce meaningful global cooling.

The possibility of detrimental displaced climate effects (some described in §4) is uncertain and will require further investigation [5] but similar or greater unfavourable climate impacts may be caused by other SRM methods [6]. Equivalent unintended environmental effects may also result from CDR schemes such as ocean fertilization or biomass sequestration. Indeed, climate modelling suggests that food production in some regions may actually be enhanced by crop albedo bioengineering compared with land-based CDR, such as biofuel production. Although biofuels have been promoted for their large potential saving of fossil fuel [44] their impact on food security could be severe if their production was favoured over food production. Similarly, significant afforestation could encroach on arable land, creating a conflict of interests. High-albedo crop plants have the advantage for food security that they need only be a different variety of the same food crop to create a significant localized cooling.

The risk to natural ecosystems by crop albedo climate engineering is also minimal. Cropland has already been altered by humans (see §2), and substitution of one variety of wheat for another is unlikely to significantly affect the land. By comparison, the impact to the ecosystem of desert albedo schemes is likely to be high [1]. Other proposed schemes involve the intentional modification of natural ecosystems, such as geoengineering peatlands to increase their carbon sequestration potential discussed in this Discussion Meeting Issue [5]. Because crops are not perceived as ‘wild’ or ‘natural’, the public may be initially more willing to use cropland to counteract climate change than, for instance, peatland or desert areas. If a combination of geoengineering approaches were used, there may also be some potential for synergies. High-albedo crops could for instance be used in conjunction with methods to increase soil carbon sequestration on degraded farmland. Soil carbon sequestration could potentially sequester up to 1 tonne C ha−1 yr−1 and increase yield by up to 20–40 kg ha−1 for wheat [45]. If high crop albedo and soil carbon sequestration techniques were employed together, they could form an effective short-term combined CDR–SRM technique.

Combining geoengineering methods could, conversely, create land-use conflicts. The Royal Society report on geoengineering [1] suggests that low-grade agricultural land could be used for afforestation. However, afforestation of low-grade agricultural land may also affect surface albedo [46]. Given that crop albedo biogeoengineering and afforestation have similar radiative forcing when considering their intended effects, the choice of whether to use low-grade agricultural land for afforestation or crop albedo biogeoengineering may be a question of priorities. High crop albedo would provide a short-term store of carbon and an immediate mitigation of temperature rises. Afforestation of cropland would probably decrease the albedo in the short term, which may increase local temperatures [46], but would store more carbon in the medium term (or long term if subsequently used as biochar). It is important to communicate that this is not an advocation of turning forest into cropland, as this would probably produce a net increase in radiative forcing owing to the release of wood and soil carbon [45].

As well as looking at the scientific aspects of geoengineering proposals, research has begun to examine the social aspects of geoengineering. The Oxford [47] and Asilomar [48] principles are recently formed recommendations for ways of working to create geoengineering solutions, which are transparent and equitable. They are concerned with: regulation and governance; open and accessible research; public consultation; and robust assessment of impacts. These principles seem to be aimed towards managing large-scale global geoengineering and it is less certain to what extent they are applicable to regional climate engineering proposals. For example, adherence to the principles of responsible governance and public consultation would be more easily achievable for biogeoengineering than for space-based reflectors, owing to the local implementation, regional impacts and pre-existing agricultural regulation, compared with the international cooperation and consultation required in order to put solar reflectors in space and the global impacts (table 1). Crop biogeoengineering and afforestation have many similarities in their adherence to the Oxford/Asilomar principles.

View this table:
Table 1.

Principles derived from Oxford [47] and Asilomar [48] principles and the extent to which crop albedo, space-based reflectors and afforestation meet these criteria.

There are significant disparities for geoengineering schemes in their potential for adhering to these derived principles for ethics and governance. The perception of individual schemes may also influence future research, and for this reason crop albedo biogeoengineering may not benefit from its categorization as an SRM technique. Geoengineering proposals grouped together are often very different in scale, effect and risk. SRM geoengineering is frequently discussed as synonymous with space-based reflectors or stratospheric aerosols [1]. Other less radical SRM proposals, such as biogeoengineering, are at risk of being discounted along with space-based SRM, or disregarded altogether because of this association.

6. Discussion

Biogeoengineering research is in its infancy. Based on modelling studies, it appears to present a low-cost and low-risk method for providing regional climate change mitigation. Its application would probably be more easily achieved than most other geoengineering schemes since cropland is extensive and is an already anthropogenically altered habitat. Empirical research is now required to characterize varieties of various crops for their biogeoengineering potential. This is presently being undertaken for wheat, which is currently the most widely grown crop globally and therefore a good prospect for significant impact. Importantly, the potential indirect cost in loss of yield from lesser disease or drought resistance has been raised as a question [1,37] and needs to be examined simultaneously to the radiative properties of crops. Ideally, high-albedo crops should equal or better the operational yield of current versions. The potential to achieve this has been questioned [49], if reflectivity in the photosynthetically active region is increased as a result.

The effects on yield may well be dependent on the method by which crop albedo is increased (using canopy morphology, leaf trichomes, or glaucousness; see §3). Taking glaucousness as an example, it has been observed that wheat strains with higher levels of surface waxiness were higher yielding under water stress [36,50]. Similar results have been found for varieties of barley under various conditions [33]. This is often attributed to reduced leaf heating and consequent reduction in evapotranspiration [51], but there is currently incomplete understanding of how glaucousness increases yield and drought resistance [50]. Studies also suggest a range of responses in disease and pest resistance to glaucousness. Glaucous leaf surfaces have been recorded as more susceptible to aphids [52] and powdery mildew [53]. On the other hand, super-hydrophobic leaf wax surfaces can ‘self-clean’ pathogens from their surfaces as a defence mechanism [54]. Since glaucousness can increase the leaf hydrophobicity and create very hydrophobic surfaces, the net disease resistance effect could be positive. Clearly, more research is needed to clarify the drought and disease resistance of glaucous crops. However, it seems likely that albedo could be increased without necessarily affecting crop performance. One further point is that, as an SRM method that does not influence atmospheric CO2 concentrations, biogeoengineering could potentially benefit from the CO2 fertilization effect to increase crop productivitiy as CO2 levels rise in the near future. However, we would not advocate only using SRM methods on this basis, as this would ignore other important detrimental impacts of increasing CO2 emissions such as ocean acidification.

Predicted increases in inter-annual variation can result in a grain yield decrease equal to a 3 K increase in the mean temperature [55]. Lower summertime temperatures provided by increased crop albedo could reduce the damaging effect of increased inter-annual variation, making the provision of food security easier. Further, if the increased crop albedo resulted in increased summertime precipitation, as found for Europe ([5], §4b), there could be an additional benefit. The central estimate of probabalistic model changes in UK summer precipitation by the 2080s under a medium emissions scenario is for overall drier conditions: –40 per cent in southern England to virtually zero change in northern Scotland [56]. The UK Environment Agency expects increasing water pressure through increased demand and a drop in UK precipitation because of climate change [57]. A summertime increase in precipitation owing to increased crop albedo could help reduce crop water stress and water shortages for some regions (but not for all regions of high-density cropland; see §4b).

There is certainly promising scope for further investigation of crop biogeoengineering. High-albedo crops could achieve significant seasonal climate mitigation, although it is probable that implementation would not produce equal benefits for all cropland regions. The logical next steps for developing this idea are laboratory and field-scale evaluations of crop cultivar characteristics. This should not just involve radiative transfer qualities, but also the impact on water use and disease resistance, with an emphasis on maintaining or enhancing crop yields. At the field scale it will be important to assess the additional influence of farming practices such as crop rotation, row orientation, irrigation and spraying of pesticides on radiative and other characteristics. Implementation of biogeoengineering could take place at a national scale, and therefore, in conjunction with experimental laboratory and field studies, further regional-scale climate model studies with more detailed agricultural parametrizations (e.g. harvesting) will also be essential to examine climate impacts that may cross national boundaries via climate teleconnections. It is also crucial that ample consultation with the public, farming community and policy-makers takes place to assess acceptability of different ways by which biogeoengineering could be achieved.

Acknowledgements

We thank Andy Ridgwell for his patience in dealing with the completion of this paper, and for inviting J.S.S. to speak at the Royal Society meeting ‘Geoengineering: taking control of our planet's climate?’. We thank Paul Valdes for use of the computer cluster to perform the climate model simulations. We thank DEFRA for the funding which facilitated this work.

Footnotes

References

  1. ↵
    Royal Society 2009 Geoengineering the climate: science, governance and uncertainty. RS Policy document 10/09. London, UK: Royal Society.
  2. ↵
    1. Lenton T. M.,
    2. Vaughan N. E.
    2009 The radiative forcing potential of different climate geoengineering options. Atmos. Chem. Phys. Discuss. 9, 2559–2608. doi:10.5194/acpd-9-2559-2009 (doi:10.5194/acpd-9-2559-2009)
    OpenUrlCrossRef
  3. ↵
    1. Ridgwell A.,
    2. Singarayer J. S.,
    3. Hetherington A. M.,
    4. Valdes P. J.
    2009 Tackling regional climate change by leaf albedo bio-geoengineering. Curr. Biol. 19, 146–150. doi:10.1016/j.cub.2008.12.025 (doi:10.1016/j.cub.2008.12.025)
    OpenUrlCrossRefPubMed
  4. ↵
    1. Freeman C.,
    2. Fenner N.,
    3. Shirsat A. H.
    2012 Peatland geoengineering: an alternative approach to terrestrial carbon sequestration. Phil. Trans. R. Soc. A 370, 4404–4421. doi:10.1098/rsta.2012.0105 (doi:10.1098/rsta.2012.0105)
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Singarayer J. S.,
    2. Ridgwell A. H.,
    3. Irvine P.
    2009 Assessing the benefits of crop albedo bio-geoengineering. Environ. Res. Lett. 4, 045110. doi:10.1088/1748-9326/4/4/045110 (doi:10.1088/1748-9326/4/4/045110)
    OpenUrlCrossRef
  6. ↵
    1. Lunt D. J.,
    2. Ridgwell A.,
    3. Valdes P. J.,
    4. Seale A.
    2008 ‘Sunshade world’: a fully coupled GCM evaluation of the climatic impacts of geoengineering. Geophys. Res. Lett. 35, L12710. doi:10.1029/2008GL033674 (doi:10.1029/2008GL033674)
    OpenUrlCrossRef
    1. Irvine P. J.,
    2. Ridgwell A. J.,
    3. Lunt D. J.
    2010 Assessing the regional disparities in geoengineering impacts. Geophys. Res. Lett. 37, L18702. doi:10.1029/2010GL044447 (doi:10.1029/2010GL044447)
    OpenUrlCrossRef
  8. ↵
    1. Vaughan N. E.,
    2. Lenton T. M.,
    3. Shepherd J. G.
    2009 Climate change mitigation: trade-offs between delay and strength of action required. Clim. Change 96, 29–43. doi:10.1007/s10584-009-9573-7 (doi:10.1007/s10584-009-9573-7)
    OpenUrlCrossRef
  9. ↵
    1. Klein Goldewijk K.,
    2. Beusen A.,
    3. de Vos M.,
    4. van Drecht G.
    2010 The HYDE 3.1 spatially explicit database of human induced land use change over the past 12 000 years. Glob. Ecol. Biogeogr. 20, 73–86. doi:10.1111/j.1466-8238.2010.00587.x (doi:10.1111/j.1466-8238.2010.00587.x)
    OpenUrlCrossRefWeb of Science
  10. ↵
    1. Klein Goldewijk K.,
    2. Beusen A.,
    3. Janssen P.
    2010 Long term dynamic modeling of global population and built-up area in a spatially explicit way, HYDE 3 1. Holocene 20, 565–573. doi:10.1177/0959683609356587 (doi:10.1177/0959683609356587)
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Kaplan J. O.,
    2. Krumhardt K. M.,
    3. Zimmerman N.
    2009 The prehistorical and preindustrial deforestation of Europe. Quat. Sci. Rev. 28, 2015–3034. doi:10.1016/j.quascirev.2009.09.028 (doi:10.1016/j.quascirev.2009.09.028)
    OpenUrlCrossRef
  12. ↵
    1. Rackham O.
    1980 Ancient woodland. London, UK: Edward Arnold.
  13. ↵
    1. Le Quéré C,
    2. et al.
    2009 Trends in the sources and sinks of carbon dioxide. Nat. Geosci. 2, 831–836. doi:10.1038/ngeo689 (doi:10.1038/ngeo689)
    OpenUrlCrossRefWeb of Science
  14. ↵
    1. Monteith J.,
    2. Unsworth M.
    1990 Principles of environmental physics, vol. 2. London, UK: Arnold.
  15. ↵
    1. Solomon S.,
    2. Qin D.,
    3. Manning M.,
    4. Chen Z.,
    5. Marquis M.,
    6. Averyt K. B.,
    7. Tignor M.,
    8. Miller H. L.
    1. Forster P.,
    2. et al.
    2007 Changes in atmospheric constituents and in radiative forcing. In Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Solomon S., Qin D., Manning M., Chen Z., Marquis M., Averyt K. B., Tignor M., Miller H. L.). Cambridge, UK: Cambridge University Press.
  16. ↵
    1. Matthews H. D.,
    2. Weaver A. J.,
    3. Eby M.,
    4. Meissner K. J.
    2003 Radiative forcing of climate by historical land cover change. Geophys. Res. Lett. 30, 1055. doi:10.1029/2002GL016098 (doi:10.1029/2002GL016098)
    OpenUrlCrossRef
  17. ↵
    Food and Agriculture Organization of the United Nations. 2002 Agricultural databases. See ftp://ftp.fao.org/docrep/fao/004/y3557e/y3557e01.pdf.
  18. ↵
    1. Ramankutty N.,
    2. Foley J. A.,
    3. Olejniczak N. J.
    2002 People on the land: changes in global population and croplands during the 20th century. Ambio 31, 251–257. doi:10.1579/0044-7447-31.3.251 (doi:10.1579/0044-7447-31.3.251)
    OpenUrlPubMed
  19. ↵
    1. Lin M.,
    2. Huybers P.
    2012 Reckoning wheat yield trends. Environ. Res. Lett. 7, 024016. doi:10.1088/1748-9326/7/2/024016 (doi:10.1088/1748-9326/7/2/024016)
    OpenUrlCrossRef
  20. ↵
    1. Parry M. L.,
    2. Rosenzweig C.,
    3. Iglesias A.,
    4. Livermore M.,
    5. Fischer G.
    2004 Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Glob. Environ. Change 14, 53–67. doi:10.1016/j.gloenvcha.2003.10.008 (doi:10.1016/j.gloenvcha.2003.10.008)
    OpenUrlCrossRef
  21. ↵
    1. Doebley J.
    2004 The genetics of maize evolution. Annu. Rev. Genet. 38, 37–59. doi:10.1146/annurev.genet.38.072902.092425 (doi:10.1146/annurev.genet.38.072902.092425)
    OpenUrlCrossRefPubMedWeb of Science
  22. ↵
    1. Maggioni L.,
    2. von Bothmer R.,
    3. Poulsen G.,
    4. Branca F.
    2010 Origin and domestication of cole crops (Brassica oleracea L.): linguistic and literary considerations. Econ. Bot. 64, 109–123. doi:10.1007/s12231-010-9115-2 (doi:10.1007/s12231-010-9115-2)
    OpenUrlCrossRef
  23. ↵
    1. Tanno K.-I.,
    2. Wilcox G.
    2006 How fast was wild wheat domesticated?. Science 311, 1886. doi:10.1126/science.1124635 (doi:10.1126/science.1124635)
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Ladizinsky G.
    1999 On the origin of almond. Genet. Resour. Crop Evol. 46, 143–147. doi:10.1023/A:1008690409554 (doi:10.1023/A:1008690409554)
    OpenUrlCrossRefWeb of Science
  25. ↵
    1. Buddenhagen I.
    1983 Breeding strategies for stress and disease resistance in developing countries. Annu. Rev. Phytopathol. 21, 385–409. doi:10.1146/annurev.py.21.090183.002125 (doi:10.1146/annurev.py.21.090183.002125)
    OpenUrlCrossRefWeb of Science
  26. ↵
    1. Bus V.,
    2. Ranatunga C.,
    3. Gardiner S.,
    4. Bassett H.,
    5. Rikkerink E.
    2000 Marker assisted selection for pest and disease resistance in the New Zealand apple breeding programme. Acta Horticulturae 538, 541–547.
    OpenUrl
  27. ↵
    1. Gausmann H. W.
    1977 Reflectance of leaf components. Remote Sens. Environ. 6, 1–9. doi:10.1016/0034-4257(77)90015-3 (doi:10.1016/0034-4257(77)90015-3)
    OpenUrlCrossRefWeb of Science
  28. ↵
    1. Gueymard C.
    2004 The sun's total and spectral irradiance for solar energy applications and solar radiation models. Sol. Energy 76, 423–453. doi:10.1016/j.solener.2003.08.039 (doi:10.1016/j.solener.2003.08.039)
    OpenUrlCrossRefWeb of Science
  29. ↵
    1. Mulroy T. W.
    1979 Spectral properties of heavily glaucous and non-glaucous leaves of a succulent rosette-plant. Oecologia 38, 349–357. doi:10.1007/BF00345193 (doi:10.1007/BF00345193)
    OpenUrlCrossRefWeb of Science
  30. ↵
    1. Knapp A. K.,
    2. Carter G. A.
    1998 Variability in leaf optical properties among 26 species from a broad range of habitats. Am. J. Bot. 85, 940–946. doi:10.2307/2446360 (doi:10.2307/2446360)
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Hatfield J. L.,
    2. Carlson R. E.
    1979 Light quality distributions and spectral albedo of three maize canopies. Agric. Meteorol. 20, 215–226. doi:10.1016/0002-1571(79)90022-0 (doi:10.1016/0002-1571(79)90022-0)
    OpenUrlCrossRef
  32. ↵
    1. Holmes M. G.,
    2. Keiller D. R.
    2002 Effects of pubescence and waxes on the reflectance of leaves in the ultraviolet and photosynthetic wavebands: a composition of a range of species. Plant Cell Environ. 25, 85–93. doi:10.1046/j.1365-3040.2002.00779.x (doi:10.1046/j.1365-3040.2002.00779.x)
    OpenUrlCrossRefWeb of Science
  33. ↵
    1. Febrero A.,
    2. Fernandez S.,
    3. Molina-Cano J.,
    4. Araus J.
    1998 Yield, carbon isotope discrimination, canopy reflectance and cuticular conductance of barley isolines of differing glaucousness. J. Exp. Bot. 49, 1575–1581. doi:10.1093/jxb/49.326.1575 (doi:10.1093/jxb/49.326.1575)
    OpenUrlAbstract/FREE Full Text
  34. ↵
    1. Grant R. H.,
    2. Heisler G. M.,
    3. Gao W.,
    4. Jenks M.
    2003 Ultraviolet leaf reflectance of common urban trees and the prediction of reflectance from leaf surface characteristics. Agric. Meteorol. 120, 127–139. doi:10.1016/j.agrformet.2003.08.025 (doi:10.1016/j.agrformet.2003.08.025)
    OpenUrlCrossRef
  35. ↵
    1. Rashotte A. M.,
    2. Jenks M. A.,
    3. Nguyen T. D.,
    4. Feldmann K. A.
    1997 Epicuticular wax variation in ecotypes of. Arabidopsis thaliana. Phytochemistry 45, 251–255. doi:10.1016/S0031-9422(96)00792-3 (doi:10.1016/S0031-9422(96)00792-3)
    OpenUrlCrossRefPubMedWeb of Science
  36. ↵
    1. Uddin M. N.,
    2. Marshall D. R.
    1988 Variation in epicuticular wax content in wheat. Euphytica 38, 3–9. doi:10.1007/BF00024805 (doi:10.1007/BF00024805)
    OpenUrlCrossRefWeb of Science
  37. ↵
    1. Woodward I.,
    2. Bardgett R. D.,
    3. Raven J. A.,
    4. Hethrington A. M.
    2009 Biological approaches to global environment change mitigation and remediation. Curr. Biol. 19, 615–623. doi:10.1016/j.cub.2009.06.012 (doi:10.1016/j.cub.2009.06.012)
    OpenUrlCrossRef
  38. ↵
    1. Gaskill A. Jr.,
    2. Reese C. E.
    2003 Global warming mitigation by reduction of outgoing longwave radiation through large-scale surface albedo enhancement of deserts using white plastic polyethylene film: the global albedo enhancement project (GAEP) research plan. Report from Environmental Reference Materials, Inc., Research Triangle Park, NC.
  39. ↵
    1. Dong B.,
    2. Sutton R. T.
    2005 Mechanism of interdecadal thermohaline circulation variability in a coupled ocean–atmosphere GCM. J. Clim. 18, 1117–1135. doi:10.1175/JCLI3328.1 (doi:10.1175/JCLI3328.1)
    OpenUrlCrossRefWeb of Science
  40. ↵
    1. Hamwey R.
    2007 Active amplification of the terrestrial albedo to mitigate climate change: an exploratory study. Mitigation Adaptation Strateg. Glob. Change 12, 419–439. doi:10.1007/s11027-005-9024-3 (doi:10.1007/s11027-005-9024-3)
    OpenUrlCrossRef
  41. ↵
    1. Charney J.,
    2. Quirk W. J.,
    3. Chow S.-H.,
    4. Kornfeld J.
    1977 A comparative study of the effects of albedo change on drought in semi-arid regions. J. Atmos. Sci. 34, 1366–1385. doi:10.1175/1520-0469(1977)034<1366:ACSOTE>2.0.CO;2 (doi:10.1175/1520-0469(1977)034<1366:ACSOTE>2.0.CO;2)
    OpenUrlCrossRefWeb of Science
  42. ↵
    1. Henderson-Sellers A.,
    2. Gornitz V.
    1984 Possible climatic impacts of land cover transformations, with particular emphasis on tropical deforestation. Clim. Change 6, 231–257. doi:10.1007/BF00142475 (doi:10.1007/BF00142475)
    OpenUrlCrossRefWeb of Science
  43. ↵
    1. Irvine P.,
    2. Ridgwell A.
    2009 Geoengineering: taking control of our planet's climate. Sci. Progress. 92, 139–162. doi:10.3184/003685009X461495 (doi:10.3184/003685009X461495)
    OpenUrlCrossRef
  44. ↵
    1. Sauerbeck D. R.
    2001 CO2 emissions and C sequestration by agriculture: perspectives and limitations. Nutrient Cycl. Agroecosyst. 60, 253–266. doi:10.1023/A:1012617516477 (doi:10.1023/A:1012617516477)
    OpenUrlCrossRefWeb of Science
  45. ↵
    1. Lal R.
    2004 Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623–1627. doi:10.1126/science.1097396 (doi:10.1126/science.1097396)
    OpenUrlAbstract/FREE Full Text
  46. ↵
    1. Betts R. A.
    2000 Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408, 187–190. doi:10.1038/35041545 (doi:10.1038/35041545)
    OpenUrlCrossRefPubMedWeb of Science
  47. ↵
    1. Rayner S.,
    2. Redgwell C.,
    3. Savulescu J.,
    4. Pidgeon N.,
    5. Kruger T.
    2009 Memorandum on draft principles for the conduct of geoengineering research: House of Commons Science and Technology Committee inquiry into the regulation of geoengineering. See http://www.publications.parliament.uk/pa/cm200910/cmselect/cmsctech/221/221.pdf
  48. ↵
    Asilomar Scientific Organizing Committee (ASOC). 2010 The Asilomar conference recommendations on principles for research into climate engineering techniques. Washington, DC: Climate Institute.
  49. ↵
    1. Morton O.
    2009 Crops that cool. Nat. News. doi:10.1038/news.2009.33 (doi:10.1038/news.2009.33)
    OpenUrlCrossRef
  50. ↵
    1. Merah O.,
    2. Deléens E.,
    3. Souyris I.,
    4. Monneveux P.
    2000 Effect of glaucousness on carbon isotope discrimination and grain yield in durum wheat. J. Agron. Crop Sci. 185, 259–265. doi:10.1046/j.1439-037x.2000.00434.x (doi:10.1046/j.1439-037x.2000.00434.x)
    OpenUrlCrossRefWeb of Science
  51. ↵
    1. Moreshet S.,
    2. Cohen Y.,
    3. Fuchs M. E.
    1979 Effect of increasing foliage reflectance on yield, growth, and physiological behavior of a dryland cotton crop. Crop Sci. 19, 863–868. doi:10.2135/cropsci1979.0011183X001900060029x (doi:10.2135/cropsci1979.0011183X001900060029x)
    OpenUrlCrossRefWeb of Science
  52. ↵
    1. Lowe H. J. B.,
    2. Angus W. J.
    1985 Grain aphid infestations of winter wheat variety trials 1984. Ann. Appl. Biol. 106, 591–594. doi:10.1111/j.1744-7348.1985.tb03150.x (doi:10.1111/j.1744-7348.1985.tb03150.x)
    OpenUrlCrossRef
  53. ↵
    1. Ringelmann A.,
    2. Riedel M.,
    3. Riederer M.,
    4. Hildebrandt U.
    2009 Two sides of a leaf blade: Blumeria graminis needs chemical cues in cuticular waxes of Lolium perenne for germination and differentiation. Planta 230, 95–105. doi:10.1007/s00425-009-0924-4 (doi:10.1007/s00425-009-0924-4)
    OpenUrlCrossRefPubMedWeb of Science
  54. ↵
    1. Koch K.,
    2. Ensikat H. J.
    2008 The hydrophobic coatings of plant surfaces: epicuticular wax crystals and their morphologies, crystallinity and molecular self-assembly. Micron 39, 759–772. doi:10.1016/j.micron.2007.11.010 (doi:10.1016/j.micron.2007.11.010)
    OpenUrlCrossRefPubMedWeb of Science
  55. ↵
    1. Atkinson D.,
    2. Porter J. R.
    1996 Temperature, plant development and crop yields. Trends Plant Sci. 1, 119–124. doi:10.1016/S1360-1385(96)90006-0 (doi:10.1016/S1360-1385(96)90006-0)
    OpenUrlCrossRefWeb of Science
  56. ↵
    1. Murphy J. M.,
    2. et al.
    2009 UK Climate projections science report: climate change projections. Exeter, UK: Met Office Hadley Centre.
  57. ↵
    Environment Agency. 2009 Water for people and the environment: water resources strategy for England and Wales. Bristol, UK: Environment Agency. See http://publications.environment-agency.gov.uk/pdf/GEHO0309BPKX-E-E.pdf
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