Combined effects of climate and land-use change on the provision of ecosystem services in rice agro-ecosystems

Rice is the most consumed staple food for more than 3.5 billion people, with annual per capita consumption exceeding 100 kg in many Asian countries (Seck et al 2012). With a world population that is expected to increase from current 7.4 to 9.7 billion by 2050 (United Nations 2015) rice demand will continue to grow in the next decades. Even under ambitious scenarios of reducing food waste and distribution inequality (Ericksen et al 2009, Foley et al 2011), considerable increases in rice production will be necessary. These conditions place irrigated rice croplands among the world's most important agro-ecosystems (FAOSTAT 2014).

In addition to food production, rice agro-ecosystems simultaneously provide a number of other ecosystem services (ESS) that contribute to human well-being in rice producing regions as well as globally. These services include provision of fuel and fibre, regulation of water supply for irrigation and fishing, nutrient cycling and carbon sequestration, but also cultural services such as cultural identity associated with traditional rice farming (Burkhard et al 2015, Spangenberg et al 2014). Maintaining essential ESS, while meeting the increasing rice demand at the same time, represents a major challenge for rice producing countries, especially in Southeast Asia (Greenland 2006, Laborte et al 2012).

Rice agro-ecosystems, however, are affected by a range of natural and anthropogenic drivers, such as land use and climate change. In these irrigated cropping systems (Václavík et al 2013), rice terraces and other crop fields are often expanded, typically at the expense of natural forests, leading to substantial forest loss and degradation (Castella and Verburg 2007, Fox et al 2012, Settele 1998). Although much of the original landscapes in Southeast Asia had already been transformed centuries ago (Pongratz et al 2008), when native vegetation was turned into agricultural land, large environmental impacts from land use expansion and intensification still prevail (Field et al 2014, Houghton and Hackler 1999, Torres et al 2014).

In the future, ESS in rice agro-ecosystems will be affected by further increasing atmospheric CO₂ and associated climate change, which includes increasing temperature and shifts in rainfall regimes (Howden et al 2007). In Southeast Asia, temperatures are projected to rise regionally between 1.5 and 4 K depending on the scenario (Nakićenović et al 2000), but even moderate warming will likely reduce rice yields in the next coming decades (Peng et al 2004, Welch et al 2010). Additionally, projections of future precipitation show changes in the amount of rainfall, regionally varying between −20% to +20% (Meehl et al 2007) and a gradual increment in winter monsoon rainfall in Southeast Asia under most climate change scenarios (Siew et al 2013). Despite the complex interplay of factors, the question how the multiple interactions of drivers and their expected changes affect future provision of important ESS in rice agro-ecosystems has not been consistently investigated.

Considering the need to maintain various ESS in rice agro-ecosystems under changing climate and land use, integrative approaches are required to assess environmental as well as social-ecological impacts. While previous studies examined the potential effect of climate change on rice production (Welch et al 2010, Peng et al 2004, Naylor et al 2007), it has not yet been systematically examined how the combination of both climate and land-use change simultaneously impacts multiple ESS in rice agro-ecosystems. Such integrative approach is crucial to better understand whether the interaction of both drivers amplifies their impact on ESS (both leading to decrease or both leading to increase, i.e. amplification effect) or whether the projected change in one driver can balance out the effect of the other driver (i.e. offset effect). In addition, understanding the relationships among multiple ESS is increasingly recognized as essential to ensure multi-functionality of landscapes (Bennett et al 2009, Rodríguez et al 2006, Bennett et al 2015). Therefore, we need to examine whether ESS are bundled in either positive ways (synergies) or negative ways (trade-offs) in a response to common drivers that affect the changes in multiple services at the same time (Bennett et al 2009).

In this study, we use an integrative simulation approach to assess the combined effect of projected climate and land-use change on a bundle of ESS in rice agro-ecosystems in seven study areas in the Philippines and Vietnam. These areas represent suitable investigation systems, as both countries doubled their rice yield in only 20 years, reaching 44 and 18 million t yr⁻¹ in 2012, respectively (FAOSTAT 2014). At the same time, climate and land-use changes in these regions affect ESS that are crucial for local communities and the sustainable cultivation of rice (Settele et al 2015). We specifically focus on four ESS: (a) carbon storage, (b) carbon sequestration by the vegetation, (c) provision of irrigation water and (d) rice production, because these services are provided by the natural vegetation (a–c) or the cropland (d). Therefore, the ESS strongly depend on land-use change (d); they are connected to the carbon cycle/balance (a–b), thus closely related to climate change; and they are expected to show either synergistic effects (e.g. forest expansion increases carbon storage and provision of irrigation water) or trade-off effects (e.g. loss of forest due to rice field expansion reduces carbon storage).

Here, we address the following research questions: (1) What are the combined effects of projected climate and land-use changes on the provision of selected ESS in rice agro-ecosystems (amplification vs. offset effect)? (2) How do the relationships among multiple ESS change under scenarios of climate and land-use change (synergies vs. trade-offs)? To answer these questions we make use of LPJmL (Sitch et al 2003, Gerten et al 2004, Bondeau et al 2007, Rost et al 2008), a dynamic global vegetation and hydrology model (DGVM), and apply it at fine spatial resolution of 30 m to capture local heterogeneities in the seven study areas representative for rice production systems in Southeast Asia.

The novelty of our study lies first in quantifying the combined effects of climate and land-use change on multiple ESS and examining the ESS interactions in response to these two drivers. Second, for the first time, we apply a DGVM at the landscape scale, which enables us to provide more nuanced information for stakeholders and decision-makers in each study area. We briefly discuss the potential consequences of estimated changes for future socioeconomic development of the regions and the implications of our results as a first step to examine possible local adaptations to climate change.

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2.1. Study areas

The study was conducted in seven study areas in the Philippines (n = 3) and Vietnam (n = 4, figure 1) as part of a larger research project on sustainable rice production (LEGATO; Settele et al 2015). All areas were approximately 15 × 15 km in size, located along a gradient of elevation and land use (figure 2(a)). The proportion of agricultural land ranged from 19%−96% and the forest coverage ranged from 76% to 0% (table S1, available at stacks.iop.org/ERL/12/015003/mmedia). Because the climatic conditions and the coverage of agricultural land differ substantially in regions with different elevation, we grouped the study areas for the analyses into lowland sites and highland sites. The five lowland sites, Laguna (PH_1), Nueva Ecija (PH_2), Hai Duong (VN_1), Vinh Phuc (VN_2) and Tien Giang (VN_4), are situated below 500 m a.s.l. and show less than 35% of natural vegetation. The two highland sites, Ifugao (PH_3) and Lao Cai (VN_3), are situated above 500 m a.s.l. and have more than 60% of natural vegetation left. The two highland sites in particular have a long history of sustainable rice production with traditional cultivation methods, such as building of rice terraces and manual planting and maintaining of the rice crop (Settele 1998). For detailed descriptions of the study areas see table S1 as well as Klotzbücher et al (2015) and Burkhard et al (2015).

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Table 1. Overview of the selected ecosystem services.

Ecosystem service (ESS)	Short definition	Indicator (model output)	Unit	Reaction to climate change	Reaction to land use change (deforestation)
Carbon storage	Amount of carbon that is stored in above and below ground living and dead biomass.	Sum of carbon stored in vegetation, litter and soil.	[kg C m−2]	+∆T causes higher heterotrophic respiration and lower photosynthesis causes lower carbon storage; +∆T on high altitudes causes sparse vegetation gets more dense.	fewer forests cause less carbon storage
Carbon sequestration	Amount of carbon that is sequestered by natural vegetation and crops.	Annual sum of net primary production and carbon allocated in seeds, reduced by the annually respired carbon (heterotrophic respiration).	[g C m−2 yr−1]	+∆T causes higher respiration causes lower carbon sequestration.	more crops cause higher carbon sequestration
Irrigation water	Amount of water that is available for irrigation (while maintaining the environmental flow requirements of rivers, which is 45%–75% of the available water (Steffen et al 2015); amount before crop irrigation is calculated in the model.	25% of the annual sum of run-off water	[mm yr−1]	+∆T causes higher evaporation causes less irrigation water; +∆P causes more irrigation water.	negligible
Rice production	Amount of rice harvested in the study area.	Carbon harvested from rice plants multiplied by the factor 1/0.45 to convert from carbon to biomass.	[t yr−1]	+∆T causes lower yield.	more rice area causes more rice production

2.2. Simulating ecosystem services

2.3. Climate data and scenarios

2.4. Land use data and scenarios

2.5. Simulation experiments and analyses

For most ESS and scenarios, combined climate and land-use change reduced the provision of ESS when compared to the baseline period 2001–2010 (figures 3 and 4 for SRES A2; figure S4 and figure S5 for SRES B1). With the exception of irrigation water, climate change alone caused a considerable decrease in ESS by the end of this century (figure 3 (black boxes, representing no land-use change) and figure 4(a)). In contrast, the response to LUC depended largely on the considered land-use scenario (see also figure S2 table S8 for absolute values).

Carbon storage declined by 5%−30% by the end of the century, with the highest decrease in the lowland sites under the DART scenario (figure 3(b), light-grey boxes). The overall negative effect of climate change was typically amplified by LUC, especially under the more drastic High-conversion scenario (figure 4(c)). However, in the case of highland sites under Low-conversion scenario (figure 3(a) and figure 4(b)), LUC did partially offset the negative effect of projected climate change on carbon storage.

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Table 2. Pearson correlation coefficient between the ecosystem services for highland sites (A) and lowland sites (B). Correlation under land use change and climate change (either under SRES A2—CC_A2, or SRES B1—CC_B1) together for 2000–2099, or land-use change only (LUC only) for 2000–2030 Order of land use scenarios within climate scenarios is Const, Low-conversion, High-conversion, DART. Red indicates a positive correlation (> +0.5), while blue indicates a negative correlation (< −0.5). Significance indicated by ⁎ for p < 0.05 and ⁎⁎ for p < 0.01.

Carbon sequestration showed a slight overall decrease by 2099 (figure 3), although it showed mid-century increases in the lowland sites and continued to increase until the end of the century in the highland sites under the High-conversion scenario (+25%). The periodicity in this ESS, as shown in figure 4, is caused by the climate input (e.g. El Niño events or repeating climate characteristics), which has direct effects on the temperature and therefore influences the carbon sequestration. Nevertheless, the overall trend is negative towards 2099. LUC was only able to temporarily offset the negative effects of climate change, especially when greater shifts in land use were assumed, as in the High-conversion scenario (figure 4(c)).

The provision of irrigation water showed an overall positive trend with mean increases of +11% in highland sites (figure 3(a)) and +21% in lowland sites (figure 3(b)). This trend was driven mainly by climate change with only marginal amplification by LUC, irrespective of the LUC scenario. Like the carbon sequestration, irrigation water shows periodically repeating patterns, which can also be explained by the climate input (primarily precipitation). These two services are estimated on a short term (few months) and are therefore more sensitive to short-term fluctuations than the carbon storage and the production of rice.

In contrast to irrigation water, rice production showed a clear response to LUC. While the combination of both drivers had mostly negative effects on rice production in the long term, leading to losses typically between 20% and 40% by 2099, changes in land use in the highlands were able to offset these effects in the first decades of the century. In the High-conversion scenario, the increase by 2030 was strong enough (50%) to override climate change effects even after the period of assumed land-use change, leading to overall 10% increase by 2099 (figure 3(a) and figure 4(c)). The strong decrease in rice production after 2030 is caused solely by the negative effects of climate change, with higher minimum temperatures reducing yields (Peng et al 2004, Welch et al 2010). In the lowland sites, where options for cropland expansions are limited, LUC amplified climate-change induced decline in rice production. All rice production estimates were validated against on-site measurements. The results of this analysis showed that the simulated yields were comparable to measured yields as well to the yields reported by farmers (table S5).

The correlation analysis, using Pearson correlation coefficient r, identified whether the effects of climate and land-use change on provision of multiple ESS were in the same direction for two services (positive correlation indicates synergy, i.e. enhancing both ESS or diminishing both ESS) or in opposite directions (negative correlation indicates trade-off, i.e. diminishing one service while enhancing the other). The 'LUC only' columns in tables 2(a) and (b) show the effects of land-use change alone, while the other columns show the combined effects of climate and land-use change. Most pair-wise relationships were significant (table 2), especially for the lowland sites (table 2(b)), suggesting clear synergies and trade-offs among individual ESS. In lowlands, carbon storage and rice production, among others, were always positively correlated (synergy) with r ranging between 0.790 and 0.999, while carbon storage and irrigation water in lowlands were mostly negatively correlated (trade-off) with r ranging between −0.989 and 0.998 and nearly independent of the climate and the land-use change scenario. For some services the relationship changed slightly depending on (a) the climate scenario, showing large differences between the climate-change scenarios, e.g. irrigation water and rice production in highlands, or on (b) the LUC scenario, e.g. carbon sequestration and carbon storage in highland, or on (c) a combination of both drivers, e.g. carbon sequestration and irrigation water in lowlands.

Our results show that future changes in climate and land use lead to significant declines in the provision of three out of four quantified ESS by the end of the century. With the exception of irrigation water, whose provision increases due to increased precipitation levels, climate change reduces the supply of the considered ESS. The additional effect of LUC is smaller (figure S3). Where unmanaged land is still available, new land conversion may allow partially offsetting negative climate change effects, but only at the expense of carbon storage in natural vegetation and therewith at the expense of natural habitat.

The future climate-induced reduction in carbon storage is mainly caused by lower photosynthesis rate and higher respiration under elevated temperatures (Ryan 1991). This trend is further amplified because under most LUC scenarios the extent of natural vegetation decreases, and therewith also carbon stored in forests. In contrast to carbon storage, the sequestration of carbon is likely to increase with projected LUC in all cases, except for the High-conversion scenario in highland sites. Carbon sequestration represents the ability of the vegetation to absorb carbon. In systems at equilibrium, such as old growth forest, the maintenance respiration is higher than in agricultural systems, which leads to a lower NPP. As a consequence, the carbon sequestration in crop systems is much higher, although trees have larger leaf area available for photosynthesis. Therefore, the expansion of agricultural areas with fast growing rice and vegetables, which exhibit low rates of maintenance respiration (Ryan 1991), will lead to an increase in carbon sequestration. This is especially evident in the highland sites under the High-conversion LUC scenario. In these cases, large forest-to-cropland conversions are expected. This changes the ratio of trees (less trees, with lower carbon sequestration) to crops (more crops, with higher carbon sequestration), causing a substantial offset of the negative climate change impact by the year 2100.

The availability of water for irrigation is a major prerequisite for rice production. Despite the projected increase in its provision under all considered scenarios, climate change leads to a decline in rice production which is in agreement with previous studies (Peng et al 2004, Welch et al 2010). Where rice production can only be increased through expansion of rice terraces as projected by our LUC scenarios in the highland sites, trade-offs to carbon storage emerge due to significant losses of natural forest vegetation, however this trade-off can only be assessed by considering land-use change only. In the lowland sites, where nearly no additional land is available for agricultural expansion and the extent of settlements is likely to grow, we project an additional decline in rice production compared to climate change only (figures 3 and 4).

In addition to the effects arising from land available for conversion, the observed differences that we found between highland and lowland sites for most projections of ESS can be mainly attributed to the lower cropland coverage and lower temperatures in the highland compared to the lowland sites. The negative effects of climate change are less pronounced in the highland sites, because the increase in carbon storage in the highest altitudes caused by a temperature increase can compensate for losses in lower lying areas. This positive effect, however, has its limitation due to the decreasing available area in higher altitudes. Among our study areas, Lao Cai (VN_3) is the highest in elevation and would benefit most from increasing temperatures, since the mountain tops are only sparsely covered with vegetation. The other highland site (Ifugao, PH_3) is at lower elevation and would benefit less because the mountain tops are already covered with vegetation.

Our findings narrow the scope of potential land-use options that can be adopted to reduce the threat posed by future climate change to ESS in rice agro-ecosystems. The three LUC scenarios developed for this study allowed us to assess a range of such options. However, in all cases the potential of land use for local adaptation to climate change is limited. In the case of rice production, for example, the expansion of rice terraces would have to be drastic (see also figure 2(c) Lao Cai) to even partially offset the impact of climate change. In addition, our results indicate that local policies promoting such type of LUC might work only in the horizon of a few decades, but alone would be insufficient to mitigate climate change in the long term. Therefore, local policies aiming at sustainable rice production and food security in the face of climate change should consider other adaptation strategies suitable for rice agro-ecosystems, including crop diversification and rotation, the use of stress-tolerant rice varieties, adjustments of sowing season, or methods of ecological engineering (Banerjee et al 2016, Kumar 2016, Li et al 2015).

Managing rice agro-ecosystems for multiple ESS is even more challenging because several ESS are often provided by the same land-use type but they do not always respond the same way to underlying drivers (Haase et al 2012). We identified such trade-offs, e.g. between irrigation water and all other ESS, as the provision of irrigation water shows consistently positive response to combined climate and land-use change effects while the provision of other ESS declines. Similarly, trade-offs between rice production and carbon storage were found as a response to LUC especially in highland regions of Lao Cai (VN_3) and Ifugao (PH_3) (table 2(a)). However, the trade-offs between ESS are often not obvious because both ESS considered are heavily influenced by climate change, which masks the effects of LUC (table 2(a)). The identified trade-off between rice production and carbon storage—under land-use change only—corroborates findings by Burkhard et al (2015) who documented trade-offs between crop production and a range of other ESS, including biodiversity, crop pollination and recreation. Especially when high rates of LUC are assumed, the encroachment of crop fields in natural forests not only leads to a reduction in carbon storage but also reduces potential timber and firewood extraction and affects habitat for plant and animal species. Therefore, we caution that, although we quantified the response of arguably the most important ESS in rice agro-ecosystems, more detailed and context-specific assessments are needed to understand the possible outcomes of climate change and land management strategies (Castonguay et al 2016). In addition to rice production, these assessments should consider other non-provisioning ecosystem services, impacts on biodiversity, resilience of rice agro-ecosystems, and cultural and societal implications (Förster et al 2015).

Understanding the effects of climate and land-use change on the provision of ESS and identifying synergies and trade-offs in their responses is crucial for maintaining multi-functional production systems. Our study of rice agro-ecosystems showed that the trend in the ESS provision is relatively clear if we consider climate change only, but it becomes more complex when LUC is included, leading to opposite trends depending on the severity of environmental change and the study area. In general, climate change and LUC reduced ESS provision in most of the considered scenarios, both in highland (10 out of 16) and lowland sites (12 out of 16). Only high land-conversion rates were able to partially offset negative climate change effects. With a projected temperature increase for the Philippines and Vietnam of up to 4 K by 2100, rice production can likely be maintained only at the expense of natural vegetation, whose reduction is typically accompanied by loss of native habitat and biodiversity with poorly understood cultural and societal implications. Therefore, locally specific land-use policies and development plans have to consider not only the provision of crops but also regulating and cultural services to maintain future human well-being and natural resources of rice agro-ecosystems in Southeast Asia. This study illustrates the importance of considering small scale land-use patterns and climate-change scenarios to assess the complex interactions of several ESS and to inform local decision makers and stakeholders.

This research was conducted as part of the LEGATO project, funded by the German Ministry of Research and Education (BMBF) within their funding measure Sustainable Land Management; funding nos. 01LL0917A until 01LL0917O. TV was supported by BMBF grant 01LL0901A: GLUES. This research contributes to the Global Land Project (www.globallandproject.org). We also thank Vera Tekken, Josef Settele, Joachim Spangenberg, KL Heong, Vu Kim Chi, Dr Chien, Stefan Hotes, Monina Escalada and Ruth Delzeit for support in developing the land-use change scenarios.