Winners and losers of national and global efforts to reconcile agricultural intensification and biodiversity conservation

Closing yield gaps within existing croplands, and thereby avoiding further habitat conversions, is a prominently and controversially discussed strategy to meet the rising demand for agricultural products, while minimizing biodiversity impacts. The agricultural intensification associated with such a strategy poses additional threats to biodiversity within agricultural landscapes. The uneven spatial distribution of both yield gaps and biodiversity provides opportunities for reconciling agricultural intensification and biodiversity conservation through spatially optimized intensification. Here, we integrate distribution and habitat information for almost 20,000 vertebrate species with land‐cover and land‐use datasets. We estimate that projected agricultural intensification between 2000 and 2040 would reduce the global biodiversity value of agricultural lands by 11%, relative to 2000. Contrasting these projections with spatial land‐use optimization scenarios reveals that 88% of projected biodiversity loss could be avoided through globally coordinated land‐use planning, implying huge efficiency gains through international cooperation. However, global‐scale optimization also implies a highly uneven distribution of costs and benefits, resulting in distinct “winners and losers” in terms of national economic development, food security, food sovereignty or conservation. Given conflicting national interests and lacking effective governance mechanisms to guarantee equitable compensation of losers, multinational land‐use optimization seems politically unlikely. In turn, 61% of projected biodiversity loss could be avoided through nationally focused optimization, and 33% through optimization within just 10 countries. Targeted efforts to improve the capacity for integrated land‐use planning for sustainable intensification especially in these countries, including the strengthening of institutions that can arbitrate subnational land‐use conflicts, may offer an effective, yet politically feasible, avenue to better reconcile future trade‐offs between agriculture and conservation. The efficiency gains of optimization remained robust when assuming that yields could only be increased to 80% of their potential. Our results highlight the need to better integrate real‐world governance, political and economic challenges into sustainable development and global change mitigation research.     

Trade‐offs between land and water requirements for large‐scale bioenergy production

Bioenergy is expected to play an important role in the future energy mix as it can substitute fossil fuels and contribute to climate change mitigation. However, large‐scale bioenergy cultivation may put substantial pressure on land and water resources. While irrigated bioenergy production can reduce the pressure on land due to higher yields, associated irrigation water requirements may lead to degradation of freshwater ecosystems and to conflicts with other potential users. In this article, we investigate the trade‐offs between land and water requirements of large‐scale bioenergy production. To this end, we adopt an exogenous demand trajectory for bioenergy from dedicated energy crops, targeted at limiting greenhouse gas emissions in the energy sector to 1100 Gt carbon dioxide equivalent until 2095. We then use the spatially explicit global land‐ and water‐use allocation model MAgPIE to project the implications of this bioenergy target for global land and water resources. We find that producing 300 EJ yr^?1 of bioenergy in 2095 from dedicated bioenergy crops is likely to double agricultural water withdrawals if no explicit water protection policies are implemented. Since current human water withdrawals are dominated by agriculture and already lead to ecosystem degradation and biodiversity loss, such a doubling will pose a severe threat to freshwater ecosystems. If irrigated bioenergy production is prohibited to prevent negative impacts of bioenergy cultivation on water resources, bioenergy land requirements for meeting a 300 EJ yr^?1 bioenergy target increase substantially (+ 41%) – mainly at the expense of pasture areas and tropical forests. Thus, avoiding negative environmental impacts of large‐scale bioenergy production will require policies that balance associated water and land requirements.     

Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

A Land System representation for global assessments and land‐use modeling

Current global scale land‐change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land‐use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human‐environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi‐)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land‐use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land‐change models that include the human drivers of land change are best parameterized at sub‐global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.     

A review of global potentially available cropland estimates and their consequences for model‐based assessments

The world's population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model‐based assessments of land‐use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land‐change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land‐use change assessments, the results indicate a large range of estimates with important consequences for model‐based assessments.     

Land management: data availability and process understanding for global change studies

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human‐induced changes in terrestrial ecosystems that do not result in land‐cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one‐tenth of the ice‐free land surface is under intense human management, half under medium and one‐fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.     

Agricultural intensification in Brazil and its effects on land‐use patterns: an analysis of the 1975–2006 period

Does agricultural intensification reduce the area used for agricultural production in Brazil? Census and other data for time periods 1975–1996 and 1996–2006 were processed and analyzed using Geographic Information System and statistical tools to investigate whether and if so, how, changes in yield and stocking rate coincide with changes in cropland and pasture area. Complementary medium‐resolution data on total farmland area changes were used in a spatially explicit assessment of the land‐use transitions that occurred in Brazil during 1960–2006. The analyses show that in agriculturally consolidated areas (mainly southern and southeastern Brazil), land‐use intensification (both on cropland and pastures) coincided with either contraction of both cropland and pasture areas, or cropland expansion at the expense of pastures, both cases resulting in farmland stability or contraction. In contrast, in agricultural frontier areas (i.e., the deforestation zones in central and northern Brazil), land‐use intensification coincided with expansion of agricultural lands. These observations provide support for the thesis that (i) technological improvements create incentives for expansion in agricultural frontier areas; and (ii) farmers are likely to reduce their managed acreage only if land becomes a scarce resource. The spatially explicit examination of land‐use transitions since 1960 reveals an expansion and gradual movement of the agricultural frontier toward the interior (center‐western Cerrado) of Brazil. It also indicates a possible initiation of a reversed trend in line with the forest transition theory, i.e., agricultural contraction and recurring forests in marginally suitable areas in southeastern Brazil, mainly within the Atlantic Forest biome. The significant reduction in deforestation that has taken place in recent years, despite rising food commodity prices, indicates that policies put in place to curb conversion of native vegetation to agriculture land might be effective. This can improve the prospects for protecting native vegetation by investing in agricultural intensification.     

Effects of land use change and management on the European cropland carbon balance

We model the carbon balance of European croplands between 1901 and 2000 in response to land use and management changes. The process‐based ORCHIDEE‐STICS model is applied here in a spatially explicit framework. We reconstructed land cover changes, together with an idealized history of agro‐technology. These management parameters include the treatment of straw and stubble residues, application of mineral fertilizers, improvement of cultivar species and tillage. The model is integrated for wheat and maize during the period 1901–2000 forced by climate each 1/2‐hour, and by atmospheric CO₂, land cover change and agro‐technology each year. Several tests are performed to identify the most sensitive agro‐technological parameters that control the net biome productivity (NBP) in the 1990s, with NBP equaling for croplands the soil C balance. The current NBP is a small sink of 0.16 t C ha^?1 yr^?1. The value of NBP per unit area reflects past and current management, and to a minor extent the shrinking areas of arable land consecutive to abandonment during the 20th Century. The uncertainty associated with NBP is large, with a 1‐sigma error of 0.18 t C ha^?1 yr^?1 obtained from a qualitative, but comprehensive budget of various error terms. The NBP uncertainty is dominated by unknown historical agro‐technology changes (47%) and model structure (27%), with error in climate forcing playing a minor role. A major improvement to the framework would consist in using a larger number of representative crops. The uncertainty of historical land‐use change derived from three different reconstructions, has a surprisingly small effect on NBP (0.01 t C ha^?1 yr^?1) because cropland area remained stable during the past 20 years in all the tested land use forcing datasets. Regional cross‐validation of modeled NBP against soil C inventory measurements shows that our results are consistent with observations, within the uncertainties of both inventories and model. Our estimation of cropland NBP is however likely to be biased towards a sink, given that inventory data from different regions consistently indicate a small source whereas we model a small sink.     

Rapid redistribution of agricultural land alters avian richness,abundance, and functional diversity

The conversion of natural, or seminatural, habitats to agricultural land and changes in agricultural land use are significant drivers of biodiversity loss. Within the context of land‐sharing versus land‐sparing debates, large‐scale commercial agriculture is known to be detrimental to biodiversity, but the effects of small‐scale subsistence farming on biodiversity are disputed. This poses a problem for sustainable land‐use management in the Global South, where approximately 30% of farmland is small‐scale. Following a rapid land redistribution program in Zimbabwe, we evaluated changes in avian biodiversity by examining richness, abundance, and functional diversity. Rapid land redistribution has, in the near term, resulted in increased avian abundance in newly farmed areas containing miombo woodland and open habitat. Conversion of seminatural ranched land to small‐scale farms had a negative impact on larger‐bodied birds, but species richness increased, and birds in some feeding guilds maintained or increased abundance. We found evidence that land‐use change caused a shift in the functional traits of the communities present. However, functional analyses may not have adequately reflected the trait filtering effect of land redistribution on large species. Whether newly farmed landscapes in Zimbabwe can deliver multiple benefits in terms of food production and habitat for biodiversity in the longer term is an open question. When managing agricultural land transitions, relying on taxonomic measures of diversity, or abundance‐weighted measures of function diversity, may obscure important information. If the value of smallholder‐farmed land for birds is to be maintained or improved, it will be essential to ensure that a wide array of habitat types is retained alongside efforts to reduce hunting and persecution of large bird species.     

Forest transitions in Eastern Europe and their effects on carbon budgets

Forests often rebound from deforestation following industrialization and urbanization, but for many regions our understanding of where and when forest transitions happened, and how they affected carbon budgets remains poor. One such region is Eastern Europe, where political and socio‐economic conditions changed drastically over the last three centuries, but forest trends have not yet been analyzed in detail. We present a new assessment of historical forest change in the European part of the former Soviet Union and the legacies of these changes on contemporary carbon stocks. To reconstruct forest area, we homogenized statistics at the provincial level for ad 1700–2010 to identify forest transition years and forest trends. We contrast our reconstruction with the KK11 and HYDE 3.1 land change scenarios, and use all three datasets to drive the LPJ dynamic global vegetation model to calculate carbon stock dynamics. Our results revealed that forest transitions in Eastern Europe occurred predominantly in the early 20th century, substantially later than in Western Europe. We also found marked geographic variation in forest transitions, with some areas characterized by relatively stable or continuously declining forest area. Our data suggest extensive deforestation in European Russia already prior to ad 1700, and even greater deforestation in the 18th and 19th centuries than in the KK11 and HYDE scenarios. Based on our reconstruction, cumulative carbon emissions from deforestation were greater before 1700 (60 Pg C) than thereafter (29 Pg C). Summed over our entire study area, forest transitions led to a modest uptake in carbon over recent decades, with our dataset showing the smallest effect (<5.5 Pg C) and a more heterogeneous pattern of source and sink regions. This suggests substantial sequestration potential in regrowing forests of the region, a trend that may be amplified through ongoing land abandonment, climate change, and CO₂ fertilization.     

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.     

Importance of scale,land‐use,and stream network properties for riparian plant communities along an urban gradient

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Global change pressures on soils from land use and management

Soils are subject to varying degrees of direct or indirect human disturbance, constituting a major global change driver. Factoring out natural from direct and indirect human influence is not always straightforward, but some human activities have clear impacts. These include land‐use change, land management and land degradation (erosion, compaction, sealing and salinization). The intensity of land use also exerts a great impact on soils, and soils are also subject to indirect impacts arising from human activity, such as acid deposition (sulphur and nitrogen) and heavy metal pollution. In this critical review, we report the state‐of‐the‐art understanding of these global change pressures on soils, identify knowledge gaps and research challenges and highlight actions and policies to minimize adverse environmental impacts arising from these global change drivers. Soils are central to considerations of what constitutes sustainable intensification. Therefore, ensuring that vulnerable and high environmental value soils are considered when protecting important habitats and ecosystems, will help to reduce the pressure on land from global change drivers. To ensure that soils are protected as part of wider environmental efforts, a global soil resilience programme should be considered, to monitor, recover or sustain soil fertility and function, and to enhance the ecosystem services provided by soils. Soils cannot, and should not, be considered in isolation of the ecosystems that they underpin and vice versa. The role of soils in supporting ecosystems and natural capital needs greater recognition. The lasting legacy of the International Year of Soils in 2015 should be to put soils at the centre of policy supporting environmental protection and sustainable development.     

A spatially explicit representation of conservation agriculture for application in global change studies

Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is proposed to contribute to climate change mitigation and adaptation through reduced emission of greenhouse gases, increased solar radiation reflection, and the sustainable use of soil and water resources. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present‐day national‐level estimates of CA to a 5 arcminute regular grid, based on multicriteria analysis. We provide a best estimate of CA distribution and an uncertainty range in the form of a low and high estimate of CA distribution, reflecting the inconsistency in CA definitions. We also design two scenarios of the potential future development of CA combining present‐day data and an assessment of the potential for implementation using biophysical and socioeconomic factors. By our estimates, 122–215 Mha or 9%–15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no‐tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no‐tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533–1130 Mha (38%–81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices.     

Temporal response of soil organic carbon after grassland‐related land‐use change

The net flux of CO₂ exchanged with the atmosphere following grassland‐related land‐use change (LUC) depends on the subsequent temporal dynamics of soil organic carbon (SOC). Yet, the magnitude and timing of these dynamics are still unclear. We compiled a global data set of 836 paired‐sites to quantify temporal SOC changes after grassland‐related LUC. In order to discriminate between SOC losses from the initial ecosystem and gains from the secondary one, the post‐LUC time series of SOC data was combined with satellite‐based net primary production observations as a proxy of carbon input to the soil. Globally, land conversion from either cropland or forest into grassland leads to SOC accumulation; the reverse shows net SOC loss. The SOC response curves vary between different regions. Conversion of cropland to managed grassland results in more SOC accumulation than natural grassland recovery from abandoned cropland. We did not consider the biophysical variables (e.g., climate conditions and soil properties) when fitting the SOC turnover rate into the observation data but analyzed the relationships between the fitted turnover rate and these variables. The SOC turnover rate is significantly correlated with temperature and precipitation (p < 0.05), but not with the clay fraction of soils (p > 0.05). Comparing our results with predictions from bookkeeping models, we found that bookkeeping models overestimate by 56% of the long‐term (100 years horizon) cumulative SOC emissions for grassland‐related LUC types in tropical and temperate regions since 2000. We also tested the spatial representativeness of our data set and calculated SOC response curves using the representative subset of sites in each region. Our study provides new insight into the impact grassland‐related LUC on the global carbon budget and sheds light on the potential of grassland conservation for climate mitigation.     

Spatial co‐localisation of extreme weather events: a clear and present danger

Extreme weather events have become a dominant feature of the narrative surrounding changes in global climate with large impacts on ecosystem stability, functioning and resilience; however, understanding of their risk of co‐occurrence at the regional scale is lacking. Based on the UK Met Office’s long‐term temperature and rainfall records, we present the first evidence demonstrating significant increases in the magnitude, direction of change and spatial co‐localisation of extreme weather events since 1961. Combining this new understanding with land‐use data sets allowed us to assess the likely consequences on future agricultural production and conservation priority areas. All land‐uses are impacted by the increasing risk of at least one extreme event and conservation areas were identified as the hotspots of risk for the co‐occurrence of multiple event types. Our findings provide a basis to regionally guide land‐use optimisation, land management practices and regulatory actions preserving ecosystem services against multiple climate threats.     

Optimizing carbon storage and biodiversity protection in tropical agricultural landscapes

With the rapidly expanding ecological footprint of agriculture, the design of farmed landscapes will play an increasingly important role for both carbon storage and biodiversity protection. Carbon and biodiversity can be enhanced by integrating natural habitats into agricultural lands, but a key question is whether benefits are maximized by including many small features throughout the landscape (‘land‐sharing’ agriculture) or a few large contiguous blocks alongside intensive farmland (‘land‐sparing’ agriculture). In this study, we are the first to integrate carbon storage alongside multi‐taxa biodiversity assessments to compare land‐sparing and land‐sharing frameworks. We do so by sampling carbon stocks and biodiversity (birds and dung beetles) in landscapes containing agriculture and forest within the Colombian Chocó‐Andes, a zone of high global conservation priority. We show that woodland fragments embedded within a matrix of cattle pasture hold less carbon per unit area than contiguous primary or advanced secondary forests (>15 years). Farmland sites also support less diverse bird and dung beetle communities than contiguous forests, even when farmland retains high levels of woodland habitat cover. Landscape simulations based on these data suggest that land‐sparing strategies would be more beneficial for both carbon storage and biodiversity than land‐sharing strategies across a range of production levels. Biodiversity benefits of land‐sparing are predicted to be similar whether spared lands protect primary or advanced secondary forests, owing to the close similarity of bird and dung beetle communities between the two forest classes. Land‐sparing schemes that encourage the protection and regeneration of natural forest blocks thus provide a synergy between carbon and biodiversity conservation, and represent a promising strategy for reducing the negative impacts of agriculture on tropical ecosystems. However, further studies examining a wider range of ecosystem services will be necessary to fully understand the links between land‐allocation strategies and long‐term ecosystem service provision.