Land use for animal production in global change studies: Defining and characterizing a framework

Land use for animal production influences the earth system in a variety of ways, including local‐scale modification to biodiversity, soils, and nutrient cycling; regional changes in albedo and hydrology; and global‐scale changes in greenhouse gas and aerosol concentrations. Pasture is furthermore the single most extensive form of land cover, currently comprising about 22–26% of the earth's ice‐free land surface. Despite the importance and variable expressions of animal production, distinctions among different systems are effectively absent from studies of land use and land cover change. This deficiency is improving; however, livestock production system classifications are rarely applied in this context, and the most popular global land cover inventories still present only a single, usually poorly defined category of “pasture” or “rangeland” with no characterization of land use. There is a marked lack of bottom‐up, evidence‐based methodology, creating a pressing need to incorporate cross‐disciplinary evidence of past and present animal production systems into global change studies. Here, we present a framework, modified from existing livestock production systems, that is rooted in sociocultural, socioeconomic, and ecological contexts. The framework defines and characterizes the range of land usage pertaining to animal production, and is suitable for application in land use inventories and scenarios, land cover modeling, and studies on sustainable land use in the past, present, and future.     

Land abandonment and changes in snow cover period accelerate range expansions of sika deer

Ongoing climate change and land‐use change have the potential to substantially alter the distribution of large herbivores. This may result in drastic changes in ecosystems by changing plant–herbivore interactions. Here, we developed a model explaining sika deer persistence and colonization between 25 years in terms of neighborhood occupancy and habitat suitability. We used climatic, land‐use, and topographic variables to calculate the habitat suitability and evaluated the contributions of the variables to past range changes of sika deer. We used this model to predict the changes in the range of sika deer over the next 100 years under four scenario groups with the combination of land‐use change and climate change. Our results showed that both climate change and land‐use change had affected the range of sika deer in the past 25 years. Habitat suitability increased in northern or mountainous regions, which account for 71.6% of Japan, in line with a decrease in the snow cover period. Habitat suitability decreased in suburban areas, which account for 28.4% of Japan, corresponding to land‐use changes related to urbanization. In the next 100 years, the decrease in snow cover period and the increase in land abandonment were predicted to accelerate the range expansion of sika deer. Comparison of these two driving factors revealed that climate change will contribute more to range expansion, particularly from the 2070s onward. In scenarios that assumed the influence of both climate change and land‐use change, the total sika deer range increased by between +4.6% and +11.9% from the baseline scenario. Climate change and land‐use change will require additional efforts for future management of sika deer, particularly in the long term.     

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.     

Biodiversity scenarios neglect future land‐use changes

Efficient management of biodiversity requires a forward‐looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land‐use and land‐cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land‐use and land‐cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward‐looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge.     

Spatial relationship between climatologies and changes in global vegetation activity

Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land‐cover and climate‐related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982–2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate‐associated effects and a spatially correlated field representing the combined influence of other factors, including land‐use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large‐scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land‐cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).     

Land use change and carbon cycle in arid and semi-arid lands of East and Central Asia

Dramatic changes in land use have occurred in arid and semi-arid landsof Asia during the 20th century. Grassland conversion into croplands and ecosystem degradation is widespread due to the high growth rate of human population and political reforms of pastoral systems. Rangeland degradation made many parts of this region vulnerable to environmental and political changes. The collapse of the livestock sector in some states of central Asia, expansion of livestock inChina and intensive degradation of grasslands in China are examples of the responses of pastoral systems to these changes over the past decades. Carbon dynamics in this region is highly variable in space and time. Land use/cover changes with widespread reduction of forest and grasslands increased carbon emission from the region.     

Land cover change or land‐use intensification: simulating land system change with a global‐scale land change model

Land‐use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land‐use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970–2000 period and projections of other global and regional land change models.     

Land use change and carbon cycle in arid and semi-arid lands of East and Central Asia

Dramatic changes in land use have occurred in arid and semi-arid lands of Asia duringthe 20th century. Grassland conversion into croplands and ecosystem degradation is widespreaddue to the high growth rate of human population and political reforms of pastoral systems. Rangeland degradation made many parts of this region vulnerable to environmental and political changes. The collapse of the livestock sector in some states of central Asia, expansion of livestockin China and intensive degradation of grasslands in China are examples of the responses of pastoral systems to these changes over the past decades. Carbon dynamics in this region is highly variable in space and time. Land use/cover changes with widespread reduction of forest and grasslands increased carbon emission from the region.     

Historical land‐use and landscape change in southern Sweden and implications for present and future biodiversity

The two major aims of this study are (1) To test the performance of the Landscape Reconstruction Algorithm (LRA) to quantify past landscape changes using historical maps and related written sources, and (2) to use the LRA and map reconstructions for a better understanding of the origin of landscape diversity and the recent loss of species diversity. Southern Sweden, hemiboreal vegetation zone. The LRA was applied on pollen records from three small bogs for four time windows between AD 1700 and 2010. The LRA estimates of % cover for woodland/forest, grassland, wetland, and cultivated land were compared with those extracted from historical maps within 3‐km radius around each bog. Map‐extracted land‐use categories and pollen‐based LRA estimates (in % cover) of the same land‐use categories show a reasonable agreement in several cases; when they do not agree, the assumptions used in the data (maps)‐model (LRA) comparison are a better explanation of the discrepancies between the two than possible biases of the LRA modeling approach. Both the LRA reconstructions and the historical maps reveal between‐site differences in landscape characteristics through time, but they demonstrate comparable, profound transformations of the regional and local landscapes over time and space due to the agrarian reforms in southern Sweden during the 18th and 19th centuries. The LRA was found to be the most reasonable approach so far to reconstruct quantitatively past landscape changes from fossil pollen data. The existing landscape diversity in the region at the beginning of the 18th century had its origin in the long‐term regional and local vegetation and land‐use history over millennia. Agrarian reforms since the 18th century resulted in a dramatic loss of landscape diversity and evenness in both time and space over the last two centuries leading to a similarly dramatic loss of species (e.g., beetles).     

Multiple Methods in the Study of Driving Forces of Land Use and Land Cover Change: A Case Study of SE Kajiado District,Kenya

This landscape-scale study combines analysis of multitemporal satellite imagery spanning 30 years and information from field studies extending over 25 years to assess the extent and causes of land use and land cover change in the Loitokitok area, southeast Kajiado District, Kenya. Rain fed and irrigated agriculture, livestock herding, and wildlife and tourism have all experienced rapid change in their structure, extent, and interactions over the past 30 years in response to a variety of economic, cultural, political, institutional, and demographic processes. Land use patterns and processes are explored through a complementary application of interpretation of satellite imagery and case study analysis that explicitly addresses the local–national spatial scale over a time frame appropriate to the identification of fundamental causal processes. The results illustrate that this combination provides an effective basis for describing and explaining patterns of land use and land cover change and their root causes.     

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.     

From forest to farmland: pollen‐inferred land cover change across Europe using the pseudobiomization approach

Maps of continental‐scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time‐scales. User groups with an interest in past land cover include the climate modelling community, socio‐ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan‐European land cover change for the period 9000 bp to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 bp through reduction in broad‐leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan‐European scale moved outside the range of previous background variability from 4000 bp onwards. From 2200 bp land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 bp . Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover‐climate interactions, and the origins of the modern cultural landscape.     

The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States

Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km² of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700–2005, or 13.4% of carbon losses in non‐PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001–2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large‐scale disturbances that would release large amounts of carbon in PAs.     

The effects of land use and climate change on the carbon cycle of Europe over the past 500 years

The long residence time of carbon in forests and soils means that both the current state and future behavior of the terrestrial biosphere are influenced by past variability in climate and anthropogenic land use. Over the last half‐millennium, European terrestrial ecosystems were affected by the cool temperatures of the Little Ice Age, rising CO₂ concentrations, and human induced deforestation and land abandonment. To quantify the importance of these processes, we performed a series of simulations with the LPJ dynamic vegetation model driven by reconstructed climate, land use, and CO₂ concentrations. Although land use change was the major control on the carbon inventory of Europe over the last 500 years, the current state of the terrestrial biosphere is largely controlled by land use change during the past century. Between 1500 and 2000, climate variability led to temporary sequestration events of up to 3 Pg, whereas increasing atmospheric CO₂ concentrations during the 20th century led to an increase in carbon storage of up to 15 Pg. Anthropogenic land use caused between 25 Pg of carbon emissions and 5 Pg of uptake over the same time period, depending on the historical and spatial pattern of past land use and the timing of the reversal from deforestation to afforestation during the last two centuries. None of the currently existing anthropogenic land use change datasets adequately capture the timing of the forest transition in most European countries as recorded in historical observations. Despite considerable uncertainty, our scenarios indicate that with limited management, extant European forests have the potential to absorb between 5 and 12 Pg of carbon at the present day.     

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.     

Defining the importance of including transient ecosystem responses to simulate C‐cycle dynamics in a global change model

The ability of plant species to migrate is one of the critical issues in assessing accurately the future response of the terrestrial biosphere to climate change. This ability is confined by both natural and human‐induced changes in land cover. In this paper we present land‐cover and Carbon (C) cycle models designed to simulate the biospheric consequences of different types of land‐cover changes. These models, imbedded in the larger integrated assessment model IMAGE 2, were used to demonstrate the importance of considering spatial aspects for global C‐cycle modelling. A gradual‐migration, an unlimited‐migration and a no‐migration case were compared to show the range of possible consequences. Major differences between these cases were simulated for land‐cover patterns and the carbon budget. A large geographical variation in the biospheric response was also simulated. The strongest response was simulated in high‐latitude regions, especially for the migration cases in which land‐cover changes were permitted. In low‐latitudes regions the differences between the migration cases were smaller, mainly due to the effects of land‐use changes. The geographical variation among, and the different responses, the migration cases clearly demonstrate how essential it is to assess biospheric responses to climate change and land use simultaneously. Moreover, it also shows the urgent need for enhanced understanding of spatial and temporal dynamics of the biospheric responses.     

Net changes in regional woody vegetation cover and carbon storage in Texas Drylands, 1937–1999

Although local increases in woody plant cover have been documented in arid and semiarid ecosystems worldwide, there have been few long‐term, large‐scale analyses of changes in woody plant cover and aboveground carbon (C) stocks. We used historical aerial photography, contemporary Landsat satellite data, field observations, and image analysis techniques to assess spatially specific changes in woody vegetation cover and aboveground C stocks between 1937 and 1999 in a 400‐km² region of northern Texas, USA. Changes in land cover were then related to topo‐edaphic setting and historical land‐use practices. Mechanical or chemical brush management occurred over much of the region in the 1940–1950s. Rangelands not targeted for brush management experienced woody cover increases of up to 500% in 63 years. Areas managed with herbicides, mechanical treatments or fire exhibited a wide range of woody cover changes relative to 1937 (?75% to + 280%), depending on soil type and time since last management action. At the integrated regional scale, there was a net 30% increase in woody plant cover over the 63‐year period. Regional increases were greatest in riparian corridors (33%) and shallow clay uplands (26%) and least on upland clay loams (15%). Allometric relationships between canopy cover and aboveground biomass were used to estimate net aboveground C storage changes in upland (nonriparian) portions of regional landscapes. Carbon stocks increased from 380 g C m^?2 in 1937 to 500 g C m^?2 in 1999, a 32% net increase across the 400 km² region over the 63‐year period. These plant C storage change estimates are highly conservative in that they did not include the substantial increases in woody plant cover observed within riparian landscape elements. Results are discussed in terms of implications for ‘carbon accounting’ and the global C cycle.     

Spatial and temporal dynamics of methane emissions from agricultural sources in China

Agricultural activities contribute significantly to the global methane budget. Agricultural sources of methane are influenced by land‐use change, including changes in agricultural area, livestock keeping and agricultural management practices. A spatially explicit inventory of methane emissions from agriculture is made for China taking the interconnections between the different agricultural sources into account. The influence of land‐use change on methane emissions is studied by linking a dynamic land‐use change model with emission calculations. The land‐use change model calculates changes in rice area and livestock numbers for a base‐line scenario. Emissions are calculated for 1991 based on land‐use statistics and for 2010 based on simulated changes in land‐use patterns. Emissions from enteric fermentation and manure management are based on emission factors, while emissions from rice paddies involve the calculation of total organic carbon added to rice paddy soils and assume that a constant fraction is emitted as methane. Spatial patterns of emissions are presented for the different sources. For the land‐use scenario considered it is expected that total methane emissions from agricultural sources in China increase by 11% while the relative contribution of rice fields to the emission decreases. Emissions from manure management are expected to become more important. These results indicate that agencies should anticipate changes in source strengths as a consequence of land‐use changes when proposing mitigation strategies and future national greenhouse gas budgets.     

Introduction to the Special Section on Alternative Futures for Great Basin Ecosystems

Natural and anthropogenic processes are causing extensive and rapid ecological, social, and economic changes in arid and semiarid ecosystems worldwide. Nowhere are these changes more evident than in the Great Basin of the western United States, a region of 400,000 km² that largely is managed by federal agencies. Major drivers of ecosystems and human demographics of the Great Basin include human population growth, grazing by domestic livestock, extraction of minerals, development and production of energy, changes in fire and other disturbance regimes, and invasion of non-native annual plants. Exploration of alternative futures may increase the ability of management and policy to maximize the system's resistance and resilience to changes in climate, disturbance regimes, and anthropogenic perturbations. This special section examines the issues facing the Great Basin and then provides examples of approaches to predicting changes in land cover and avifaunal distributions under different management scenarios. Future sustainability of the Great Basin's natural and human systems requires strong, collaborative partnerships among research and management organizations that are capable of obtaining public support and financial resources and developing effective policies and institutional mechanisms.     

Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor

The spatial distribution of human activities in forest frontier regions is strongly influenced by transportation infrastructure. With the planned paving of 6000 km of highway in the Amazon Basin, agricultural frontier expansion will follow, triggering potentially large changes in the location and rate of deforestation. We developed a land‐cover change simulation model that is responsive to road paving and policy intervention scenarios for the BR‐163 highway in central Amazonia. This corridor links the cities of Cuiabá, in central Brazil, and Santarém, on the southern margin of the Amazon River. It connects important soybean production regions and burgeoning population centers in Mato Grosso State with the international port of Santarém, but 1000 km of this road are still not paved. It is within this context that the Brazilian government has prioritized the paving of this road to turn it into a major soybean exportation facility. The model assesses the impacts of this road paving within four scenarios: two population scenarios (high and moderate growth) and two policy intervention scenarios. In the ‘business‐as‐usual’ policy scenario, the responses of deforestation and land abandonment to road paving are estimated based on historical rates of Amazon regions that had a major road paved. In the ‘governance’ scenario, several plausible improvements in the enforcement of environmental regulations, support for sustainable land‐use systems, and local institutional capacity are invoked to modify the historical rates. Model inputs include data collected during expeditions and through participatory mapping exercises conducted with agents from four major frontier types along the road. The model has two components. A scenario‐generating submodel is coupled to a landscape dynamics simulator, ‘DINAMICA’, which spatially allocates the land‐cover transitions using a GIS database. The model was run for 30 years, divided into annual time steps. It predicted more than twice as much deforestation along the corridor in business‐as‐usual vs. governance scenarios. The model demonstrates how field data gathered along a 1000 km corridor can be used to develop plausible scenarios of future land‐cover change trajectories that are relevant to both global change science and the decision‐making process of governments and civil society in an important rainforest region.