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.     

Large‐scale impact of climate change vs. land‐use change on future biome shifts in Latin America

Climate change and land‐use change are two major drivers of biome shifts causing habitat and biodiversity loss. What is missing is a continental‐scale future projection of the estimated relative impacts of both drivers on biome shifts over the course of this century. Here, we provide such a projection for the biodiverse region of Latin America under four socio‐economic development scenarios. We find that across all scenarios 5–6% of the total area will undergo biome shifts that can be attributed to climate change until 2099. The relative impact of climate change on biome shifts may overtake land‐use change even under an optimistic climate scenario, if land‐use expansion is halted by the mid‐century. We suggest that constraining land‐use change and preserving the remaining natural vegetation early during this century creates opportunities to mitigate climate‐change impacts during the second half of this century. Our results may guide the evaluation of socio‐economic scenarios in terms of their potential for biome conservation under global change.     

The effects of climate change and land‐use change on demographic rates and population viability

Understanding the processes that lead to species extinctions is vital for lessening pressures on biodiversity. While species diversity, presence and abundance are most commonly used to measure the effects of human pressures, demographic responses give a more proximal indication of how pressures affect population viability and contribute to extinction risk. We reviewed how demographic rates are affected by the major anthropogenic pressures, changed landscape condition caused by human land use, and climate change. We synthesized the results of 147 empirical studies to compare the relative effect size of climate and landscape condition on birth, death, immigration and emigration rates in plant and animal populations. While changed landscape condition is recognized as the major driver of species declines and losses worldwide, we found that, on average, climate variables had equally strong effects on demographic rates in plant and animal populations. This is significant given that the pressures of climate change will continue to intensify in coming decades. The effects of climate change on some populations may be underestimated because changes in climate conditions during critical windows of species life cycles may have disproportionate effects on demographic rates. The combined pressures of land‐use change and climate change may result in species declines and extinctions occurring faster than otherwise predicted, particularly if their effects are multiplicative.     

Population trends influence species ability to track climate change

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species’ climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche tracking imply shifts in species’ realized climate niches. We argue that quantifying climate niche shifts and analyzing them for a suite of species reveal general patterns of niche shifts and the factors affecting species’ ability to track climate change. We analyzed changes in realized climate niche between 1984 and 2012 for 46 species of North American birds in relation to population trends in an effort to determine whether species differ in the ability to track climate change and whether differences in niche tracking are related to population trends. We found that increasingly abundant species tended to show greater levels of niche expansion (climate space occupied in 2012 but not in 1980) compared to declining species. Declining species had significantly greater niche unfilling (climate space occupied in 1980 but not in 2012) compared to increasing species due to an inability to colonize new sites beyond their range peripheries after climate had changed at sites of occurrence. Increasing species, conversely, were better able to colonize new sites and therefore showed very little niche unfilling. Our results indicate that species with increasing trends are better able to geographically track climate change compared to declining species, which exhibited lags relative to changes in climate. These findings have important implications for understanding past changes in distribution, as well as modeling dynamic species distributions in the face of climate change.     

Effect of historical land‐use and climate change on tree‐climate relationships in the upper Midwestern United States

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree‐climate relationships are poorly understood. We show that tree‐climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land‐use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land‐use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land‐use interactions are compounding, in which historical land‐use reinforces shifts in species‐climate relationships toward wetter distributions, or confounding, in which land‐use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary‐based models of species distributions may underestimate species resilience to climate change.     

Predicting the potential distribution of a riparian invasive plant: the effects of changing climate,flood regimes and land‐use patterns

Climate change is likely to affect plants in multiple ways, but predicting the consequences for habitat suitability requires a process‐based understanding of the interactions. This is at odds with existing approaches that are mostly phenomenological and largely restricted to predicting the effects of changing temperature and rainfall on species distributions at a coarse spatial scale. We examine the multiple effects of climate change, including predicting the effects of altered flood regimes and land‐use change, on the potential distribution of the invasive riparian species lippia (Phyla canescens) across a 26 000 km² catchment in eastern Australia. We determined habitat suitability for lippia by combining process‐understanding of experts and an eco‐physiological bioclimatic model within a Bayesian belief network. The bioclimatic model predicted substantial changes in habitat suitability by 2070 under both a wetter (Echam Mark 3) and drier (Hadley Centre Mark 2) climate change scenario, but only the more likely drier scenario reduced suitability in our test region. The area suitable for lippia was predicted to increase at least threefold with increased flooding under a wet climate scenario, although this would be partially negated by land‐use change to cultivation. The region would become unsuitable to lippia with reduced flooding under a drier scenario irrespective of land‐use changes, although existing populations would persist if grazing persisted. Independent field validation verified model structure and parameterization, and therefore the opinion of experts, but identified site‐scale deficiencies in the available environmental data layers. Model predictions suggest that adaptation options for managing lippia will be greatly reduced under a drying scenario, but identify potential restoration opportunities under either scenario. This work highlights the value of predictive models that incorporate process‐understanding at sufficiently fine spatial resolution to capture the important processes underpinning habitat suitability.     

A socio‐ecological model for predicting impacts of land‐use and climate change on regional plant diversity in the Austrian Alps

Climate and land‐use change jointly affect the future of biodiversity. Yet, biodiversity scenarios have so far concentrated on climatic effects because forecasts of land use are rarely available at appropriate spatial and thematic scales. Agent‐based models (ABMs) represent a potentially powerful but little explored tool for establishing thematically and spatially fine‐grained land‐use scenarios. Here, we use an ABM parameterized for 1,329 agents, mostly farmers, in a Central European model region, and simulate the changes to land‐use patterns resulting from their response to three scenarios of changing socio‐economic conditions and three scenarios of climate change until the mid of the century. Subsequently, we use species distribution models to, first, analyse relationships between the realized niches of 832 plant species and climatic gradients or land‐use types, respectively, and, second, to project consequent changes in potential regional ranges of these species as triggered by changes in both the altered land‐use patterns and the changing climate. We find that both drivers determine the realized niches of the studied plants, with land use having a stronger effect than any single climatic variable in the model. Nevertheless, the plants' future distributions appear much more responsive to climate than to land‐use changes because alternative future socio‐economic backgrounds have only modest impact on land‐use decisions in the model region. However, relative effects of climate and land‐use changes on biodiversity may differ drastically in other regions, especially where landscapes are still dominated by natural or semi‐natural habitat. We conclude that agent‐based modelling of land use is able to provide scenarios at scales relevant to individual species distribution and suggest that coupling ABMs with models of species' range change should be intensified to provide more realistic biodiversity forecasts.     

Land use and climate influences on waterbirds in the Prairie Potholes

Aim We examined the influences of regional climate and land‐use variables on mallard (Anas platyrhynchos), blue‐winged teal (Anas discors), ruddy duck (Oxyura jamaicensis) and pied‐billed grebe (Podilymbus podiceps) abundances to inform conservation planning in the Prairie Pothole Region of the United States. Location The US portion of Bird Conservation Region 11 (US‐BCR11, the Prairie Potholes), which encompasses six states within the United States: Montana, North Dakota, South Dakota, Nebraska, Minnesota and Iowa. Methods We used data from the North American Breeding Bird Survey (NABBS), the National Land Cover Data Set, and the National Climatic Data Center to model the effects of environmental variables on waterbird abundance. We evaluated land‐use covariates at three logarithmically related spatial scales (1000, 10,000 and 100,000 ha), and constructed hierarchical spatial count models a priori using information from published habitat associations. Model fitting was performed using a hierarchical modelling approach within a Bayesian framework. Results Models with the same variables expressed at different scales were often in the best model subset, indicating that the influence of spatial scale was small. Both land‐use and climate variables contributed strongly to predicting waterbird abundance in US‐BCR11. The strongest positive influences on waterbird abundance were the percentage of wetland area across all three spatial scales, herbaceous vegetation and precipitation variables. Other variables that we included in our models did not appear to influence waterbirds in this study. Main conclusions Understanding the relationships of waterbird abundance to climate and land use may allow us to make predictions of future distribution and abundance as environmental factors change. Additionally, results from this study can suggest locations where conservation and management efforts should be focused.     

Weighing the relative potential impacts of climate change and land‐use change on an endangered bird

Climate change and land‐use change are projected to be the two greatest drivers of biodiversity loss over the coming century. Land‐use change has resulted in extensive habitat loss for many species. Likewise, climate change has affected many species resulting in range shifts, changes in phenology, and altered interactions. We used a spatially explicit, individual‐based model to explore the effects of land‐use change and climate change on a population of the endangered Red‐cockaded Woodpecker (RCW; Picoides borealis). We modeled the effects of land‐use change using multiple scenarios representing different spatial arrangements of new training areas for troops across Fort Benning. We used projected climate‐driven changes in habitat and changes in reproductive output to explore the potential effects of climate change. We summarized potential changes in habitat based on the output of the dynamic vegetation model LPJ‐GUESS, run for multiple climate change scenarios through the year 2100. We projected potential changes in reproduction based on an empirical relationship between spring precipitation and the mean number of successful fledglings produced per nest attempt. As modeled in our study, climate change had virtually no effect on the RCW population. Conversely, simulated effects of land‐use change resulted in the loss of up to 28 breeding pairs by 2100. However, the simulated impacts of development depended on where the development occurred and could be completely avoided if the new training areas were placed in poor‐quality habitat. Our results demonstrate the flexibility inherent in many systems that allows seemingly incompatible human land uses, such as development, and conservation actions to exist side by side.     

Land‐use and climate change effects on population size and extinction risk of Andean plants

Andean plant species are predicted to shift their distributions, or ‘migrate,’ upslope in response to future warming. The impacts of these shifts on species' population sizes and their abilities to persist in the face of climate change will depend on many factors including the distribution of individuals within species' ranges, the ability of species to migrate and remain at equilibrium with climate, and patterns of human land‐use. Human land‐use may be especially important in the Andes where anthropogenic activities above tree line may create a hard barrier to upward migrations, imperiling high‐elevation Andean biodiversity. In order to better understand how climate change may impact the Andean biodiversity hotspot, we predict the distributional responses of hundreds of plant species to changes in temperature incorporating population density distributions, migration rates, and patterns of human land‐use. We show that plant species from high Andean forests may increase their population sizes if able to migrate onto the expansive land areas above current tree line. However, if the pace of climate change exceeds species' abilities to migrate, all species will experience large population losses and consequently may face high risk of extinction. Using intermediate migration rates consistent with those observed for the region, most species are still predicted to experience population declines. Under a business‐as‐usual land‐use scenario, we find that all species will experience large population losses regardless of migration rate. The effect of human land‐use is most pronounced for high‐elevation species that switch from predicted increases in population sizes to predicted decreases. The overriding influence of land‐use on the predicted responses of Andean species to climate change can be viewed as encouraging since there is still time to initiate conservation programs that limit disturbances and/or facilitate the upward migration and persistence of Andean plant species.     

Predicted declines in suitable habitat for greater one‐horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios

Rapidly changing climate is likely to modify the spatial distribution of both flora and fauna. Land use change continues to alter the availability and quality of habitat and further intensifies the effects of climate change on wildlife species. We used an ensemble modeling approach to predict changes in habitat suitability for an iconic wildlife species, greater one‐horned rhinoceros due to the combined effects of climate and land use changes. We compiled an extensive database on current rhinoceros distribution and selected nine ecologically meaningful environmental variables for developing ensemble models of habitat suitability using ten different species distribution modeling algorithms in the BIOMOD2 R package; and we did this under current climatic conditions and then projected them onto two possible climate change scenarios (SSP1‐2.6 and SSP5‐8.5) and two different time frames (2050 and 2070). Out of ten algorithms, random forest performed the best, and five environmental variables—distance from grasslands, mean temperature of driest quarter, distance from wetlands, annual precipitation, and slope, contributed the most in the model. The ensemble model estimated the current suitable habitat of rhinoceros to be 2610 km², about 1.77% of the total area of Nepal. The future habitat suitability under the lowest and highest emission scenarios was estimated to be: (1) 2325 and 1904 km² in 2050; and (2) 2287 and 1686 km² in 2070, respectively. Our results suggest that over one‐third of the current rhinoceros habitat would become unsuitable within a period of 50 years, with the predicted declines being influenced to a greater degree by climatic changes than land use changes. We have recommended several measures to moderate these impacts, including relocation of the proposed Nijgad International Airport given that a considerable portion of potential rhinoceros habitat will be lost if the airport is constructed on the currently proposed site.     

Integrating broad‐scale data to assess demographic and climatic contributions to population change in a declining songbird

Climate variation and trends affect species distribution and abundance across large spatial extents. However, most studies that predict species response to climate are implemented at small spatial scales or are based on occurrence‐environment relationships that lack mechanistic detail. Here, we develop an integrated population model (IPM) for multi‐site count and capture‐recapture data for a declining migratory songbird, Wilson's warbler (Cardellina pusilla), in three genetically distinct breeding populations in western North America. We include climate covariates of vital rates, including spring temperatures on the breeding grounds, drought on the wintering range in northwest Mexico, and wind conditions during spring migration. Spring temperatures were positively related to productivity in Sierra Nevada and Pacific Northwest genetic groups, and annual changes in productivity were important predictors of changes in growth rate in these populations. Drought condition on the wintering grounds was a strong predictor of adult survival for coastal California and Sierra Nevada populations; however, adult survival played a relatively minor role in explaining annual variation in population change. A latent parameter representing a mixture of first‐year survival and immigration was the largest contributor to variation in population change; however, this parameter was estimated imprecisely, and its importance likely reflects, in part, differences in spatio‐temporal distribution of samples between count and capture‐recapture data sets. Our modeling approach represents a novel and flexible framework for linking broad‐scale multi‐site monitoring data sets. Our results highlight both the potential of the approach for extension to additional species and systems, as well as needs for additional data and/or model development.     

Long‐term and widespread changes in agricultural practices influence ring‐necked pheasant abundance in California

Declines in bird populations in agricultural regions of North America and Europe have been attributed to agricultural industrialization, increases in use of agrochemical application, and increased predation related to habitat modification. Based on count data compiled from Breeding Bird Survey (BBS) from 1974 to 2012, Christmas Bird Count (CBC) collected from 1914 to 2013, and hunter data from Annual Game Take Survey (AGTS) for years 1948–2010, ring‐necked pheasants (Phasianus colchicus) in California have experienced substantial declines in agricultural environments. Using a modeling approach that integrates all three forms of survey data into a joint response abundance index, we found pheasant abundance was related to the amount of harvested and unharvested crop land, types of crops produced, amount of total pesticide applied, minimum temperature, precipitation, and numbers of avian competitors and predators. Specifically, major changes in agricultural practices over the last three decades were associated with declines in pheasant numbers and likely reflected widespread loss of habitat. For example, increases in cropland were associated with increased pheasant abundance during early years of study but this effect decreased through time, such that no association in recent years was evidenced. A post hoc analysis revealed that crops beneficial to pheasant abundance (e.g., barley) have declined substantially in recent decades and were replaced by less advantageous crops (e.g., nut trees). An additional analysis using a restricted data set (1990–2013) indicated recent negative impacts on pheasant numbers associated with land use practices were also associated with relatively high levels of pesticide application. Our results may provide valuable information for management policies aimed at reducing widespread declines in pheasant populations in California and may be applicable to other avian species within agricultural settings. Furthermore, this general analytical approach is not limited to pheasants and could be applied to other taxa for which multiple survey data sources exist.     

Global environmental change effects on ecosystems: the importance of land‐use legacies

One of the major challenges in ecology is to predict how multiple global environmental changes will affect future ecosystem patterns (e.g. plant community composition) and processes (e.g. nutrient cycling). Here, we highlight arguments for the necessary inclusion of land‐use legacies in this endeavour. Alterations in resources and conditions engendered by previous land use, together with influences on plant community processes such as dispersal, selection, drift and speciation, have steered communities and ecosystem functions onto trajectories of change. These trajectories may be modulated by contemporary environmental changes such as climate warming and nitrogen deposition. We performed a literature review which suggests that these potential interactions have rarely been investigated. This crucial oversight is potentially due to an assumption that knowledge of the contemporary state allows accurate projection into the future. Lessons from other complex dynamic systems, and the recent recognition of the importance of previous conditions in explaining contemporary and future ecosystem properties, demand the testing of this assumption. Vegetation resurvey databases across gradients of land use and environmental change, complemented by rigorous experiments, offer a means to test for interactions between land‐use legacies and multiple environmental changes. Implementing these tests in the context of a trait‐based framework will allow biologists to synthesize compositional and functional ecosystem responses. This will further our understanding of the importance of land‐use legacies in determining future ecosystem properties, and soundly inform conservation and restoration management actions.     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

Land suitability for energy crops under scenarios of climate change and land‐use

Bioenergy is expected to play a critical role in climate change mitigation. Most integrated assessment models assume an expansion of agricultural land for cultivation of energy crops. This study examines the suitability of land for growing a range of energy crops on areas that are not required for food production, accounting for climate change impacts and conservation requirements. A global fuzzy logic model is employed to ascertain the suitable cropping areas for a number of sugar, starch and oil crops, energy grasses and short rotation tree species that could be grown specifically for energy. Two climate change scenarios are modelled (RCP2.6 and RCP8.5), along with two scenarios representing the land which cannot be used for energy crops due to forest and biodiversity conservation, food agriculture and urban areas. Results indicate that 40% of the global area currently suitable for energy crops overlaps with food land and 31% overlaps with forested or protected areas, highlighting hotspots of potential land competition risks. Approximately 18.8 million km² is suitable for energy crops, to some degree, and does not overlap with protected, forested, urban or food agricultural land. Under the climate change scenario RCP8.5, this increases to 19.6 million km² by the end of the century. Broadly, climate change is projected to decrease suitable areas in southern regions and increase them in northern regions, most notably for grass crops in Russia and China, indicating that potential production areas will shift northwards which could potentially affect domestic use and trade of biomass significantly. The majority of the land which becomes suitable is in current grasslands and is just marginally or moderately suitable. This study therefore highlights the vital importance of further studies examining the carbon and ecosystem balance of this potential land‐use change, energy crop yields in sub‐optimal soil and climatic conditions and potential impacts on livelihoods.     

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.