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.     

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.     

Old‐growth forests buffer climate‐sensitive bird populations from warming

Aim

Habitat loss and climate change constitute two of the greatest threats to biodiversity worldwide, and theory predicts that these factors may act synergistically to affect population trajectories. Recent evidence indicates that structurally complex old‐growth forest can be cooler than other forest types during spring and summer months, thereby offering potential to buffer populations from negative effects of warming. Old growth may also have higher food and nest‐site availability for certain species, which could have disproportionate fitness benefits as species approach their thermal limits.

Location

Pacific Northwestern United States.

Methods

We predicted that negative effects of climate change on 30‐year population trends of old‐growth‐associated birds should be dampened in landscapes with high proportions of old‐growth forest. We modelled population trends from Breeding Bird Survey data for 13 species as a function of temperature change and proportion old‐growth forest.

Results

We found a significant negative effect of summer warming on only two species. However, in both of these species, this relationship between warming and population decline was not only reduced but reversed, in old‐growth‐dominated landscapes. Across all 13 species, evidence for a buffering effect of old‐growth forest increased with the degree to which species were negatively influenced by summer warming.

Main conclusions

These findings suggest that old‐growth forests may buffer the negative effects of climate change for those species that are most sensitive to temperature increases. Our study highlights a mechanism whereby management strategies to curb degradation and loss of old‐growth forests—in addition to protecting habitat—could enhance biodiversity persistence in the face of climate warming.

     

Downscaling land‐use data to provide global 30″ estimates of five land‐use classes

Land‐use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land‐use mapping. Assessments of land‐use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land‐use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land‐use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km²) estimates of five land‐use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio‐realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine‐grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land‐use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio‐realms produced global fine‐grained layers from the 2005 time step of the Land‐use Harmonization dataset. Coarse‐scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R²: 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land‐use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R² improvement of 0.12 compared with the Land‐use Harmonization data. The downscaling method presented here produced the first global land‐use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land‐use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse‐resolution data for other environmental variables.     

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

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Woody plant encroachment reduces species richness of herb‐rich woodlands in southern Australia

Abstract Woody plants have been increasing in many woodland and savanna ecosystems owing to land use changes in recent decades. We examined the effects of encroachment by the indigenous shrub Leptospermum scoparium (Myrtaceae) on herb‐rich Eucalyptus camaldulensis woodlands in southern Australia. Species richness and compositional patterns were examined under the canopy of L. scoparium and in surrounding open areas to determine the species most susceptible to structural changes. Richness was significantly lower in areas of moderate to high L. scoparium cover (>15%), suggesting that a threshold shrub cover caused major change in this ecosystem. Shrubs were associated with a significant reduction in above‐ground biomass of the ground‐layer flora and a significant shift in community composition. The few species that were positively associated with high L. scoparium cover were also common in the woodland flora; no new species were recorded under the shrub canopy. Important environmental changes associated with L. scoparium cover were decreased light availability and increased litter cover, which were likely a consequence of encroachment. Leptospermum scoparium cover was also associated with greater surface soil moisture, which may be a consequence of increased shading under the shrub canopy or indicate favourable soil conditions for L. scoparium establishment. Reductions in species richness and abundance of the germinable seed bank were found in soil samples taken from under L. scoparium. With ongoing recruitment of L. scoparium and consequent increases in shrub cover, ground‐layer diversity in these species‐rich woodlands should continue to decline over time.     

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.     

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.     

Landslides and Their Contribution to Land‐cover Change in the Mountains of Mexico and Central America1

Landsliding is a natural process influencing montane ecosystems, particularly in areas with elevated rainfall and seismic activity. Yet, to date, little effort has been made to quantify the contribution of this process to land‐cover change. Focusing on the mountains of Mexico and Central America (M‐CA), we estimated the contribution of landsliding to land‐cover change at two scales. At the scale of M‐CA, we classified the terrain into major landforms and entered in a GIS historical data on earthquake‐ and rainfall‐triggered landslides. At the scale of the Sierra de Las Minas of Guatemala, we investigated Landsat TM data to map rainfall‐triggered landslides. During the past 110 yr, >136,200 ha of land in the mountains of M‐CA have been affected by landslides, which translates into disturbance rates exceeding 0.317 percent/century. In Sierra de Las Minas, rainfall associated with hurricane Mitch affected 1765 ha of forest, or equivalently, landslides triggered by storms of this magnitude transformed between 0.196 (return time of 500 yr) and 1.290 (return time of 75 yr) percent of forest/century. Although landsliding results in smaller rates of land‐cover change than deforestation, we hypothesize that it has a stronger impact on ecosystems, both in qualitative and quantitative terms, given its influence on vegetation and soil. Moreover, interactions between landsliding and deforestation may be altering the expression of this complex process such that the few protected areas in the mountains of M‐CA may represent the only possibility for the conservation of this process.     

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.     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

Large‐scale degradation of Amazonian freshwater ecosystems

Hydrological connectivity regulates the structure and function of Amazonian freshwater ecosystems and the provisioning of services that sustain local populations. This connectivity is increasingly being disrupted by the construction of dams, mining, land‐cover changes, and global climate change. This review analyzes these drivers of degradation, evaluates their impacts on hydrological connectivity, and identifies policy deficiencies that hinder freshwater ecosystem protection. There are 154 large hydroelectric dams in operation today, and 21 dams under construction. The current trajectory of dam construction will leave only three free‐flowing tributaries in the next few decades if all 277 planned dams are completed. Land‐cover changes driven by mining, dam and road construction, agriculture and cattle ranching have already affected ~20% of the Basin and up to ~50% of riparian forests in some regions. Global climate change will likely exacerbate these impacts by creating warmer and dryer conditions, with less predictable rainfall and more extreme events (e.g., droughts and floods). The resulting hydrological alterations are rapidly degrading freshwater ecosystems, both independently and via complex feedbacks and synergistic interactions. The ecosystem impacts include biodiversity loss, warmer stream temperatures, stronger and more frequent floodplain fires, and changes to biogeochemical cycles, transport of organic and inorganic materials, and freshwater community structure and function. The impacts also include reductions in water quality, fish yields, and availability of water for navigation, power generation, and human use. This degradation of Amazonian freshwater ecosystems cannot be curbed presently because existing policies are inconsistent across the Basin, ignore cumulative effects, and overlook the hydrological connectivity of freshwater ecosystems. Maintaining the integrity of these freshwater ecosystems requires a basinwide research and policy framework to understand and manage hydrological connectivity across multiple spatial scales and jurisdictional boundaries.     

Continental‐scale determinants of population trends in European amphibians and reptiles

The continuous decline of biodiversity is determined by the complex and joint effects of multiple environmental drivers. Still, a large part of past global change studies reporting and explaining biodiversity trends have focused on a single driver. Therefore, we are often unable to attribute biodiversity changes to different drivers, since a multivariable design is required to disentangle joint effects and interactions. In this work, we used a meta‐regression within a Bayesian framework to analyze 843 time series of population abundance from 17 European amphibian and reptile species over the last 45 years. We investigated the relative effects of climate change, alien species, habitat availability, and habitat change in driving trends of population abundance over time, and evaluated how the importance of these factors differs across species. A large number of populations (54%) declined, but differences between species were strong, with some species showing positive trends. Populations declined more often in areas with a high number of alien species, and in areas where climate change has caused loss of suitability. Habitat features showed small variation over the last 25 years, with an average loss of suitable habitat of 0.1%/year per population. Still, a strong interaction between habitat availability and the richness of alien species indicated that the negative impact of alien species was particularly strong for populations living in landscapes with less suitable habitat. Furthermore, when excluding the two commonest species, habitat loss was the main correlate of negative population trends for the remaining species. By analyzing trends for multiple species across a broad spatial scale, we identify alien species, climate change, and habitat changes as the major drivers of European amphibian and reptile decline.     

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.