Land-cover Change Projections Research Articles

Integrating aquatic species, assemblage, and habitat climate change vulnerabilities into a watershed-scale decision support framework

Climate change is increasingly recognized as a serious threat to ecological systems, particularly freshwater systems. As a result, climate adaptation planning is more common in natural resource management. Because conservation resources are limited, decision support tools can help managers prioritize actions. We created the Species and Habitat-based Ecological Decision Support tool (wtrSHEDS) for conservation managers by integrating two distinct indices: one biologically based on aquatic watershed-scale species assemblages and the other a habitat climate change vulnerability index. To do this, we evaluated 60 crayfish and fish species in West Virginia, USA, using the NatureServe Climate Change Vulnerability Index under an A1B emissions scenario. The species vulnerability assessment results indicated that most species we assessed are vulnerable to climate change. Four species of fish and two species of crayfish had extremely high vulnerability due to their dependence on a specific hydrological cycle, sensitivity to barriers, and reproductive dependence on a thermal niche. Aggregating species at the watershed scale (8-digit hydrological unit code [HUC]) using an adapted weighted sum indicated which assemblages were the most and least vulnerable to climate change. Secondly, we created a unique habitat vulnerability index using the established Northeast Association of Fish and Wildlife Agencies habitat vulnerability index and an index of land cover vulnerability from the Forecast Scenario model’s land cover change projections under the A1B emissions scenario to incorporate potential synergistic impacts of land use. Land cover projections were reclassified based on the assumption that developed land would have a higher potential to interact with climate change than forested lands synergistically. We combined the two habitat indices at the watershed scale (HUC 8) and performed a Hot Spot Analysis to 1) combine the assemblage and habitat vulnerability indices and 2) identify watersheds of conservation priority. This assessment methodology illustrates a means of identifying priority conservation areas in West Virginia that utilize pre-existing data, can be modified to suit management needs, and, therefore, one that managers across regions can readily apply to their system.

On the sustainability of paddy rice cultivation in the Paraíba do Sul river basin (Brazil) under a changing climate

Located in Southeast Brazil, the Paraíba do Sul River Basin is considered one of the most strategic in the country since it is the main source of fresh water for more than 14.3 million people. The population growth in recent decades, in combination with increased demand for water for industrial and agricultural activities, has generated concerns about how the combined effect of land uses and global climate change might affect water availability in the future. Once irrigation is one of the main water consumers, especially for paddy rice cultivation, in this study we used a crop simulation model to determine the water requirements of paddy rice under current and future climate conditions based on three different regionalized climate scenarios and for different land use and land cover change projections. In addition, we estimated water footprints for different irrigation and soil fertility strategies. Finally, we explored adaptation actions that can lead to more sustainable production. Projections indicate an increase in the productivity and efficiency of irrigated rice. Intermittent flooding proved to be an efficient alternative, rather than the traditional practice of continuous ponding. Most scenarios projected a gradual decrease in water footprint for rice cultivated using irrigation and soil fertility management. On the other hand, the water footprint under rainfed and non-optimum soil fertility resulted in higher water footprints. Due to changes in land use and land cover, mainly urban sprawl, the rice areas are expected to decrease in the future reducing the production in the region, which is expected to decrease by almost 10% in the period 2016–2035 and up to 38% in the period 2036–2055. This trend can be compensated by adopting sustainable practices in rice cultivation, such as rational soil fertility and water management, which can boost the current level of productivity by 50% and reduce water use by up to 15%.

Cross-sectoral projections of future land-cover change for the Upper Western Bug River catchment, Ukraine

Projections of future land-cover (LC) change are challenging because of the multitude of spatial and dynamic drivers involved, such as politics, economics, demographics, and the environment. This paper presents a combined qualitative and quantitative scenario approach for giving consistent projections of urban and rural land-cover change (LCC), considering both the demands of certain LC types, and their allocation. The approach has been implemented in the Upper Western Bug River catchment in Ukraine in the context of integrated water resource management. Special attention is paid to the identification of spatial and dynamic drivers of LCC, the scenario formulation and projection of the identified drivers, and the projections of alternative plausible LCC. The identification of spatial and dynamic drivers is based on the detection of retrospective LCC, statistical analysis of interrelations between LCC and drivers, and expert validation of transition rules. The scenario formulation and projection of the drivers involve storylines with inputs from expert interviews. The creation of future LC change projections followed four steps: suitability maps from retrospective LCC detection, expert validation, the future development of drivers, and the allocation of LCC. Results indicate demographic change and GDP development as dynamic drivers mainly influencing the LCC, as other studies have implied. Furthermore, there are spatial drivers influencing the local allocation such as the regional capital of Lviv, and they are shaped by, for example, environmental laws, distances to roads and settlements, slope, and soil fertility.

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 25years 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.

Effects of Climate and Land Cover on Hydrology in the Southeastern U.S.: Potential Impacts on Watershed Planning

AbstractThe hydrologic response to statistically downscaled general circulation model simulations of daily surface climate and land cover through 2099 was assessed for the Apalachicola‐Chattahoochee‐Flint River Basin located in the southeastern United States. Projections of climate, urbanization, vegetation, and surface‐depression storage capacity were used as inputs to the Precipitation‐Runoff Modeling System to simulate projected impacts on hydrologic response. Surface runoff substantially increased when land cover change was applied. However, once the surface depression storage was added to mitigate the land cover change and increases of surface runoff (due to urbanization), the groundwater flow component then increased. For hydrologic studies that include projections of land cover change (urbanization in particular), any analysis of runoff beyond the change in total runoff should include effects of stormwater management practices as these features affect flow timing and magnitude and may be useful in mitigating land cover change impacts on streamflow. Potential changes in water availability and how biota may respond to changes in flow regime in response to climate and land cover change may prove challenging for managers attempting to balance the needs of future development and the environment. However, these models are still useful for assessing the relative impacts of climate and land cover change and for evaluating tradeoffs when managing to mitigate different stressors.

Downscaling global land cover projections from an integrated assessment model for use in regional analyses: results and evaluation for the US from 2005 to 2095

Projections of land cover change generated from integrated assessment models (IAM) and other economic-based models can be applied for analyses of environmental impacts at sub-regional and landscape scales. For those IAM and economic models that project land cover change at the continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30 m) and at the global extent with relatively coarse spatial resolution (0.5°). We revised existing methods to downscale global land cover change projections for the US to 0.05° resolution using MODIS land cover data as the initial proxy for land class distribution. Land cover change realizations generated here represent a reference scenario and two emissions mitigation pathways (MPs) generated by the global change assessment model (GCAM). Future gridded land cover realizations are constructed for each MODIS plant functional type (PFT) from 2005 to 2095, commensurate with the community land model PFT land classes, and archived for public use. The GCAM land cover realizations provide spatially explicit estimates of potential shifts in croplands, grasslands, shrublands, and forest lands. Downscaling of the MPs indicate a net replacement of grassland by cropland in the western US and by forest in the eastern US. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions in respective areas in the US, suggesting it could provide relevant insights into the potential impacts of socio-economic and environmental drivers on future changes in land cover.

RCP 8.5—A scenario of comparatively high greenhouse gas emissions

This paper summarizes the main characteristics of the RCP8.5 scenario. The RCP8.5 combines assumptions about high population and relatively slow income growth with modest rates of technological change and energy intensity improvements, leading in the long term to high energy demand and GHG emissions in absence of climate change policies. Compared to the total set of Representative Concentration Pathways (RCPs), RCP8.5 thus corresponds to the pathway with the highest greenhouse gas emissions. Using the IIASA Integrated Assessment Framework and the MESSAGE model for the development of the RCP8.5, we focus in this paper on two important extensions compared to earlier scenarios: 1) the development of spatially explicit air pollution projections, and 2) enhancements in the land-use and land-cover change projections. In addition, we explore scenario variants that use RCP8.5 as a baseline, and assume different degrees of greenhouse gas mitigation policies to reduce radiative forcing. Based on our modeling framework, we find it technically possible to limit forcing from RCP8.5 to lower levels comparable to the other RCPs (2.6 to 6 W/m2). Our scenario analysis further indicates that climate policy-induced changes of global energy supply and demand may lead to significant co-benefits for other policy priorities, such as local air pollution.

Unravelling the structure of species extinction risk for predictive conservation science

Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process.

Quantifying processes of land-cover change by remote sensing: Resettlement and rapid land-cover changes in south-eastern Zambia

The objectives of this study are to quantify, based on remote sensing data, processes of land-cover change and to test a Markov-based model to generate short-term land-cover change projections in a region characterised by exceptionally high rates of change. The region of Lusitu, in the Southern Province of Zambia, has been a land-cover change 'hot spot' since the resettlement of 6000 people in the Lusitu area and the succession of several droughts. Land-cover changes were analysed on the basis of a temporal series of three multispectral SPOT images in three steps: (i) land-cover change detection was performed by combining the postclassification and image differencing techniques; (ii) the change detection results were examined in terms of proportion of land-cover classes, change trajectories and spatio-temporal patterns of change; (iii) the process of land-cover change was modelled by a Markov chain to predict land-cover distributions in the near future. The remote sensing approach allowed: (i) to quantify land-cover changes in terms of percentage of area affected and rates of change; (ii) to qualify the nature of changes in terms of impact on natural vegetation; (iii) to map the spatial pattern of land-cover change. 44% of the area has been affected by at least one change in land cover during the period 1986 to 1997. The average annual rate of land-cover change was 4.0%. Agricultural expansion was the dominant change process. Land-cover change trajectories highlighted the dynamic character of changes. The results obtained by applying a Markov chain for projecting future evolutions showed the continuing upward trend of bare soils and cultivated land, and the rapid downward trend of forests and other natural vegetation covers.