Future Land Cover Change Scenarios Research Articles

Carbon storage and sequestration in Southeast Asian urban clusters under future land cover change scenarios (2015–2050)

Land-use land-cover (LULC) changes are occurring rapidly in Southeast Asia (SEA), generally associated with population growth, economic development and competing demands for land. Land cover change is one of the vital factors affecting carbon dynamics and emissions. SEA is an important region to study urban-caused LULC emissions and the potential for nature-based solutions (NBS) and nature climate solutions (NCS), as it is home to nearly 15% of the world’s tropical forests and has some of the world’s fastest rates of urban growth. We present a fine-scale urban cluster level assessment for SEA of current (2015) and future (2050) scenarios for carbon sequestration service and climate mitigation potential. We identified 956 urban clusters distributed across 11 countries of SEA. Considering the urban expansion projected and decline in forests, this region could see a carbon loss of up to 0.11 Gigatonnes (Scenario SSP4 RCP 3.4). Comparing carbon change values to urban emissions, we found that the average offset value ranging from −2% (Scenario SSP1 RCP 2.6) to −21%. We also found that a few medium and large urban clusters could add to more than double the existing carbon emissions in 2050 in the SSP3 and SSP4 RCP 3.4 scenarios, while a minority of clusters could offset their emissions under SSP1. Our study confirms that NCS, and particularly reforestation, are in many cases able to offset the direct emissions from land cover conversion from SEA urban clusters. Hence, documenting the plausible LULC transitions and the associated impacts gains significance in the SEA region as the results can be useful for informing policy and sustainable land management.

Responses in ecosystem services to projected land cover changes on the Tibetan Plateau

The Tibetan Plateau (TP) is an important ecological security shelter in China, yet the environment here remains fragile and is difficult to restore. This ecosystem is likely to face additional threats in the future as it will be influenced by human activities and climate change. Although a number of investigations regarding land cover changes on the TP as well as resultant influences on ecosystem services have been performed over recent decades, reliable evaluation of future land cover change scenarios and their potential ecological impacts remain absent. Thus, to remedy this, we developed a method that can spatially and explicitly evaluate TP ecosystem services responses to future land cover changes. Simulation results for TP land cover changes between 2010 and 2030 reveal that under a business-as-usual scenario, grassland area will increase by 1.04%, wetland area will increase by 6.01%, and forested area will increase by 0.07%. In contrast, under an ecological protection scenario, forested and wetland areas will increase by 1.06% and 28.87% respectively, while grassland area will increase by 7.09%. We then calculated the responses of ecosystem services over the period same period; results show that under a business-as-usual scenario, land cover changes on the TP would lead to a net primary productively (NPP) increase of 0.004%, a 0.011% decrease in soil conservation services, and a 0.023% decrease in water yield. In contrast, under an ecological protection scenario, land cover changes on the TP would lead to a NPP increase of 0.006%, a 0.007% decrease in soil conservation services, and a 0.007% decrease in water yield. Ecosystem service values given an ecological protection scenario will be slightly higher than those given a business-as-usual scenario.

Future land cover change scenarios in South African grasslands – implications of altered biophysical drivers on land management

Future land cover changes may result in adjustments to biophysical drivers impacting on net ecosystem carbon exchange (NEE), catchment water use through evapotranspiration (ET), and the surface energy balance through a change in albedo. The Land Change Modeller (Idrisi Terrset 18.08) and land cover for 2000 and 2014 are used to create a future scenario of land cover for two catchment with different land management systems in the Eastern Cape Province for the year 2030. In the S50E catchment, a dualistic farming system, the trend shows that grasslands represented 57% of the total catchment area in 2014 decreasing to 52% by 2030 with losses likely to favour a gain in woody plants and cultivated land. In T35B, a commercial system, persistence of grasslands is modelled with approximately 80% coverage in both years, representing a more stable system. Finally, for S50E, NEE and ET will increase under this land cover change scenario leading to increased carbon sequestration but less water availability and corresponding surface temperature increases. This implies that rehabilitation and land management initiatives should be targeted in catchments under a dualistic farming system, rather than those which are predominantly commercial systems.

Historical and future land-cover changes in the Upper Ganges basin of India

The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multi-temporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (–9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.

Development of Future Land Cover Change Scenarios in the Metropolitan Fringe, Oregon, U.S., with Stakeholder Involvement

We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from the stakeholder storyline to modify it. These identified variables related to our study area’s land use regulation system as the major driver in the placement of new urban growth on the landscape; and the accommodation of new population as the determinant of its growth rate. The outcome was a series of three scenario maps depicting a gradient of increased urbanization. The effort attempted to create a simple and transparent modeling framework that is easy to communicate. The incorporation of the regulatory context and rules and place-specific modeling for denser urban and sparse rural areas provide new insights of future land conversions. This relatively rapid mapping process provides useful information for spatial planning and projects for where and how much urban land will be present by the year 2050.

The relative impact of regional scale land cover change and increasing CO2 over China

A series of 17-yr equilibrium simulations using the NCAR CCM3 (T42 resolution) were performed to investigate the regional scale impacts of land cover change and increasing CO2 over China. Simulations with natural and current land cover at CO2 levels of 280, 355, 430, and 505 ppmv were conducted. Results show statistically significant changes in major climate fields (e.g. temperature and surface wind speed) on a 15-yr average following land cover change. We also found increases in the maximum temperature and in the diurnal temperature range due to land cover change. Increases in CO2 affect both the maximum and minimum temperature so that changes in the diurnal range are small. Both land cover change and CO2 change also impact the frequency distribution of precipitation with increasing CO2 tending to lead to more intense precipitation and land cover change leading to less intense precipitation—indeed, the impact of land cover change typically had the opposite effect versus the impacts of CO2. Our results provide support for the inclusion of future land cover change scenarios in long-term transitory climate modelling experiments of the 21st Century. Our results also support the inclusion of land surface models that can represent future land cover changes resulting from an ecological response to natural climate variability or increasing CO2. Overall, we show that land cover change can have a significant impact on the regional scale climate of China, and that regionally, this impact is of a similar magnitude to increases in CO2 of up to about 430 ppmv. This means that that the impact of land cover change must be accounted for in detection and attribution studies over China.