Global projections of future urban land expansion under shared socioeconomic pathways

Chen, Guangzhao; Li, Xia; Liu, Xiaoping; Chen, Yimin; Liang, Xun; Leng, Jiye; Xu, Xiaocong; Liao, Weilin; Qiu, Yuean; Wu, Qianlian; Huang, Kangning

doi:10.1038/s41467-020-14386-x

Cited by 489 publications

(303 citation statements)

References 64 publications

(77 reference statements)

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“…Moreover, it can realize large-scale simulation. Therefore, it is widely used in regional, national and even global land use simulations [57][58][59].…”

Section: Land Use Change and Climate Change Scenariosmentioning

confidence: 99%

Simulating the Impact of Future Climate Change and Ecological Restoration on Trade-Offs and Synergies of Ecosystem Services in Two Ecological Shelters and Three Belts in China

Wang

Qiao

et al. 2020

IJERPH

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Development of suitable ecological protection and restoration policies for sustainable management needs to assess the potential impacts of future land use and climate change on ecosystem services. The two ecological shelters and three belts (TSTB) are significant for improving ecosystem services and ensuring China’s and global ecological security. In this study, we simulated land use in 2050 and estimated the spatial distribution pattern of net primary productivity (NPP), water yield, and soil conservation from 2010 to 2050 under future climate change. The results showed that water yield, NPP, and soil conservation exhibited a spatial pattern of decreasing from southeast to northwest, while in terms of the temporal pattern, water yield and NPP increased, but soil conservation decreased. Water yield was mainly influenced by precipitation, NPP was affected by temperature and implementation of ecological restoration, and soil conservation was controlled by precipitation and slope. There was a strong spatial heterogeneity between trade-offs and synergies. In terms of the temporal, with the combination of climate change and ecological restoration, there was a synergistic relationship between water yield and NPP. However, the relationships between water yield and soil conservation, and between NPP and soil conservation were characterized by trade-offs. In the process of ecological construction, it is necessary to consider the differences between overall and local trade-offs and synergies, as well as formulate sustainable ecological management policies according to local conditions. Understanding the response of ecosystem services to future climate change and land use policies can help address the challenges posed by climate change and achieve sustainable management of natural resources.

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“…Moreover, it can realize large-scale simulation. Therefore, it is widely used in regional, national and even global land use simulations [57][58][59].…”

Section: Land Use Change and Climate Change Scenariosmentioning

confidence: 99%

Simulating the Impact of Future Climate Change and Ecological Restoration on Trade-Offs and Synergies of Ecosystem Services in Two Ecological Shelters and Three Belts in China

Wang

Qiao

et al. 2020

IJERPH

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“…Water shortage in rivers, lakes, and reservoirs, a result of both changed water availability and increased water demand, results in freshwater scarcity and hampers electricity generation [11][12][13]. And the uncontrolled increasing urbanization destroys adjacent ecosystems, impairs biodiversity, and often affects agricultural lands that are needed to support a growing population [14,15]. In the 2030 Agenda for Sustainable Development, the United Nations (UN) have therefore formulated the Sustainable Development Goals (SDGs) to foster social and economic development in the future while at the same time using natural resources sustainably and mitigate climate change [16].…”

Section: The Need For Forecastsmentioning

confidence: 99%

Forecasting Spatio-Temporal Dynamics on the Land Surface Using Earth Observation Data—A Review

Koehler

Kuenzer

2020

Remote Sensing

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Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.

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“…Along the rural-urban gradient the number and the density of human inhabitants increases (Montalvo et al, 2019). The urbanization rate is associated with an increase in road density (Shi et al, 2019), area with artificial cover and paved surfaces (Murata & Kawai, 2018;Chen et al, 2020), and air and soil pollution (Duh et al, 2008;Jia et al, 2018). Urban forests are constantly exposed to elevated temperatures, carbon dioxide, nitrogen deposition and ozone (Carreiro & Tripler, 2005).…”

Section: Introductionmentioning

confidence: 99%

Applying plant disturbance indicators to reveal the hemeroby of soil macrofauna species

et al. 2020

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Hemeroby is an integrated indicator for measuring human impacts on environmental systems. Hemeroby has a complex nature and a variety of mechanisms to affect ecosystems. Hemeroby is often used to assess disturbances in different vegetation types but this concept has seldom been evaluated for animals. The role of the hemeroby gradient in structuring the soil macrofauna community was investigated. The experimental polygon was located in Botanical Garden of the Oles Honchar Dnipro National University (Dnipro City, Ukraine). There were 20 sites within the polygon. On each of them at 105 points samples of soil macrofauna were taken, soil penetration resistance, electrical conductivity of soil, depth of litter, height of grasses were measured. Within each site, a description of the vegetation cover was made. Based on the description of the vegetation, an indication of the level of ecosystem hemeroby within the polygons was conducted. In total, 48,457 invertebrate (Annelida, Arthropoda, and Mollusca) individuals of 6 classes, 13 orders, 50 families and 83 species or parataxonomic units were recorded. Phytoindication reveals that the level of hemeroby within the studied polygons varies from 34.9 to 67.2. The model V and VI from the HOFJO-list were the most optimal model of the species response to hemeroby gradient. The weighted average factor value was used to assess the optimal factor level for the species in a symmetrical bell-shaped response model. The optimal factor level of the hemeroby for the soil macrofauna species ranges from 34.9 to 66.0. Species also differ in degree of specialization to the factor of hemeroby. There was a regular change in the soil macrofauna community size and diversity in the hemeroby gradient. The limiting influence of anthropogenic transformation of the environment on the abundance of soil macrofauna community is clearly marked at the level of hemeroby above average. Species diversity of the community is greatest at moderate hemeroby level. Both relatively little transformed habitats and strongly transformed ones are characterized by lower species richness of the soil macrofauna community. The Shannon index shows a clear upward trend with increasing hemeroby. The Pielou index indicates that the main reason for this trend is an increase in community evenness with increasing hemeroby. The intermediate disturbance hypothesis was fully supported with respect to species richness. For the number of species, there is indeed a certain level of heterogeneity at which the number of species is highest. For another aspect of diversity, evenness, this pattern is not true. The evenness increases with increasing habitat disturbance. This result is due to a decrease in the abundance of dominant species.

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Global projections of future urban land expansion under shared socioeconomic pathways

Cited by 489 publications

References 64 publications

Simulating the Impact of Future Climate Change and Ecological Restoration on Trade-Offs and Synergies of Ecosystem Services in Two Ecological Shelters and Three Belts in China

Simulating the Impact of Future Climate Change and Ecological Restoration on Trade-Offs and Synergies of Ecosystem Services in Two Ecological Shelters and Three Belts in China

Forecasting Spatio-Temporal Dynamics on the Land Surface Using Earth Observation Data—A Review

Applying plant disturbance indicators to reveal the hemeroby of soil macrofauna species

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