scholarly journals Towards more integration of physiology, dispersal and land-use change to understand the responses of species to climate change

2021 ◽  
Vol 224 (Suppl 1) ◽  
pp. jeb238352
Author(s):  
Christian Hof
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Change ◽  
Land Use Change ◽  
Scientific Community ◽  
Climatic Conditions ◽  
Extrinsic Factors ◽  
Related Factors ◽  
Dispersal Capacity ◽  
Biodiversity Crisis

ABSTRACTThe accelerating biodiversity crisis, for which climate change has become an important driver, urges the scientific community for answers to the question of whether and how species are capable of responding successfully to rapidly changing climatic conditions. For a better understanding and more realistic predictions of species' and biodiversity responses, the consideration of extrinsic (i.e. environment-related) and intrinsic (i.e. organism-related) factors is important, among which four appear to be particularly crucial: climate change and land-use change, as extrinsic factors, as well as physiology and dispersal capacity, as intrinsic factors. Here, I argue that these four factors should be considered in an integrative way, but that the scientific community has not yet been very successful in doing so. A quantitative literature review revealed a generally low level of integration within global change biology, with a pronounced gap especially between the field of physiology and other (sub)disciplines. After a discussion of potential reasons for this unfortunate lack of integration, some of which may relate to key deficits e.g. in the reward and incentive systems of academia, I suggest a few ideas that might help to overcome some of the barriers between separated research communities. Furthermore, I list several examples for promising research along the integration frontier, after which I outline some research questions that could become relevant if one is to push the boundary of integration among disciplines, of data and methods, and across scales even further – for a better understanding and more reliable predictions of species and biodiversity in a world of global change.

scholarly journals Scenario-Based Analysis on the Structural Change of Land Uses in China

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Qian Xu ◽  
Qunou Jiang ◽  
Kai Cao ◽  
Xing Li ◽  
Xiangzheng Deng
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Change ◽  
Land Use Change ◽  
Global Environmental Change ◽  
Structure Change ◽  
Assessment Model ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
The Impact

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

scholarly journals Multi-Scenario Prediction of Intra-Urban Land Use Change Using a Cellular Automata-Random Forest Model

2021 ◽  
Vol 10 (8) ◽  
pp. 503
Author(s):  
Hang Liu ◽  
Riken Homma ◽  
Qiang Liu ◽  
Congying Fang
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Land ◽  
Urban Land Use ◽  
Random Forest Model ◽  
Growth Trend ◽  
Related Factors ◽  
Forest Model

The simulation of future land use can provide decision support for urban planners and decision makers, which is important for sustainable urban development. Using a cellular automata-random forest model, we considered two scenarios to predict intra-land use changes in Kumamoto City from 2018 to 2030: an unconstrained development scenario, and a planning-constrained development scenario that considers disaster-related factors. The random forest was used to calculate the transition probabilities and the importance of driving factors, and cellular automata were used for future land use prediction. The results show that disaster-related factors greatly influence land vacancy, while urban planning factors are more important for medium high-rise residential, commercial, and public facilities. Under the unconstrained development scenario, urban land use tends towards spatially disordered growth in the total amount of steady growth, with the largest increase in low-rise residential areas. Under the planning-constrained development scenario that considers disaster-related factors, the urban land area will continue to grow, albeit slowly and with a compact growth trend. This study provides planners with information on the relevant trends in different scenarios of land use change in Kumamoto City. Furthermore, it provides a reference for Kumamoto City’s future post-disaster recovery and reconstruction planning.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Governing the global commons: an ethical-legal framework

2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Prue Taylor
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Ocean Acidification ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Legal Framework ◽  
State System ◽  
Global Commons ◽  
Global Challenges

Governance of the Earth’s global ecological commons creates unprecedented challenges for humanity. Our traditional Westphalian state system was not designed to respond to these global challenges and thus far it has failed to transform. Climate change is the current headline issue; 30 years on and we still swing between hope and despair about our collective ability to radically reduce greenhouse gas emissions. Related issues are beginning to vie for our response: ocean acidification, mass species extinction, land use change and freshwater scarcity. 

scholarly journals Modeling Urban Futures: Data-Driven Scenarios of Climate Change and Vulnerability in Cities

2021 ◽  
pp. 129-144
Author(s):  
L. Ortiz ◽  
A. Mustafa ◽  
B. Rosenzweig ◽  
Timon McPhearson
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Numerical Models ◽  
Flood Hazards ◽  
Ancillary Data ◽  
Road Systems ◽  
Urban Futures ◽  
Land Use Development

AbstractCities are complex systems where social, ecological, and technological processes are deeply coupled. This coupling complicates urban planning and land use development, as changing one facet of the urban fabric will likely impact the others. As cities grapple with climate change, there is a growing need to envision urban futures that not only address more frequent and intense severe weather events but also improve day-to-day livability. Here we examine climate risks as functions of the local land use with numerical models. These models leverage a wide array of data sources, from satellite imagery to tax assessments and land cover. We then present a machine-learning cellular automata approach to combine historical land use change with local coproduced urban future scenarios. The cellular automata model uses historical and ancillary data like existing road systems and natural features to develop a set of probabilistic land use change rules, which are then modified according to stakeholder priorities. The resulting land use scenarios are evaluated against historical flood hazards, showcasing how they perform against stakeholder expectations. Our work shows that coproduced scenarios, when grounded with historical and emerging data, can provide paths that increase resilience to weather hazards as well as enhancing ecosystem services provided to citizens.

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