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Climate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent
The impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management and optimization.
Perspectives from CO+RE: How COVID-19 changed our food systems and food security paradigms
[no abstract available]
The Earth system model CLIMBER-X v1.0 – Part 1: Climate model description and validation
The newly developed fast Earth system model CLIMBER-X is presented. The climate component of CLIMBER-X consists of a 2.5-D semi-empirical statistical-dynamical atmosphere model, a 3-D frictional-geostrophic ocean model, a dynamic-thermodynamic sea ice model and a land surface model. All the model components are discretized on a regular lat-long grid with a horizontal resolution of 5 ° ×5 °. The model has a throughput of ° ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100000 years. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing many observed climate characteristics, with results that generally lie within the range of state-of-the-art general circulation models. The analysis of model performance is complemented by a thorough assessment of climate feedbacks and model sensitivities to changes in external forcings and boundary conditions. Limitations and applicability of the model are critically discussed. CLIMBER-X also includes a detailed representation of the global carbon cycle and is coupled to an ice sheet model, which will be described in separate papers. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
Climate change and international migration: Exploring the macroeconomic channel
International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries. On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades. Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape. Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration. As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal. Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income. Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change. We illustrate these different possibilities, and the corresponding effects of 3°C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.
Overview: The Baltic Earth Assessment Reports (BEAR)
Baltic Earth is an independent research network of scientists from all Baltic Sea countries that promotes regional Earth system research. Within the framework of this network, the Baltic Earth Assessment Reports (BEARs) were produced in the period 2019-2022. These are a collection of 10 review articles summarising current knowledge on the environmental and climatic state of the Earth system in the Baltic Sea region and its changes in the past (palaeoclimate), present (historical period with instrumental observations) and prospective future (until 2100) caused by natural variability, climate change and other human activities. The division of topics among articles follows the grand challenges and selected themes of the Baltic Earth Science Plan, such as the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Each review article contains an introduction, the current state of knowledge, knowledge gaps, conclusions and key messages; the latter are the bases on which recommendations for future research are made. Based on the BEARs, Baltic Earth has published an information leaflet on climate change in the Baltic Sea as part of its outreach work, which has been published in two languages so far, and organised conferences and workshops for stakeholders, in collaboration with the Baltic Marine Environment Protection Commission (Helsinki Commission, HELCOM).
Anticipation-induced social tipping: can the environment be stabilised by social dynamics?
In the past decades, human activities caused global Earth system changes, e.g., climate change or biodiversity loss. Simultaneously, these associated impacts have increased environmental awareness within societies across the globe, thereby leading to dynamical feedbacks between the social and natural Earth system. Contemporary modelling attempts of Earth system dynamics rarely incorporate such co-evolutions and interactions are mostly studied unidirectionally through direct or remembered past impacts. Acknowledging that societies have the additional capability for foresight, this work proposes a conceptual feedback model of socio-ecological co-evolution with the specific construct of anticipation acting as a mediator between the social and natural system. Our model reproduces results from previous sociological threshold models with bistability if one assumes a static environment. Once the environment changes in response to societal behaviour, the system instead converges towards a globally stable, but not necessarily desired, attractor. Ultimately, we show that anticipation of future ecological states then leads to metastability of the system where desired states can persist for a long time. We thereby demonstrate that foresight and anticipation form an important mechanism which, once its time horizon becomes large enough, fosters social tipping towards behaviour that can stabilise the environment and prevents potential socio-ecological collapse.
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
The process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model.
Chapter scientists in the IPCC AR5-experience and lessons learned
IPCC Assessment Reports provide timely and accurate information on anthropogenic climate change to policy makers and the public. The reports are written by hundreds of scientists in a voluntary, collaborative effort. Growing amounts of literature and complex procedural and administrative requirements, however, make this effort a substantial management challenge next to a scientific one. During the 5th Assessment Cycle, IPCC Working Groups II and III initiated a program that recruited volunteer scientific assistants who provided technical and logistical support to author teams. In this paper we describe and analyze strengths and weaknesses of this ‘Chapter Scientist program’, based on an extensive survey among Chapter Scientists (CS) and interviews with other stakeholders. We conclude that the program was a useful innovation that that enabled authors to focus more on their core scientific tasks and that contributed to improving the quality of the assessment. We highly recommend similar programs for future scientific assessments. Key criteria for success that we identified are (a) involvement of early-career scientists as CS, (b) close integration of CS in the assessment process, (c) recruitment of CS through an open call to achieve transparency, and (d) provision of funds for such a program to support travel costs and compensation of CS.
The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios
To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs)-SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6-to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.