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  • English  (40)
  • 2020-2024  (40)
  • 1960-1964
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  • 1
    Publication Date: 2023-01-21
    Description: Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (〉 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2023-01-21
    Description: Countries’ reliance on global food trade networks implies that regionally different climate change impacts on crop yields will be transmitted across borders. This redistribution constitutes a significant challenge for climate adaptation planning and may affect how countries engage in cooperative action. This paper investigates the long-term (2070–2099) potential impacts of climate change on global food trade networks of three key crops: wheat, rice and maize. We propose a simple network model to project how climate change impacts on crop yields may be translated into changes in trade. Combining trade and climate impact data, our analysis proceeds in three steps. First, we use network community detection to analyse how the concentration of global production in present-day trade communities may become disrupted with climate change impacts. Second, we study how countries may change their network position following climate change impacts. Third, we study the total climate-induced change in production plus import within trade communities. Results indicate that the stability of food trade network structures compared to today differs between crops, and that countries’ maize trade is least stable under climate change impacts. Results also project that threats to global food security may depend on production change in a few major global producers, and whether trade communities can balance production and import loss in some vulnerable countries. Overall, our model contributes a baseline analysis of cross-border climate impacts on food trade networks.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 3
    Publication Date: 2023-03-03
    Description: Modern food production is spatially concentrated in global “breadbaskets.” A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climate-related losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end of century warming using seven process-based models simulating five major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP 8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 4
    Publication Date: 2023-03-08
    Description: Soil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975–2010, this SOC debt continued to expand by 5 GtC (0.14 GtC yr−1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtC yr−1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement – also within computationally demanding integrated (land use) assessment modeling.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 5
    Publication Date: 2023-05-02
    Description: To satisfy the increasing global demand for agricultural products, the expansion of irrigation is an important intensification measure. At the same time, unsustainable water abstractions and cropland expansion pose a threat to biodiversity and ecosystem functioning. Irrigation potentials are influenced by local biophysical irrigation water availability and competition of different water users. Using a novel hydro-economic data processing routine that considers economic criteria of water allocation via a productivity ranking of grid cells and both land and water sustainability criteria, we estimate global irrigation potentials at a 0.5 ° spatial resolution. We show that there is considerable technical potential to expand irrigation within local water and land boundaries. In terms of potentially irrigated areas on all global land suitable for crop production, 2144 Mha could be irrigated within land and water environmental boundaries when only considering biophysical criteria. However, not all of these areas would actually be irrigated under consideration of irrigation costs. Of these, only 698 Mha (330 Mha) have a yield gain of more than 300 (600) USD ha-1 under the current crop mix valued at their current commodity price (economic irrigation potential).
    Language: English
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  • 6
    Publication Date: 2023-06-20
    Description: This repository contains the data used to produce all figures in Beringer et al. "CO2 fertilization effect may balance climate change impacts on oil palm cultivation".
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 7
    Publication Date: 2023-07-06
    Description: The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (doi: 10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 8
    Publication Date: 2023-07-26
    Description: The Chinese food system has undergone a transition of unprecedented speed, leading to complex interactions with China’s economy, health and environment. Structural changes experienced by the country over the past few decades have boosted economic development but have worsened the mismatch between food supply and demand, deteriorated the environment, driven obesity and overnutrition levels up, and increased the risk for pathogen spread. Here we propose a strategy for slimming and greening the Chinese food system towards sustainability targets. This strategy takes into account the interlinkages between agricultural production and food consumption across the food system, going beyond agriculture-focused perspectives. We call for a food-system approach with integrated analysis of potential triple benefits for the economy, health and the environment, as well as multisector collaboration in support of evidence-based policymaking.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 9
    Publication Date: 2023-07-26
    Description: Interactions between soil quality and climate change may influence the capacity of croplands to produce sufficient food. Here, we address this issue by using a new dataset of soil, climate and associated yield observations for 12,115 site-years representing 90% of total cereal production in China. Across crops and environmental conditions, we show that high-quality soils reduced the sensitivity of crop yield to climate variability leading to both higher mean crop yield (10.3 ± 6.7%) and higher yield stability (decreasing variability by 15.6 ± 14.4%). High-quality soils improve the outcome for yields under climate change by 1.7% (0.5–4.0%), compared to low-quality soils. Climate-driven yield change could result in reductions of national cereal production of 11.4 Mt annually under representative concentration pathway RCP 8.5 by 2080–2099. While this production reduction was exacerbated by 14% due to soil degradation, it can be reduced by 21% through soil improvement. This study emphasizes the vital role of soil quality in agriculture under climate change.
    Language: English
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  • 10
    Publication Date: 2023-07-26
    Description: Population growth and economic development in China has increased the demand for food and animal feed, raising questions regarding China’s future maize production self-sufficiency. Here, we address this challenge by combining data-driven projections with a machine learning method on data from 402 stations, with data from 87 field experiments across China. Current maize yield would be roughly doubled with the implementation of optimal planting density and management. In the 2030 s, we estimate a 52% yield improvement through dense planting and soil improvement under a high-end climate forcing Shared Socio-Economic Pathway (SSP585), compared with a historical climate trend. Based on our results, yield gains from soil improvement outweigh the adverse effects of climate change. This implies that China can be self-sufficient in maize by using current cropping areas. Our results challenge the view of yield stagnation in most global areas and provide an example of how food security can be achieved with optimal crop-soil management under future climate change scenarios.
    Language: English
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