International agricultural trade triggers inter-dependency among distant countries, not only in economic terms but also under an environmental perspective. Agricultural trade has been shown to drive environmental threats pertaining to biodiversity loss and depletion and pollution of freshwater resources. Meanwhile, trade can also encourage production where it is most efficient, hence minimizing the use of natural resources required by agriculture. In this study, we provide a country-level assessment of the future international trade for 6 primary crops and 3 animal products composing 70% of the human diet caloric content. We set up four variegate socio-economic scenarios with different level of economic developments, diets habits, population growth dynamics, and levels of market liberalization. Results show that the demand of agricultural goods and the correspondent trade flow will increase with respect to current levels by 10-50% and 74-178% by 2050, respectively. The largest increase in the amount of traded goods is expected under the Economic Optimism scenario that will see an average trade flow of 2830 kcal/cap/day (i.e., nearly doubling the current per-capita flow). Most of the increase will be driven by the trade of crops for animal feeding, particularly maize will be the most traded crop. The trade networks architecture in 2050 and 2080 will be very different from the one we actually know, with a clear shift of the trade pole from the Western toward the Eastern economies. The dramatic changes of global food-sources and trade patterns will jeopardize the water resources of new regions while exacerbating the pressure in those areas that will continue serving food also in the future. In spite of this, trade may annually save around 40-60 m of water per person, compared to a situation where countries are self-sufficient.
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http://dx.doi.org/10.1016/j.scitotenv.2020.136626 | DOI Listing |
BMC Vet Res
January 2025
Technology Center, Hohhot Customs District, Hohhot, 010020, Inner Mongolia, China.
Background: Bovine viral diarrhoea virus genotype 1 (BVDV-1) and bluetongue virus (BTV) are potent viral pathogens that may be transmitted through semen, resulting in the spread of diseases via artificial insemination. Thus, establishing an early detection method for BVDV-1 and BTV infection is important for the trading of semen. In this study, we developed two RT‒ddPCR methods to detect BVDV-1 and BTV, and each method was evaluated for repeatability, limit of detection and specificity.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Key Comprehensive Laboratory of Forestry, Northwest A&F University, Yangling, Shaanxi Province, 712100, P. R. China.
Background: Study the leaf functional traits is highly important for understanding the survival strategies and climate adaptability of old trees. In this study, the old (over 100 years old) and mature trees (about 50 years old) of Pinus tabulaeformis in the Loess Plateau were studied, and the variation of 18 leaf functional traits (6 economic, 4 anatomical, 2 photosynthetic and 6 physiological traits) was analyzed to understand the differences of survival strategies between old and mature trees. Combined with transcriptome and simple sequence repeats (SSR) techniques, the effects of soil property factors and genetic factors on leaf functional traits and the potential molecular mechanisms of traits differences were studied.
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January 2025
Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
Long-lived iteroparous organisms vary resource expenditures toward migration and reproduction in response to individual physical factors and conspecific interactions, which can affect future reproductive timing and interval. Reproductive actions can lead to trade-offs associated with allocations to current vs. future reproduction, including longer reproductive interval, require additional study.
View Article and Find Full Text PDFSci Rep
January 2025
Biotechnology Major, Sangmyung University, Seoul, 03016, South Korea.
Numerous studies have proven the potential of deep learning models for classifying wildlife. Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade. Although deep learning models typically perform better with more input data, the available wildlife data are ordinarily limited, specifically for rare or endangered species.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Civil Engineering & Sustainable Structures, Technical University (Kadoorie), Jaffa Street, P.O. Box (7), Tulkarem, Palestine.
In the context of the Sustainable Development Goals (SDGs), which strive to ensure comprehensive access to fundamental water, sanitation, and hygiene (WASH) services, it is extremely imperative to prioritize communities in need and still disadvantaged. Moreover, tackling the worldwide sanitation crisis entails advancing the development of productive and sustainable sanitation systems and infrastructure. Sanitation planning is a multidimensional exercise encompassing multiple dimensions, stakeholders, and strategies, typically with conflicting objectives.
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