Vast areas of arable land have been retired from crop production and "rehabilitated" to improved system states through landowner incentive programs in the United States (e.g., Conservation and Wetland Reserve Programs), as well as Europe (i.e., Agri-Environment Schemes). Our review of studies conducted on invasion of rehabilitated agricultural production systems by nontarget species elucidates several factors that may increase the vulnerability of these systems to invasion. These systems often exist in highly fragmented and agriculturally dominated landscapes, where propagule sources of target species for colonization may be limited, and are established under conditions where legacies of past disturbance persist and prevent target species from persisting. Furthermore, rehabilitation approaches often do not include or successfully attain all target species or historical ecological processes (e.g., hydrology, grazing, and/or fire cycles) key to resisting invasion. Uncertainty surrounds ways in which nontarget species may compromise long term goals of improving biodiversity and ecosystem services through rehabilitation efforts on former agricultural production lands. This review demonstrates that more studies are needed on the extent and ecological impacts of nontarget species as related to the goals of rehabilitation efforts to secure current and future environmental benefits arising from this widespread conservation practice.
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http://dx.doi.org/10.1007/s00267-008-9167-6 | DOI Listing |
Ecohealth
January 2025
Forestry and Forest Products Research Institute, Matsunosato 1, Tsukuba, Ibaraki, 305-8687, Japan.
Anthropogenic disturbances degrade ecosystems, elevating the risk of emerging infectious diseases from wildlife. However, the key environmental factors for preventing tick-borne disease infection in relation to host species, landscape components, and climate conditions remain unknown. This study focuses on identifying crucial environmental factors contributing to the outbreak of severe fever with thrombocytopenia syndrome (SFTS), a tick-borne disease, in Miyazaki Prefecture, southern Japan.
View Article and Find Full Text PDFJ Plant Res
January 2025
College of Marine and Biological Engineering, Yancheng Institute of Technology, Yancheng, 224002, Jiangsu, China.
Barley (Hordeum vulgare L.) is an important cereal crop used in animal feed, beer brewing, and food production. Waterlogging stress is one of the prominent abiotic stresses that has a significant impact on the yield and quality of barley.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Department of Field Crops, Faculty of Agriculture, Necmettin Erbakan University, Konya, 42310, Türkiye.
Background: Innovation in crop establishment is crucial for wheat productivity in drought-prone climates. Seedling establishment, the first stage of crop productivity, relies heavily on root and coleoptile system architecture for effective soil water and nutrient acquisition, particularly in regions practicing deep planting. Root phenotyping methods that quickly determine coleoptile lengths are vital for breeding studies.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Human Movement Science, Hunan Normal University, 36 Lushan Road, Changsha, Hunan, China.
Loneliness and low self-esteem are among the more prominent mental health problems among left-behind children, but most of the current research stays in cross-sectional surveys, with fewer studies proposing specific solutions. In addition, although the effective impact of dance interventions on loneliness and self-esteem has been demonstrated, the impact in the group of left-behind children remains under-explored. Therefore, this study validated the effectiveness of a dance intervention on loneliness and self-esteem in left-behind children through a 16-week randomised controlled trial.
View Article and Find Full Text PDFSci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
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