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ArticleJournal articleSpatial distribution model of phragmanthera plant parasite in Rift Valley Ecoregion of Kenya
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.About 80% of Kenya’s land area has been classified as Arid and Semi-Arid, ASALs and experiences high temperatures and low erratic rainfall throughout the year. In the search for suitable tree species for agroforestry and landscape restoration in Kenyan ASALs two Meliaceae tree species, indigenous Melia volkensii (Geurke) and exotic Azadirachta indica (A. Juss.) were selected for further research. In Kenya, Botryosphaeriaceae has been reported on Grevillea robusta on-farm causing damage to the tree and in severe cases leads to mortality. Molecular identification of cultures used in the study based on rDNA of the ITS and Tef1-alpha gene regions for 86 isolates classified into 6 species of the Botryosphaeriaceae. 3 of the Botryosphaeriaceae species belonged to the genus Lasiodiplodia namely L. pseudotheobromae, L. theobromae and L. parva. This is the first report of species Spencermartinsia viticola and Macrophoma theicola in Kenya. Pathogenicity tests done under glasshouse conditions showed that the L. pseudotheobromae species was most virulent to both M. volkensii & A. indica while L. theobromae was least virulent to both tree species. Wilting & necrosis was recorded within 7 days of inoculation but wound healing occurred on both species after 12 weeks. This study gives insight into disease resistance and tolerance of these dryland species for plantation establishment. It also revealed wider host diversity for Botryosphaeriaceae in the drylands. Further research into the species disease resistance mechanisms and proper silvicultural treatments are a prerequisite for large scale planting of the two tree species in light of climate variation and ecosystem changes. The recommendations given in the study are being taken into account for commercial forestry ventures in the drylands and advisory services being provided for diseases control and management. Key words: Pathogenicity test, Phylogenetic analyses, Lesion measurement ID: 3623720 -
ArticleJournal articleTowards predicting the potential distribution areas of phacochoerus Africanus (gmelin 1788) and potamochoerus porcus (linnaeus 1758) in Benin using specific model algorithms
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.The mistake is to think that reducing losses in tropical ecosystems is enough to control generally irreversible global change. Suids are found in biodiversity hotspots in Benin, providing enormous ecosystem services that help mitigate the impacts of climate change-related disturbances. This work rightly contributes to the assessment of the effects of climate variability on the future distribution of the Red river hog and the Common warthog in Benin. Following the occurrences collected on the GBIF platform, previous work and those collected in the field, non-climatic and climatic environmental data likely to influence their presence were used while reducing sampling errors. ArcGis software was used through the SDM Tools extension to prepare the data. Modelling was carried out using R software. The AUC, TSS, COR and deviance metrics were considered for the selection of the best model through the present and future RCP 8.5 scenarios by using the GLM, Random Forest and Maxent algorithms. For all species, the AUC and TSS of the Random Forest algorithm gave the highest values. With a quasi-regression of these favourable areas in the north and centre, the Common warthog remains more subject to the effects of climatic variability in Benin than the Red river hog. It is important to better orientate awareness-raising approaches, to carry out educational training on the mitigation of the effects of climate change while ensuring the provision of income generating/benefit activities that respect the environment. The creation of a database on the degree of threat specific to these suids and the updating of data on the status of their preferred areas in Benin is necessary. Keywords: Biodiversity conservation, Climate change, Adaptive and integrated management, Sustainable forest management, Research. ID: 3622243 -
DocumentOther documentSpatial distributions pattern and associations of dead woods in natural spruce-fir secondary forests
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Natural secondary forest is the main part of forest resources in China. Studying dead woods (DW) could better reveal the community succession rule and promote the healthy development of them. We investigated basic characteristics and coordinates of each tree (DBH≥1 cm) within a plot (100 m×100 m) using the adjacent grid method and studied the spatial distributions pattern and associations of DW (in the last five years) in a typical natural spruce-fir secondary forest in Jingouling Forest Farm, Wangqing Forestry Bureau, Jilin Province, China. The results showed that the diameter class distribution of DW showed the pattern of left-single-peak curve, while the logs showed the pattern of multi-peak curve. DW number was related to the mixing degree of one species, but not to the total number of it. The distribution of DW was concentrated at 0~8m scale. As the scale increases, it changed to random or uniform. The aggregation distribution of DW of medium (10 cm≤DBH<20 cm) and small (1 cm≤DBH<10 cm) DBH at small scale below 8 m was the main reason for the aggregation distribution of DW. The DW of large (DBH≧20 cm) DBH and Saplings (1 cm≤DBH<5 cm) showed a significant positive association at 2~25 m scale. There was no significant spatial association between DW and Small trees(5 cm≤DBH<15 cm). At 0~3m scale, there was a positive association between Medium trees (15 cm≤DBH<25 cm) and DW of small and medium DBH. At the 9 m, 11~14 m scale and the 15 m, 42~45 m scale, the DW of small and medium DBH were significantly negatively associated with Large trees (DBH≥25 cm). In conclusion, the biological traits, diameter class distribution and spatial distribution affected the abundance and diameter class distribution of DW of one species. The spatial distributions of DW and the associations between DW and standing trees varied across diameter classes and scales. Rational utilization of spatial information could optimize stand structure and promote positive community succession. Keywords: Deforestation and forest degradation, Sustainable forest management, Adaptive and integrated management ID: 3618474
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BookletHigh-profileFAO Strategy on Climate Change 2022–2031 2022The FAO Strategy on Climate Change 2022–2031 was endorsed by FAO Council in June 2022. This new strategy replaces the previous strategy from 2017 to better FAO's climate action with the Strategic Framework 2022-2031, and other FAO strategies that have been developed since then. The Strategy was elaborated following an inclusive process of consultation with FAO Members, FAO staff from headquarters and decentralized offices, as well as external partners. It articulates FAO's vision for agrifood systems by 2050, around three main pillars of action: at global and regional level, at country level, and at local level. The Strategy also encourages key guiding principles for action, such as science and innovation, inclusiveness, partnerships, and access to finance.
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Book (stand-alone)Technical bookThe future of food and agriculture - Trends and challenges 2017
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No results found.What will be needed to realize the vision of a world free from hunger and malnutrition? After shedding light on the nature of the challenges that agriculture and food systems are facing now and throughout the 21st century, the study provides insights into what is at stake and what needs to be done. “Business as usual” is not an option. Major transformations in agricultural systems, rural economies, and natural resources management are necessary. The present study was undertaken for the quadrennial review of FAO’s strategic framework and for the preparation of the Organization Medium-Term plan 2018-2021. -
BookletCorporate general interestEmissions due to agriculture
Global, regional and country trends 2000–2018
2021Also available in:
No results found.The FAOSTAT emissions database is composed of several data domains covering the categories of the IPCC Agriculture, Forestry and Other Land Use (AFOLU) sector of the national GHG inventory. Energy use in agriculture is additionally included as relevant to emissions from agriculture as an economic production sector under the ISIC A statistical classification, though recognizing that, in terms of IPCC, they are instead part of the Energy sector of the national GHG inventory. FAO emissions estimates are available over the period 1961–2018 for agriculture production processes from crop and livestock activities. Land use emissions and removals are generally available only for the period 1990–2019. This analytical brief focuses on overall trends over the period 2000–2018.