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Báo cáo khoa học: Predicting the yield of Douglas fir from site factors on better quality sites in Scotland
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Tuyển tập các báo cáo nghiên cứu về lâm nghiệp được đăng trên tạp chí lâm nghiệp quốc tế đề tài:Predicting the yield of Douglas fir from site factors on better quality sites in Scotland...
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Báo cáo khoa học: "Predicting the yield of Douglas fir from site factors on better quality sites in Scotland" article Original Predicting the yield of Douglas fir from site factors on better quality sites in Scotland AL DC Macmillan J Dutch Tyler 1 Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB9 2QJ; 2 Forestry Authority Northern Research Station, Roslin, Midlothian EH25 9SY, UK 14 June (Received 2 January 1994; accepted 1995)Summary — In Scotland, as a result of recent changes in agricultural policy and grant schemes,there is now greater potential for planting a wider range of more productive forestry species on betterquality land. In order to permit accurate production forecasting and financial appraisals for any suchafforestation, it is necessary to develop predictive yield models. This article describes the developmentof a multiple linear regression model for the prediction of General Yield Class (GYC) of Douglas fir usingreadily assessed, or derived, site factors. Climate surfaces developed by spatial analysis of weatherdata were used to predict temperature and rainfall for 87 sample sites to a resolution of 1 km Estimates . 2of wind climate were derived from a regression model using geographic location, elevation and topo-graphic exposure. Multivariate analysis of these and other soil and topographic variables indicate thattemperature and exposure are most important in determining the productivity of Douglas fir on betterquality sites in Scotland. As crop age increases, GYC declines and the possible reasons for this effectare discussed. Other factors are also discussed, such as the genetic variability of Douglas fir, andproblems associated with establishment and form.Douglas fir / productivity / yield models / site factors / climateRésumé — Prédire la production du douglas à partir de facteurs stationnels sur des terrains demeilleure qualité en Écosse. Suite aux récents changements de politique agricole et de schémas d’at-tribution des subventions, il existe actuellement en Écosse de nouvelles possibilités pour planter un éven-tail plus large d’espèces forestières plus productives sur des terres de meilleure qualité. Afin de pré-dire de façon précise les productions et les implications financières de tels reboisements, il estnécessaire de développer des modèles de prédiction des productions. Cet article présente le déve-loppement d’un modèle de régression multilinéaire de prédiction des classes générales de productiondu douglas en utilisant des facteurs stationnels mesurés directement. Des surfaces climatiques, obte-nues par une analyse spatiale des données climatiques, ont été utilisées pour prédire la températureet la pluviométrie de 87 sites échantillons à une résolution du km Des estimations du vent ont été obte- . 2nues en appliquant un modèle de régression linéaire utilisant la localisation géographique, l’altitude etl’exposition. Une analyse multivariée incorporant les 2 précédents aspects plus des variables décrivantle sol et la topographie montre que la température et l’exposition sont les 2 principales variables expli-quant la productivité du douglas sur des terrains de meilleure qualité en Écosse. On discute ensuite lacontribution d’autres facteurs, tels que la variabilité génétique du douglas et les problèmes liés à l’éta-blissement et à la forme.douglas / productivité / modèle de production / facteur stationnel / climatINTRODUCTION later importations has not been as good (Phillips, 1993). Britain’s climate is temperate oceanic,In the European Union, tree planting on agri- and wind is therefore an important factorcultural land is seen as a way to reduce tree growth (Pears, 1967; Grace, limitingagricultural production, diversify farm income 197 ...
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Báo cáo khoa học: "Predicting the yield of Douglas fir from site factors on better quality sites in Scotland" article Original Predicting the yield of Douglas fir from site factors on better quality sites in Scotland AL DC Macmillan J Dutch Tyler 1 Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB9 2QJ; 2 Forestry Authority Northern Research Station, Roslin, Midlothian EH25 9SY, UK 14 June (Received 2 January 1994; accepted 1995)Summary — In Scotland, as a result of recent changes in agricultural policy and grant schemes,there is now greater potential for planting a wider range of more productive forestry species on betterquality land. In order to permit accurate production forecasting and financial appraisals for any suchafforestation, it is necessary to develop predictive yield models. This article describes the developmentof a multiple linear regression model for the prediction of General Yield Class (GYC) of Douglas fir usingreadily assessed, or derived, site factors. Climate surfaces developed by spatial analysis of weatherdata were used to predict temperature and rainfall for 87 sample sites to a resolution of 1 km Estimates . 2of wind climate were derived from a regression model using geographic location, elevation and topo-graphic exposure. Multivariate analysis of these and other soil and topographic variables indicate thattemperature and exposure are most important in determining the productivity of Douglas fir on betterquality sites in Scotland. As crop age increases, GYC declines and the possible reasons for this effectare discussed. Other factors are also discussed, such as the genetic variability of Douglas fir, andproblems associated with establishment and form.Douglas fir / productivity / yield models / site factors / climateRésumé — Prédire la production du douglas à partir de facteurs stationnels sur des terrains demeilleure qualité en Écosse. Suite aux récents changements de politique agricole et de schémas d’at-tribution des subventions, il existe actuellement en Écosse de nouvelles possibilités pour planter un éven-tail plus large d’espèces forestières plus productives sur des terres de meilleure qualité. Afin de pré-dire de façon précise les productions et les implications financières de tels reboisements, il estnécessaire de développer des modèles de prédiction des productions. Cet article présente le déve-loppement d’un modèle de régression multilinéaire de prédiction des classes générales de productiondu douglas en utilisant des facteurs stationnels mesurés directement. Des surfaces climatiques, obte-nues par une analyse spatiale des données climatiques, ont été utilisées pour prédire la températureet la pluviométrie de 87 sites échantillons à une résolution du km Des estimations du vent ont été obte- . 2nues en appliquant un modèle de régression linéaire utilisant la localisation géographique, l’altitude etl’exposition. Une analyse multivariée incorporant les 2 précédents aspects plus des variables décrivantle sol et la topographie montre que la température et l’exposition sont les 2 principales variables expli-quant la productivité du douglas sur des terrains de meilleure qualité en Écosse. On discute ensuite lacontribution d’autres facteurs, tels que la variabilité génétique du douglas et les problèmes liés à l’éta-blissement et à la forme.douglas / productivité / modèle de production / facteur stationnel / climatINTRODUCTION later importations has not been as good (Phillips, 1993). Britain’s climate is temperate oceanic,In the European Union, tree planting on agri- and wind is therefore an important factorcultural land is seen as a way to reduce tree growth (Pears, 1967; Grace, limitingagricultural production, diversify farm income 197 ...
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