Predicting Norway Spruce Growth From Soil and Topographic Properties in New York

Abstract

Soil‐site productivity relationships for Norway spruce (Picea abies (L.) Karst.) were studied on a single, but widespread soil catena (Bath‐Lordstown‐Mardin‐Volusia; ∼1.1 million ha) in central New York. Soils and vegetation data collected from 37 unthinned plantations (45‐55‐yr old) were used to develop multiple regression soilsite predictor equations and discriminant classification functions. Efforts were made through sampling procedures to reduce extraneous sources of variation inherent in many previous soil‐site studies (e.g., parent materials, geographic area, stand density, stand age, cultural practices, and seed sources). Results of regression analyses showed that three to seven independent variables could explain 53 to 82% of the variation in mean annual volume increment (MAI). Stratifying the data set by a common planting density (2990 stems ha−1) generally improved the precision of the regression equations. Independent tests of the soil‐site equations across diverse drainage conditions showed a significant correlation between predicted and measured values of MAI (r = 0.70). More accurate predictions resulted (r = 0.80) when the equations were restricted to moderately well‐ and well‐drained soils only. Discriminant functions correctly reclassified (jackknifed analysis) 81% of the 37 stands into two MAI productivity groups. In general, results from the discriminant analyses supported interpretations made from the regression analyses. Soil properties, such as textural components, coarse fragments, pH, exchangeable cations, organic C, and cation exchange capacity (CEC), were most consistently correlated with Norway spruce volume production. Topographic properties made little or no independent contribution to the predictive models developed for growth. Results should aid yield predictions and site classification decisions for Norway spruce in New York.

Soil and forest productivity: a case study from Stone pine (Pinus pinea L.) stands in Calabria (southern Italy)

“…Soil samples (0-10 cm depth) were used to describe the characteristic of forest soils in accordance with the methodology proposed by Jokela et al (1988), particularly because the changes caused by environmental or to pographic factors are more prominent and relevant (e.g., on organic matter and soil bio chemical properties) on the upper layer of the soils.…”

“…appropriate stand va riables are not available. Studies based on soil-growth relationship (soil-site method) have been carried on for a wide range of spe cies elsewhere (e.g., Harding et al 1985, Jokela et al 1988, Monserud et al 1990, Pacheco 1991, Wang 1995, Bravo & Montero 2001, but very few soil-site studies have been reported for Stone pine (Bra vo-Oviedo & Montero 2005). Site index is a variable surrogate of the net stem growth that can be harvested in traditional forestry.…”

“…Altitude, slope, aspect (Jokela et al 1988, Pacheco 1991, Holmgren 1994 and geographic position (Pacheco 1991) are the topographic factors commonly used (Jokelaet al 1988, Pacheco 1991, Holmgren 1994 to estimate site index. It is common knowledge that topography, in the forest ecosystem, influences local microclimates by changing the pattern of precipitation, tem perature and relative humidity (Tsui et al 2004, Yimer et al 2006) and significantly af fects soil physical and chemical characte ristics and soil organic matter trend, strictly related to the dynamic and ecology of the soils.…”

“…Soil tex ture and nutrients levels are commonly used to estimate site index (Baker & Broadfoot 1979, Jokela et al 1988, Turner et al 1990, Pacheco 1991, though the wide range of nu trients and analytical methods make difficult to compare the results. On the other hand, it is well known that nutrients explain a low percentage of height increment (Baker & Broadfoot 1979).…”

Características ambientais determinantes da capacidade produtiva de sítios cultivados com eucalipto

“…Os enfoques mais holísticos, empregando estatística multivariada e envolvendo múltiplos fatores simultaneamente (clima, solo, relevo, vegetação, geologia), levam a melhores resultados (Spurr & Barnes, 1980;Laar, 1987), razão por que têm sido usados no desenvolvimento de vários sistemas de classificação de sítios (Pregitzer & Barnes, 1984;Harding et al, 1985;Hix, 1988;Jokela et al, 1988;Burton et al, 1991;Corns, 1992;Fincher & Smith, 1994).…”