Relationship between environmental parameters and Pinus sylvestris L. site index in forest plantations in northern Spain acidic plateau

Abstract

The assessment of forest productivity at early stages of stand development may help to define the most appropriate silviculture treatment to be applied for each stand. Site index (dominant height at a reference age) is a useful tool for forest productivity estimation. The aim of this study was to develop a model to predict site index for Scots pine (Pinus sylvestris L.) plantations in northern Spain acidic plateau by using soil (physical, chemical and biochemical), climatic and physiographic parameters. To meet this objective, data from 35 stands classified into three different site quality classes and 63 soil, climatic and physiographic parameters were examined in order to develop a discriminant model. After selecting 12 discriminant models which were biologically consistent and presented the higher cross-validated rate of correct classification, a model including four parameters (latitude, inorganic Al, porosity and microbial biomass carbon) as predictors was chosen. The discriminant model classified 71% of cases correctly and no inferior-quality stands were misassigned to the highest quality class. Soil and physiographic parameters included in the above model are easily obtainable in the field or by simple laboratory analysis, thus our results can be easily integrated in operational forestry to determine site quality.

Factors determining enzyme activities in soils under Pinus halepensis and Pinus sylvestris plantations in Spain: a basis for establishing sustainable forest management strategies

“…As an active component of soil organic matter, microbial biomass participates in the transformations and accumulation of nutrients in soil and serves as a good measurement of organic matter turnover and biological activity in forest and agricultural ecosystems (Bueis et al 2016;Gartzia-Bengoetxea et al 2009). Enzyme activities and soil microbial biomass have been proposed as suitable indicators of nutrient availability (Yang et al 2012) and soil quality (Muscolo et al 2015) because of their relation to soil biology and their quick reaction to changes (Bandick and Dick 1999;Das and Varma 2011;Llorente and Turrion 2010;Muscolo et al 2007).…”

Stand and environmental data from Pinus halepensis Mill. and Pinus sylvestris L. plantations in Spain

“…Soil sampling and stand, climatic and physiographic data collection were done as detailed in Bueis et al (2016) available at https://doi.org/10.3832/ifor1600-008, in Bueis et al (2017) available at https://doi.org/10.1007/s13595-016-0609-7 and in Bueis et al (2018b) available at https://doi. org/10.1007/s13595-018-0720-z.…”

“…Climatic, physiographic and soil physical and chemical parameters are usually included in this kind of models. However, soil biochemical parameters are seldom included, even when soil microorganisms play a key role in soil quality and productivity (Bueis et al 2016(Bueis et al , 2017Gartzia-Bengoetxea et al 2009). They have also been used to assess the differences between the enzyme activities in the contrasting soils under Pinus sylvestris and Pinus halepensis plantations and to trace those differences back to edapho-climatic parameters to determine which environmental factors drive enzyme activities in these soils (Bueis et al 2018b).…”

“…The knowledge about the relationships between environmental factors and stand data in forest plantations can help forest managers to achieve both protective and productive goals for these plantations and are useful for the understanding of the ecosystem functioning (Bueis et al 2016(Bueis et al , 2017. Environmental parameters including climatic, topographic and soil (physical, chemical and biochemical) parameters have proved useful for estimating forest productivity (Aertsen et al 2012;Afif-Khouri et al 2010;Bravo-Oviedo and Montero 2005;Bravo and Montero 2001;Bueis et al 2016Bueis et al , 2017Corona et al 1998;Hagglund and Lundmark 1977;Nieppola and Carleton 1991;Pietrzykowski et al 2015;Romanya and Vallejo 2004;Sanchez-Rodriguez et al 2002;Sharma et al 2012). Forest productivity is usually estimated through stand parameters such as the dominant height (the height of the 100 thickest trees per hectare) at a reference age, because it is strongly correlated to wood production (Skovsgaard and Vanclay 2008).…”

“…However, some silvicultural practices modify the dominant height of the stands leading to underestimation of forest productivity. In those cases, the methods based on environmental parameters are more appropriate (Bueis et al 2016(Bueis et al , 2017. Besides, soil biochemical parameters reflect the status of the soil biological activity responsible for mineralisation and humification processes and then responsible for nutrient availability in forest ecosystems (Bueis et al 2018b;Yang et al 2012) and are also useful indicators of health and quality in forest ecosystems (Bloem et al 2006).…”