A robust growth model for smallholder tree plantations

Information is a prerequisite for wise forest management decisions, but is inadequate in many situations, especially in the context of small non-industrial forest growers. This paper presents a series of robust functions able be calibrated with sparse data, and integrated into a simple spreadsheet-based growth model designed to assist silvicultural decisions in smallholder plantations. A case study with Gmelina arborea is presented. Introduction Many people who plant, or who have planted trees, anticipate a reasonable return on their investment but often have insufficient information to make informed silvicultural decisions to maximize their financial return. Often there is no shortage of inventory data; the limitation is usually that data are not in a suitable form to support practical silvicultural inferences by small private growers. This paper seeks to provide guidance and offer a practical illustration of one way to distil practical silvicultural advice from routine forest management data. 1 Paper to End-of-Project Workshop, ACIAR ASEM/2003/052 Improving Financial Returns to Smallholder Tree Farmers in the Philippines, 11-12 February 2009, Sabin Resort Hotel, Ormoc City, Leyte. Context Forest inventory and monitoring by industrial forest growers may provide data that can support conventional growth modelling enterprises (Vanclay 1991a; Vanclay et al 1995; Mendoza and Vanclay 2008), but extension and small-scale afforestation efforts often exist in a context where neither data nor models satisfy practical needs (Vanclay 2006a). ACIAR Project ASEM/2003/052 − Improving Financial Returns to Smallholder Tree Farmers in the Philippines − is designed to improve the livelihoods of smallholder farmers in Leyte Province through investigating ways of improving financial returns from forestry, and promoting the adoption of these improved management methods (Herbohn et al 2007). Smallholder farmers in Leyte find themselves in an all-to-common situation with insufficient information to inform their slivicultural decisions. One objective of the ACIAR project was to improve livelihoods by providing better access to such information. In many cases, tree growers need assistance with three compelling questions: 1. should I thin the non-commercial (eg, crooked) trees in my plantings; 2. should I thin my plantation for cash-flow and silvicultural reasons, and if so, the best age(s) to thin; and 3. when should I anticipate my final harvest? In order to satisfy these questions, a simple growth model should provide estimates of tree heights, diameters, and stem numbers, aggregated to indicate likely harvest volumes and values. This may seem a daunting task, but extension workers can take heart from two observations: namely that tree growth tends to be similar in many regions of the world, enabling the use of models developed elsewhere (Vanclay et al 2008); and that there are a number of established hypotheses (Skovsgaard and Vanclay 2008) that can be calibrated with few data.