Economics of Coharvesting Smallwood by Chainsaw and Skidder for Crop Tree Management in Missouri

The objective of the case studies reported here was to quantify actual timber revenues, the production rates and hourly machine costs of conventional harvest equipment (chainsaw and skidder), and the cost of loading and transporting timber from the woods to the mill. This permitted an assessment of the net operating revenues to loggers generated by forest improvement harvests using BMPs and crop tree management in the Missouri Ozarks. Our aim was to assess whether these harvest practices were an affordable option for loggers and landowners. Neither silvicultural prescriptions nor harvest practices were modified for this study, which measured outcomes based on actual costs and revenues. The loggers were exceptional in that all but one team were state or regional loggers of the year, and all incorporated smallwood harvesting in their normal operations. The low capital cost of their equipment was, however, typical of family logging operations, which predominate in the Missouri Ozarks. Materials and Methods Site Descriptions and Silvicultural Prescriptions Four upland oak or oak-hickory stands in the Missouri Ozarks were selected on the basis of the willingness of landowners and their loggers to participate in the study. All stands had some sawtimber 70 years old. Slope varied from 0% to 50%, and soils were mainly silt loams varying in depth from 1 to 8 ft. Our harvests occurred in 2008 and 2009, at least 30 years after the previous harvest. We studied a variety of approaches to crop tree management to better assess the economic feasibility of forest improvement harvests. At all sites, professional foresters selected individual crop trees (e.g., Iffrig et al. 2008) and marked trees for felling. Additionally, some group openings due to mortality or current prescription occurred at Sites II and IV. Two sites (II and III) had been harvested under crop tree management for at least three decades and were already producing sawtimber of greater size and quality than the other two sites, which had experienced only diameter-limit cuts. These groups were further dichotomized by the extent of FSI performed (greatest at Sites I and II). Smallwood consequently made up very different proportions of harvested timber volume and revenue among the sites. We have reported the results for individual sites so that readers can better judge their generality. Stand Inventories Preharvest inventories of trees l.5 in. dbh with a basal area factor prism of 10 followed standard procedures (Missouri Department of Conservation 2007). Postharvest damage was assessed for all live trees 5 in. dbh in 7 or 12 plots of 0.1 ac each, established in a systematic grid at about 3% sampling intensity. The boundary of the harvest area was mapped with a GPS device, as were the location of log decks within the harvest area and skid trails with three or more hauls to measure their areas. Work and Production Records Loggers were financially compensated for their time to record production data and furnish inputs for estimation of machine costs. Operators used electronic stopwatches and recorded the daily operational hours (to nearest 0.25 hour) for each piece of equipment. Becker et al. (2006) found that this procedure was sufficiently accurate at the whole system operational level. At Site I, the landowner performed FSI around crop trees only, felling, delimbing, and topping small trees down to a 4-in. dbh. The time to process used trees only was charged to the operation at the logger’s machine cost for a chainsaw. Prior to delivery to the mill, sawlogs were scaled (International 1/4-in. rule for 8or 9-ft logs) by one of the authors (Sites I and III) or the loggers (II and IV). All consumer scale weight tickets for sawlogs and smallwood were collected. Because the harvest times of sawlogs and smallwood were not separated and these products were sometimes sold by different units, volumes were converted to a common unit (green tons) for productivity analyses. Tons per thousand board feet (mbf) (International 1/4-in. rule) was calculated for each sawlog according to Doruska et al. (2006, Equation 10 for all logs of all study species, namely, oak, hickory, and sweetgum). This ratio (site averages: 5.9–6.3 tons/mbf) was multiplied by the scaled mbf per log to estimate the weight in tons, which was then summed over all sawlogs. This estimated value was just 3% greater and 2% less than the mill-measured weights of sawlogs from Sites III and IV, respectively. Machine Costs Machine costs of the harvest equipment (Table 1) were calculated according to Miyata (1980), as modified by Brinker et al. (2002, Table 2), using a spreadsheet developed by deLasaux et al. (2009). This approach provides a standard and transparent basis for time-averaging productivity and unusual expenses, as applied to a particular operation. It does, however, partially disregard the time value of money (Bilek 2008, Rummer 2008). Loggers estimated their annual repair and maintenance costs (including tire replacement) and annual productive hours (accounting for down time due to repair, service, and bad weather) of the harvest equipment without the benefit of records. For example, ranges for skidders were $3,000–$8,700 for repair and maintenance costs and 430–1,280 for productive machine hours (PMH). These inputs were the most likely sources of error in our estimation of machine costs. Equipment capital costs were allocated over time using straightline depreciation. The analysis included any equipment insurance Table 1. Harvest equipment assessed for machine cost. Site Chainsaw Skidder Loader Tractor I 2007 Stihl 441 1973 JD 440B cable 1996 Serko 800