Jose-Luis Izursa, David R. Tilley, Patrick Kangas1Animal Science/Agricultural Engineering Building, Marine, Estuarine, Environmental Science, University of Maryland, College Park, MD 074, USA

2Animal Science/Agricultural Engineering Building, Environmental Science and Technology, University of Maryland, College Park, MD 20742, USA

Sustainability Assessment of Certified Tropical Forestry using Emergy Analysis

Jose-Luis Izursa1†, David R. Tilley2, Patrick Kangas21Animal Science/Agricultural Engineering Building, Marine, Estuarine, Environmental Science, University of Maryland, College Park, MD 20742, USA

2Animal Science/Agricultural Engineering Building, Environmental Science and Technology, University of Maryland, College Park, MD 20742, USA

Sustainable forestry production systems, such as certified forestry, reduced impact logging or sustainable forest management, have become an important part of tropical countries’ strategy to oversee their forest resources. Particularly, certification of forest products has become a widely adopted practice as a response to a growing international concern over the ecological and economic sustainability of harvesting natural tropical forests because of the benefits on reducing excessive and unnecessary construction of forest roads, reducing excessive use of heavy machinery, diminishing excessive collateral damage, and improving the inefficient milling processes and wasting of residues. To accomplish the aim of this study, which is to compare conventional and certified forestry we used a systems analysis tool that could integrate various benefits of certified forestry including, stand age, wood harvest, soil losses and economic gain or loss. We found that the affected area under uncertified logging practices is twice the area of certified forestry because conventional practices require more roads, more logging decks and more skid trails. Also, the rate of soil erosion between uncertified logging (154 Mg/ha/yr) and certified logging (66 Mg/ha/yr) is different. Based on these data, we estimated that the total emergy removed from certified forests was 40% less than the forest under conventional forestry. The fact that certification does a better job of preserving forest while removing wood was also demonstrated through the Environmental Loading Ratio (ELR). We also found that certification leaves forests with a 30% better chance to recover after logging because less wood is removed. But forestry using certification showed a lower Emergy Yield Ratio (EYR) because the lower yield and the extra cost of certification. Certification is also favored for the higher price for certified wood in international markets. Then, when Bolivia exports uncertified wood, it obtains a positive benefit, but lower than using uncertified wood domestically (EYR = 20.4). In other words the worst thing the country could do is certify wood for their domestic market and sell uncertified wood abroad.

© 2014 L&H Scientific Publishing, LLC. All rights reserved.

Submission Info

Communicated by Sergio Ulgiati

Received 26 January 2014

Accepted 25 February 2014

Available online 1 April 2014

Certified forestry

Emergy

Sustainability

Energy analysis

1 Introduction

Forestry practices in tropical forests has been characterized by poor and ineffective planning and management that has involved excessive and unnecessary construction of logging roads, excessive use of heavy machinery, excessive collateral damage, inefficient milling processes and poor use of waste residues. It has also often placed too much emphasis on a few valuable species, such as mahogany (Swietenia macrophylla King), to the point where their existence is threatened (Bawa and Seidler, 1998; Rice et al., 1997). In response to international concern over these ineffective practices and lack of sustainable management (Bennett, 2001), sustainable forestry production systems, such as certified forestry or sustainable forest management (Pearce et al., 2003; Rice et al., 1997) have been developed.

Certification of forest products in tropical countries, such as Bolivia, was adopted as a means to reduce negative impacts to the forest ecosystems and as a way to find markets for less well-known tree species. According to Auld et al. (2008) forest certification is a tool with a main goal of promoting the conservation and sustainable management of forest ecosystems by adding market value to products generated according to environmental and socio-economic standards. Forest certification allows consumers to identify products that come from well-managed forests (Elliot and Donovan, 1996) since it is based on third-party auditing of compliance with environmental and socio-economic standards with participatory public processes (Brown et al., 2001). In Bolivia, the Forest Stewardship Council (FSC) standards are used for timber certification. These standards have 10 principles, each with its own guidelines which cover social, economic and environmental aspects (Putz and Romero, 2001) (Table 1). Forest certification relies on the willingness of a growing number of consumers to pay more for sustainably generated products and it aims to reward forest managers that follow sustainable forest management practices (Auld et al., 2008).

Several studies have been carried out to assess the damage to the forests and to evaluate the environmental impacts of forestry activities under different management methods. Also, efforts have been made to evaluate the differences between conventional logging activities and improved techniques, such as certified or reduced impact logging forestry (Feldpausch et al., 2005; Rockwell et al., 2007; Sun and McNulty, 1998), especially considering the financial benefits (Hanrahan and Grimes, 1997; Holmes et al., 2000). These studies showed that forestry using improved techniques was less costly, and more profitable, than using traditional forestry techniques. Results of these studies also indicate that poorly managed roads are the main source of sediment in a forested watershed and that pre-harvest skid trail planning and improved timber felling techniques yield short-term financial gains relative to conventional management as well as potential long-term gains through future crop trees (FCT) conservation and, therefore, warrant implementation.

Table 1FSC's 10 principles for forest certification

While economic analyses have been used to compare the efficiency and profitability of conventional and improved timber harvesting systems, it provides an incomplete assessment of forestry sustainability (Boltz et al., 2003; Samad et al., 2009) due to its inability to directly compare ecological and economic changes using the same metric. That is the financial costs and benefits are measured in money, while ecological benefits, if measured, are in non-monetary units like tons of soil.

Therefore, in this study we used an energy-based environmental accounting system—emergy evaluation (Odum, 1996)—that can account for changes in the ecosystem’s performance and compare it directly, using the same metric, to financial implications of forest certification. Emergy evaluation considers the ecological values of a forest by quantifying all of the energy and material inputs needed to support and create the forest (Brown and Ulgiati, 2004; Campbell, 2008; Castellini et al., 2006; Tilley and Swank, 2003). Likewise, it considers the economic values based on the energy, material and information required to operate the forestry system, including its international market. All values can be given as solar emjoules (sej), since that is the common basis of the biogeosphere. Each unit of energy, material or information that is required to operate the forestry system (i.e., joules, grams, dollars) is converted to solar emergy via its solar transformity (sej/J), specific solar emergy (sej/g) or solar emergy per dollar (sej/$), respectively. These unit emergy values (UEV’s) are often taken from previous studies, which are now centralized in an on-line database (Tilley et al., 2012). It should be emphasized that the energy inputs driving a forest are more than the solar joules—it also includes indirect sources of solar energy that have embodied solar energy, like water, minerals and wind. Thus, all necessary inputs are quantified and translated to the single metric of solar emergy so that nature’s work can be accounted.

Emergy evaluation has been used to measure environmental sustainability of several natural resource extraction endeavors, like traditional, mechanized forestry, shrimp fishing, and conventional agricultural crop production (Martin and Tilley, 2007). To our knowledge, there has not been an emergy assessment of certified tropical forestry.

The aim of this study was to compare the ecological and economic benefits of certified and uncertified tropical forestry at the scale of the forest stand and the scale of the nation. The former scale corresponds mainly to the ecological benefits, whereas the latter scale included the economic and social effects occurring in the national and international markets for tropical wood.

Specific questions addressed in this paper include as follows:

- How much difference is there in the ecological resource flows between a certified and uncertified forest stand?

- How much difference is there in the resource benefit to the consumer and investor between certified and uncertified forestry?

- How much investment is required to implement certification, relative to the extra benefits?

We used emergy evaluation to analyze the tropical forestry practices in the Amazon of Bolivia and Brazil as a prototype for tropical forestry. We responded to our research questions by looking at how the solar emergy flows were different between certified and uncertified forestry.

2 Materials and methods

2.1 System description

The forest systems analyzed were models of 1 ha of certified forest and 1 ha of uncertified forest in the Amazon. The forests were assumed to be identical in age, structure and species composition prior to logging. Emergy inputs were those associated with logging 1 ha of forest using prescribed practices.

2.2 Data sources

The data used in this study were taken from previous studies performed in the Bolivian and the Brazilian Amazon, where environmental, social and production characteristics are similar to each other (Hanrahan andGrimes, 1997; Holmes et al., 2002; Holmes et al., 2000; Jackson et al., 2002; Krueger, 2004). The productivity used for each logging system was the average of typical productivity parameters. For example, Holmes et al. (2002) mention that the standard harvest volume is 25.4 m3/ha, which we used as the average harvest volume. The different costs were computed by taking averages of daily parameter values reflecting productive activity of crews (trained workers in the case of certified logging). Labor costs were based on the standard monthly wage for each job category. Fixed equipment costs were computed on an hourly basis according to standard parameters provided by equipment manufacturers (Caterpillar, Illinois USA).

2.3 Inventory of emergy inputs

The specific inputs evaluated for certification included the environmental basis of the forestry system and its connection to domestic and foreign markets. The method used for inventorying all inputs as solar emergy was the one described by Odum (1996). To describe the main pathways affected by certification (i.e., forest production, silvicultural practices and timber prices) an energy systems diagram was created (Figure 1). The emergy input inventory was obtained by calculating the solar emergy of each environmental and humancontrolled input, according to the standard procedures with the exception of the emergy of wood harvested, which considered the emergy stored in trees at different ages (Tilley, 1999).

Fig. 1Energy systems diagram of a forest under logging operations.

Each inventory included environmental inputs, wood harvesting, impacts to soil and impact to nonharvested trees or FCT, cost of human inputs, and revenue generated from foreign and domestic sales. For the environmental inputs the solar emergy of rain was included, but not the solar emergy of sunlight to avoid double counting of the same global emergy contribution (Odum, 1996). Wood production refers to the total amount of marketable wood extracted from the forest. Soil erosion and tree damage caused during harvesting, and merchantable wood wasted during harvesting were added together as an estimate of environmental stress. Human services consisted of payment for access to the forest (concession rights and certification fees) and the costs for each component of logging (e.g., pre-harvest, harvest planning, felling and bucking, skidding and log deck operations).

Since one of the main differences between certified and uncertified forestry was the age distribution of the wood harvested, we estimated age-specific solar transformities for each age-class. In general trees and forests accumulate emergy faster than their energy content increases, which has the effect of increasing the transformity of trees and forest products as the forest ages (Tilley, 1999). First, the number of trees removed at each DBH (Diameter at Breast Height) was based on Holmes et al. (2002). Second, DBH was used to infer tree-age based on the relationship developed in Figure 2 (Baker, 2003; Korning & Balslev, 1994; Lieberman & Lieberman, 1987; Lieberman et al., 1985). Once the estimated age for trees was found, Tilley’s (1999) agespecific estimate of the solar transformity of forest trees (Figure 3) was applied to each age-class to derive a solar emergy for each age-class (Figure 4). Summing the solar emergy across age-classes provided the total solar emergy of the wood harvested. A similar technique was applied to the wood wasted during harvesting.

Fig. 2Estimated age from measured DBH (Adapted from Lieberman and Lieberman (1987)).

2.4 Emergy indices for analysis

To address questions about the sustainability of certified tropical forestry at the scales of the forest stand and the nation, we used established emergy indices. The indices were based on the flows of emergy associated with growing, harvesting, certifying, marketing and selling the timber.

Fig. 3Transformity of trees at different ages (Adapted from Tilley (1999)).

Fig. 4Emergy value of wood harvested for each age class.

To assess whether the sustainability of the forest stand was improved from certification we used the environmental loading ratio - ELR (Odum, 1996), the emergy yield ratio - EYR (Odum, 1996) and the environmental sustainability index - ESI (Ulgiati and Brown, 1998). These indices are defined diagrammatically in Figure 1. The ELR is the ratio of the sum of purchased (F) and non-renewable (WL+SL) emergy to the renewable emergy supporting the forest (R). A low ELR corresponds to a small use of outside and non-renewable resource used relative to the availability of the renewable resource. Thus, as its name implies the ELR indicates how much load, or possible impact, is placed on the local environment. The second indicator used, the EYR is the ratio of total emergy produced by the system (Y) to the emergy purchased from outside the local system (F). The EYR indicates how much resource is yielded per unit of resource invested in its extraction. A high EYR (i.e., greater than 1.0) indicates that the extraction process provides a positive return. Higher values indicate how much more positive the return is.

Table 2Emergy evaluation of uncertified logging in 1ha per year of tropical forest (see footnotes in Appendixes for detailed assumptions and calculations)

The ELR measures local impact, while the EYR measures yield. From this perspective, Ulgiati and Brown (1998) suggested the ratio of the two (i.e., yield/impact) would be a strong index of sustainability. They defined the environmental sustainability index (ESI) as the ratio EYR/ELR. Higher ESI corresponds to higher sustainability. To assess how the sustainability of national forestry improved under certification, we estimated an emergy-based ratio of balance of trade. We defined the ratio of balance of trade for the nation as the ratio of gains made in proportion to the cash revenue generated from international sales to the losses incurred due to export of logs, wood wasted during harvest and soil erosion. A ratio balance greater than 1.0 indicates a positive benefit for the nation because it is receiving more resource than it is sending out.

3. Results

The energetic basis for certified and uncertified forestry can be reduced to evaluating the main flows and stocks of solar emergy (Figure 1). Goods and services (F) from outside the system support the forestry operations and administration, and are necessary to drive the logging operations in the forest to extract timber and non-timber products. Wood products (WY) are removed from the forest for sale to domestic and foreign markets at a price (P), which generates revenue (Z). Incidental losses from the forest include soil erosion (SL) and wasted wood (WL). The inventory of emergy flows for uncertified and certified logging operations are presented in Tables 2 and 3, respectively. Both tables (whose footnotes are in the Appendixes) list the indigenous environmental resources used, the losses of environmental resources, and the services used to extract timber from the forest.

Emergy tables show how energy and mass flows are converted to solar emjoules by multiplying them by solar transformity values. These tables were prepared considering seven columns. Column 1 is the line item number and also represents the number of the footnote in the table where raw data source is cited and calculations are shown. Column 2 is the name of the item. Column 3 contains the raw data expressed in terms of energy, mass or money (joules, grams or dollars) obtained from various sources. Column 4 shows the unit onwhat the raw data is expressed. Column 5 includes transformity values in solar emjoules per unit of energy, mass or money (sej/joule; sej/gram; or sej/$). Unless calculated in this work or otherwise noted, transformities used in this manuscript were taken from different sources making the necessary adjustment from global emergy base of reference from 9.44 E24 sej/yr (for values based on the 1996 solar empower base) to 15.83 E24 sej/yr, multiplying those values (from 1996 or older) by 1.68. Column 6 is the solar emergy, the product of columns three and five. Column 7 represents the macroeconomic value expressed in macroeconomic dollars for a selected year. To obtain this, emergy value in column six was divided by the emergy-to-dollar ratio of Bolivia (BOedr) for the year 2005. BOedrwas found by dividing the gross national product by the total contributing emergy use by the combined economy of man and nature in the country for the year 2005.

Table 3Emergy evaluation of certified logging in 1ha per year of tropical forest (see footnotes in Appendixes for detailed assumptions and calculations)

More solar emergy as wood was harvested under uncertified forestry than certified forestry but uncertified lost more solar emergy as soil and wasted wood (Table 4). The emergy of wood harvested was by far the largest flow of solar emergy for both systems because the emergy of soil loss was calculated considering the soil organic matter and not the mineral soil. A large portion of the difference in the amount of solar emergy harvested as wood was due to the removals of more old trees in uncertified forestry. In certified forestry some old trees are left as seed sources. Uncertified forestry harvested more solar emergy at nearly every age class, especially in the ages greater than 300 years old (Figure 4).

The emergy for the service costs, which includes the payment for forest access fees and the human services, were similar between the systems (Table 4). On the contrary, the natural capital removed, represented by the emergy of wood removed from forest (WY), soil loss (SL) and wood loss (WL), was lower when certified logging was practiced (Table 5). Certified logging had more effort in terms of training and pre-harvest preparation, resulting in less wood wasted. Although certification implies higher cost in goods and services per hectare harvested, uncertified forestry actually used more services due to the greater amount of timber harvested. Annual solar emergy yield of timber for certified forestry was 50% lower than for uncertified (Table 4).

Table 4Summary of emergy flows for uncertified and certified logging (1 ha)

3.1 Comparison at forest boundary

At the smallest scale of analysis, which was the forest, we compared the two forestry systems based on 1) how much total natural capital was removed, 2) how much natural capital was wasted, and 3) what percentage of the natural capital was a waste of the total timber yield. By each of these indicators, certified forestry had less impact on the forest than uncertified forest. Certified forestry removed less (153E15 sej/ha) natural capital compared to uncertified forestry (248E15 sej/ha). In absolute terms, certified forestry wasted less (4.3E15 sej/ha) natural capital than uncertified forestry (11.7E15 sej/ha). Also, certified forestry wasted less natural capital per timber harvested (3%) than uncertified forestry (5%) (Table 5).

How much difference is there in the ecological resource flows between a certified and uncertified forest stand?

Certified forestry removed 38% less natural capital from the forest than uncertified forestry (Table 5). The vast majority of the natural capital removed was in the form of timber (95% for certified and 97% for uncertified), whereas the other removal was due to soil erosion and wasted wood. Since certified lost only 3% of its natural capital to erosion and waste and uncertified lost 5%, certified was 40% more efficient than uncertified (Table 5). In total, certified forestry wasted 63% less natural capital than uncertified (Table 5). Thus, certified forestry took less and wasted less than uncertified forestry.

Uncertified forestry was less selective about the age of the trees, taking a much broader range of ages than certified. However, the mean solar transformity of the harvested timber between the two strategies was identical (～345,000 sej/J, Table 5).

The ELR for certified forestry (27.8) was 36% lower than for uncertified (43.6) (Table 5), indicating that certified forestry caused less potential impact on the ability of the forest to recover from the harvest. However, an ELR of 27.8 for certified forestry is quite high indicating that the harvesting process, whether certified or not, is damaging to the forest over the short term.

3.2Comparison at National Boundary

At the larger scale of analysis, which was done for the whole country of Bolivia, we compared the two forestry systems based on 1) Gross Emergy Yield Ratio, 2) Net Emergy Yield Ratio, and 3) Net Balance of Trade in Wood (Table 5). We found that the national benefit of implementing an international forestry certification program was sensitive to how much revenue was generated due to the export of certified wood. The Gross Emergy Yield Ratio and Net Emergy Yield Ratio, which did not consider export revenue, were greater for theuncertified forestry because the emergy imported to implement certification (F in Table 4) was more than the value of the wood yield relative to how much emergy was imported from outside to administer and operate the forestry system. Absence of an international export market for certified wood means that Bolivian forestry could provide more total benefit to the nation without implementing an international certification program. However, since certified timber commanded a price nearly double that of uncertified wood (P in Table 4), Bolivian forestry could attain more benefit for the nation by implementing an international forest certification program.

Table 5Emergy-based indicators of uncertified and certified logging (1 ha)

ELR, on the other hand, shows that the non-renewable part of the emergy is 2.6 and 3.4 times higher than the renewable part for uncertified and certified logging respectively.

How much difference is there in the resource benefit to the consumer and investor between certified and uncertified forestry?

The EYR for certified forestry (12.4) was 31% less than uncertified forestry (18.1), indicating that the yield to the economy per level of investment was not as good with certification (Table 5). From an economic perspective a higher EYR is desirable because it indicates that more is gained for less investment. However, it does not provide information about impact on the forest; it only quantifies the economic gain. Accounting for losses due to soil erosion and wasted wood changed the EYR’s slightly to 11.6 and 17.2 for certified and uncertified, respectively, but did not significantly change their relative differences (Table 5). Since timber accounts for the main flow of solar emergy in the forests’ yield, including soil and wood losses did not have much affect on the EYR.

How different is the ecological-economics between certified and uncertified forestry?

The ESI attempts to capture the trade-offs between the efficiency of the economic gain (i.e., EYR) and its environmental impact (i.e., ELR) by taking the ratio of the two indices. Based on this index, certified forestry was 7.5% more sustainable than uncertified (Table 5). However, given the inherent variability involved in all of the parameters needed to ultimately estimate the ESI, it is likely that 7.5% is close to the margin of error. Amore thorough, future study should incorporate one of the techniques for conducting a sensitivity analysis to estimate uncertainty in emergy evaluations (Hudson and Tilley, 2013; Ingwersen, 2010).

We found that the most important ecological-economic benefit from certification came, not from the ecological benefits to the forest, but rather from a more favorable trade exchange. When measured in solar emergy, certified forestry allowed the producing nation to receive 11.8 times as much emergy from the buying power of the revenue as it gave up in timber and incidental losses in natural capital (i.e., soil and wasted wood) (Table 5). This “Balance of Trade in Wood” was only 6.2 under uncertified forestry, which signified that tropical countries with large forests, such as Bolivia, can benefit from certification when certified wood is sold to foreign markets at higher prices than uncertified wood. Otherwise, the extra investment for forest certification would not be wise because the net emergy yield (Ynet) per investment was higher for uncertified forestry. However, given that a higher price is garnered for certified wood in international markets, the emergy value of Bolivia’s Balance of Trade in Wood was nearly double what it was under uncertified. In other words the wrong action for a forested nation would be to certify wood for their domestic market and sell uncertified wood abroad.

4 Discussion

Uncertified forestry placed a larger load on the forest environment than certified because it 1) removed more forest emergy, 2) yielded less wood per forest emergy removed and 3) had a higher ELR. Uncertified forestry wasted more wood, harvested more wood and eroded more soil than certified forestry. However, both types of forestry had large ELR compared to other types of agricultural activities. For example, Ulgiati et al. (1994) estimated an ERL of 2.5 for Italian agriculture (Martin and Tilley, 2007).

Although certified forestry represented a lower environmental impact, the ratio of net emergy yield (Ynet) per ha was higher than uncertified. The reason why certified forestry costs more per ha is because of the less trees harvested and the extra fees paid for certification, which decrease net emergy yield ratio.

To compare how much timber is obtained with a given quantity of emergy using both forest harvesting techniques (uncertified and certified), we used transformity values. Although certified forestry or other improved forest management systems are considered more beneficial to the local economies and the environment, in terms of emergy, the uncertified logging system requires less emergy in the process (Tables 2 and 3). This can be explained because certified forests employ qualified labor and training during the harvest planning phase, and requires the payment of certification fees. Considering that the total emergy is the sum of all local and external emergy inputs, the higher the ratio, the higher is the relative contribution of the local (renewable and non-renewable) sources of emergy to the system.

The ratios calculated in our study show that certified forestry removes and wastes less natural capital compared to uncertified forestry (Table 5), corroborating studies i.e., Holmes et al. (2002), which confirm that certification cost less and it is a more profitable practice.

Consideration of age and growth rates of future crop trees was essential for this study, as it is for the planning of sustainable forestry in tropical forests. Despite the vastness and high species richness of Bolivia’s Amazonian rainforest, little is known about the age of the trees there. Extrapolated data from short-term growth trend studies by authors such as Baker (2003) were considered. Baker studied the Macaranduba tree (Manilkara huberi - Ducke) which belongs to the Sapotaceae family as the average tree for its closeness in phenotype and environmental requirements to most of the species harvested in the Amazon.

Although the indices calculated in this study, as part of emergy analysis, allowed us to answer the proposed questions, there is one aspect that remains unsolved and it is the measurement of stress on biodiversity. Is the law that rare species and wildlife will be better protected and hunting is not allowed on certified forestlands, except in justified cases in relation to indigenous people. However, results on how much the certification reduces the damage to the biodiversity compared to uncertified forestry, has not been measured yet.

5 Conclusions

The emergy evaluation of certified tropical forestry demonstrated that the forest ecology was better off under certification, mainly due to reductions in total timber removed, timber wasted, and soil lost as erosion. However, the national economic benefit depends on the international price for certified wood. The comparison of one hectare of tropical forest under uncertified logging practices and one hectare under certified ones showed that certified forestry removed less emergy than uncertified forestry and had a better wood yield per forest emergy removed index than uncertified forestry. Certified forest had less impact per unit of regeneration capacity than uncertified forestry offering to certified forests a better chance of recovering after logging. Certified practices showed a lower emergy yield ratio because the lower yield and extra cost of certification. The higher price for certified wood in international markets favored certification. In order to evaluate the benefits of each system towards the environmental sustainability, additional research is required to measure the effect of forest certification over the biodiversity.

Appendix A

Footnotes to Table 2: Emergy evaluation of uncertified logging in 1ha per year of tropical forest, 2005

1Sunlight, J

Annual energy = (Avg. Total Annual Insolation J/yr)(1-albedo)(4186 J/Kcal)

Insolation: 1.27E+06 Kcal/m^2/yr (Odum and Arding, 1991)

Forest land: 10,000 m^2

Albedo: 0.30 Fraction absorbed at surface (Barry and Chorley, 1992)

Annual energy: 3.72E+13 J

Emergy per unit input = 1 sej/J

2Rain Chemical, J

Annual energy = (Forest land)(1000 kg/m^3)(Gibbs free energy 4.94 J/g)

Forest land: 10,000 m^2

Rainfall: 3.88 m/y (SENAMHI, 2006)

Annual energy: 1.92E+11 J

Emergy per unit input = 3.05E+04 sej/J (Odum, 2000)

3 Wood harvested, J

Biomass = (Volume)(1E+06 g/m^3)(0.5 g dry wt/g green wt)(19,200 J/g dry wt)

Average height = 40 m (Oliveira et al., 2005)

Age: For trees with DBH 0.40 to 1.10 m, age was estimated based on DHB/age measurements for canopy species in La Selva, Costa Rica using stochastic simulation technique developed by Lieberman and Lieberman (1987) and Lieberman et al. (1985).

For trees with DBH 1.10 to 1.70 m, age was extrapolated from plotted data for 0.40 to 1.10 DBH data (Lieberman & Lieberman, 1987) using equations generated on Excel ®: For minimum estimated age: y = -3E-05x2 + 0.225x - 2.7273 and for maximum estimated age: y = 196.37Ln(x) - 862.03

Transformity: Estimations based on results of simulation using EMERGYDYN (Tilley, 1999)

4Soil erosion, J

Annual energy = (Area disturbed)(Soil loss Mg/ha/yr)(1E6 g/Mg)(% OM)(5.4 Kcal/g)(4186 J/Kcal)

Soil loss = 154 Mg/ha/yr (Sun and McNulty, 1998)

Average organic content = 3 %

Annual energy: 1.04E11 J/yr

Emergy per unit input of SOM = 7.40E+04 sej/J (Brown and Bardi, 2001)

5Wood loss, J

Source of wood wasted

a High stumps 0.28 m^3/ha

b Split logs 0.87 m^3/ha

c Bucking waste 1.97 m^3/ha

d Logs lost 0.96 m^3/ha

e Total in forest (a+b+c+d) 4.08 m^3/ha

f Total in log deck 1.97 m^3/ha

g Subtotal (e+f) 6.05 m^3/ha

h FCTs killed during felling 5.49 m^3/ha

i FCTs killed in skid trailing 2.01 m^3/ha

j Subtotal (h+i) 7.50 m^3/ha

Total (g+j) 13.55 m^3/ha

Annual energy = (Wood wasted m^3)(1E+06 g/m^3)(0.5 g dry wt/g green wt)(19,200 J/g dry wt)

Average log volume: 3.66 m^3/tree (Krueger, 2004)

Annual energy: 1.30E+11 J

Emergy per unit input = 2.76E+04 sej/J (Izursa, 2008)

6Access costs, $

Annual energy = (Cost of concession $/ha)+(Payment for certification $/ha)

Cost of concession: 20.00 $/ha (UDAPE, 2005)

Cost of certification: 0.00 $/ha

Cost of access: 20.00 $/ha

Emergy per unit input = 3.31E+13 sej/$ (Izursa, 2008)

7Services, $

Activity (Holmes et al., 2000)

Pre-harvest 0.00 $/m^3

Harvest planning 0.14 $/m^3

Infrastructure 0.57 $/m^3

Felling and bucking 0.49 $/m^3

Skidding 1.99 $/m^3

Log deck operations 2.01 $/m^3

Waste adjustment 0.40 $/m^3

Stumpage cost 9.09 $/m^3

Training 0.00 $/m^3

Overhead/support 0.97 $/m^3

Total 15.66 $/m^3

Annual energy = (Cost of services $/m^3)(m^3/ha)

Harvest: 25.36 m^3/ha (Holmes et al., 2000)

Cost of services: 397.14 $/ha (Holmes et al., 2000)

Emergy per unit input = 3.31E+13 sej/$ (Izursa, 2008)

8Uncertified timber output, J

Annual energy = (Uncertified timber harvested m^3)(650 kg)(1E3 g) (3.5 Kcal/g)(4186 J/Kcal)

Total trees harvested: 76.46 m^3 (Holmes et al., 2000)

Output of logs = 7.28E+11 J

9Uncertified timber output, g

Annual energy = (Uncertified timber harvested m^3)(650 kg)(1E3 g) (3.5 Kcal/g)

Total trees harvested: 76.46 m^3 (Holmes et al., 2000)

Output of logs = 1.74E+08 G

10Timber output transformity, sej/J

Timber output transformity = (output energy of logs, J)/(sum of 2+6+7-4-5)

11Timber output transformity, sej/g

Timber output transformity = (output energy of logs, g)/(sum of 2+6+7-4-5)

Price of uncertified wood 254.24 $/m^3 (Hanrahan and Grimes, 1997)

Bolivia GDP 2.58E+10 $ (Izursa, 2008)

Bolivia, Total emergy used 8.55E+23 sej/y (Izursa, 2008)

Appendix B

Footnotes to Table 3: Emergy evaluation of certified logging in 1ha per year of tropical forest, 2005

1Sunlight, J

Annual energy = (Avg. Total Annual Insolation J/yr)(1-albedo)(4186 J/Kcal)

Insolation: 1.27E+06 Kcal/m^2/yr (Odum and Arding, 1991)

Forest land: 10,000 m^2

Albedo: 0.30 Fraction absorbed at surface (Barry and Chorley, 1992)

Annual energy: 3.72E+13 J

Emergy per unit input = 1 sej/J

2Rain Chemical, J

Annual energy = (Forest land)(1000 kg/m^3)(Gibbs free energy 4.94 J/g)

Forest land: 10,000 m^2

Rainfall: 3.88 m/y (SENAMHI, 2006)

Annual energy: 1.92E+11 J

Emergy per unit input = 3.05E+04 sej/J (Odum, 2000)

3Wood harvested, J

DBH # Trees Age Volume Biomass Transformity Emergy (m) (ind/ha) (yrs) (m^3) (J) (sej/J) (sej) 0.40 0.27 215 0.95 9.12E+09 215,000 1.96E+15 0.50 0.25 245 1.37 1.32E+10 250,000 3.30E+15 0.60 0.81 255 6.41 6.16E+10 260,000 1.60E+16 0.70 0.90 278 9.70 9.31E+10 275,000 2.56E+16 0.80 0.84 294 11.82 1.13E+11 290,000 3.29E+16

0.90 0.41 313 7.30 7.01E+10 320,000 2.24E+16 1.00 0.20 328 4.40 4.22E+10 332,000 1.40E+16 1.10 0.14 369 3.73 3.58E+10 364,000 1.30E+16 1.20 0.04 420 1.27 1.22E+10 400,000 4.86E+15 1.30 0.03 443 1.11 1.07E+10 425,000 4.55E+15 1.40 0.03 466 1.29 1.24E+10 448,000 5.56E+15 1.50 0.02 488 0.99 9.50E+09 460,000 4.37E+15 1.60 0.00 510 0.00 0.00E+00 470,000 0.00E+00 1.70 0.00 533 0.00 0.00E+00 485,000 0.00E+00 Total 5.73 50.35 4.83E+11 307,435 1.49E+17

Volume = (0.7854)(DBH^2 m)(shape factor 0.70)(height m)(# of trees/ha) (González and Cruz, 2004)

Biomass = (Volume)(1E+06 g/m^3)(0.5 g dry wt/g green wt)(19,200 J/g dry wt)

Average height = 40 m (Oliveira et al., 2005)

Age: For trees with DBH 0.40 to 1.10 m, age was estimated based on DHB/age measurements for canopy species in La Selva, Costa Rica using stochastic simulation technique developed by Lieberman and Lieberman (1985) (Lieberman and Lieberman, 1987).

For trees with DBH 1.10 to 1.70 m, age was extrapolated from plotted data for 0.40 to 1.10 DBH data (Lieberman and Lieberman, 1987) using equations generated on Excel ®: For minimum estimated age: y = -3E-05x2 + 0.225x - 2.7273 and for maximum estimated age: y = 196.37Ln(x) - 862.03

Transformity: Estimations based on results of simulation using EMERGYDYN (Tilley, 1999)

4Soil erosion, J

Annual energy = (Area disturbed)(Soil loss Mg/ha/yr)(1E6 g/Mg)(% OM)(5.4 Kcal/g)(4186 J/Kcal)

Soil loss = 66 Mg/ha/yr (Sun and McNulty, 1998)

Average organic content = 3 %

Annual energy: 4.48E9 J/yr

Emergy per unit input of SOM = 7.40E+04 sej/J (Brown and Bardi, 2001)

5Wood loss, J

Source of wood wasted

a High stumps 0.10 m^3/ha

b Split logs 0.31 m^3/ha

c Bucking waste 0.85 m^3/ha

d Logs lost 0.06 m^3/ha

e Total in forest (a+b+c+d) 1.32 m^3/ha

f Total in log deck 0.60 m^3/ha

g Subtotal (e+f) 1.92 m^3/ha

h FCTs killed during felling 1.83 m^3/ha

i FCTs killed in skid trailing 0.00 m^3/ha

j Subtotal (h+i) 1.83 m^3/ha

Total (g+j) 3.75 m^3/ha

Annual energy = (Wood wasted m^3)(1E+06 g/m^3)(0.5 g dry wt/g green wt)(19,200 J/g dry wt)

Average log volume: 3.66 m^3/tree (Krueger, 2004)

Annual energy: 3.60E+10 J

Emergy per unit input = 2.76E+04 sej/J (Izursa, 2008)

6Access costs, $

Annual energy = (Cost of concession $/ha)+(Payment for certification $/ha)

Cost of concession: 20.00 $/ha (UDAPE, 2005)

Cost of certification: 35.67 $/ha (CFB, 2007; CFV, 2006)

Cost of access: 55.67 $/ha

Emergy per unit input = 3.31E+13 sej/$ (Izursa, 2008)

7Services, $

Activity (Holmes et al., 2000)

Pre-harvest 1.18 $/m^3

Harvest planning 0.16 $/m^3

Infrastructure 0.59 $/m^3

Felling and bucking 0.62 $/m^3

Skidding 1.24 $/m^3

Log deck operations 1.28 $/m^3

Waste adjustment 0.09 $/m^3

Stumpage cost 7.61 $/m^3

Training 0.21 $/m^3

Overhead/support 0.86 $/m^3

Total 13.84 $/m^3

Annual energy = (Cost of services $/m^3)(m^3/ha)

Harvest: 25.36 m^3/ha (Holmes et al., 2000)

Cost of services: 350.98 $/ha (Holmes et al., 2000)

Emergy per unit input = 3.31E+13 sej/$ (Izursa, 2008)

8Certified timber output, J

Annual energy = (Certified timber harvested m^3)(650 kg)(1E3 g) (3.5 Kcal/g)(4186 J/Kcal)

Total trees harvested: 50.35 m^3 (Holmes et al., 2000)

Output of logs = 4.79E+11 J

9Certified timber output, g

Annual energy = (Certified timber harvested m^3)(650 kg)(1E3 g) (3.5 Kcal/g)

Total trees harvested: 50.35 m^3 (Holmes et al., 2000)

Output of logs = 1.15E+08 g

10Timber output transformity, sej/J

Timber output transformity = (output energy of logs, J)/(sum of 2+6+7-4-5)

11Timber output transformity, sej/g

Timber output transformity = (output energy of logs, g)/(sum of 2+6+7-4-5)

Price of certified wood 466.10 $/m^3 (Hanrahan and Grimes, 1997)

Bolivia GDP 2.58E+10 $ (Izursa, 2008)

Bolivia, Total emergy used 8.55E+23 sej/y (Izursa, 2008)

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†Corresponding author.

Email address: jlizursa@gmail.com (J.L. Izursa).

ISSN 2325-6192, eISSN 2325-6206/$- see front materials © 2014 L&H Scientific Publishing, LLC. All rights reserved.

10.5890/JEAM.2014.03.006