Along with design, management considerations are vital for ensuring that the ENs function optimally. Such management includes using correct fire regimes, grazing densities and controlling invasive plants, to ensure availability of high quality habitat. Using grasshoppers as sensitive indicators, management of the ENs was found to be three to five times more important than EN design (Bazelet and Samways 2011). This means that all the expense and time put into designing and setting up ENs can be undone if ENs are not managed correctly.

Using the correct fire regimes, grazing densities and the clearing of invasive plants are the three most important management considerations for the ENs to work correctly. Fire regimes are critically important for grasslands and need to simulate natural fire regimes as closely as possible (O’Connor et al. 2004). The simulation of natural fire regimes is also important to savanna and fynbos, although fire intervals are usually longer in these biomes. This management technique is often problematic in timber production areas, as fire is a major risk to plantations (Kirkman and Pott 2002). Because of this, managers in fire prone areas tend to burn entire ENs too early, so essentially using the ENs as fire breaks. The consequences of continuous annual burning are not fully understood, but generally it seems that it is not ideal for biodiversity and it would be better to rest the land occasionally (Chambers and Samways 1998; Uys et al. 2004). This would require fire protection zones to be set up next to the plantations, requiring bigger corridors to accommodate them. In fact, bigger corridors would allow half the corridors to be alternately burned between years and so have fire protection value allowing more space to bring fires under control, while being easier to manage, as well as being more accommodating for

biodiversity (Fig. 10.6). An alternative to annual burning of ecological corridors would be to alternate it with prescribed burning operations within plantation blocks where this is possible (e. g. semi-mature plantations).

A way to reduce the fuel load is to allow grazing on the ENs. Ideally native fauna should be used (Fig. 10.7). However, in areas where this is not an option, domesticated animals could be used, as long as their densities are controlled (Fynn and O’Connor 2000). Where fire and grazing are not available as realistic options, then mowing has been shown to have some success for at least grasshopper diversity (Chambers and Samways 1998).

Invasive plants are to some degree controlled in grasslands by fire and grazing. If invasive plants are allowed to take over corridors then they lose their ecological value and essentially become transformed areas themselves (Magoba and Samways 2011). This can lead to the breakdown of connectivity and of the optimal function­ality of the EN.

The effectiveness of ENs within the South African timber industry has been assessed for a wide range of different organisms from the habitat base of plants, through to large mammals and birds (Joubert 2011). Much of this research has been based on arthropods, as they are small, hyperdiverse, habitat sensitive, resource dependent, ecologically important and can be sampled in large numbers (Bazelet 2011; Pryke and Samways 2011). Although there is much variation among these groups, they all benefit from ENs, provided that the ENs are well designed (corridors wide enough and all landscape feature are considered) and good quality habitat is maintained (Figs. 10.6 and 10.7).

Methods that require a person or team of people physically working on the ground measuring physical quantities are described as terrestrial inventory. A wide array of methods from, traditional tape measurements and clinometers, to sophisticated electronic laser equipment is currently available for forest assessment. Examples of such work can be found in Seidel et al. (2012).

Inventory requires a proper sampling plan, which includes the aim or result of the measurement, error tolerance, sampling procedure, available budget, trained people and equipment. The required result will determine the error margin, which will dictate the intensity of the sample for each method selected. The method selected
will determine the equipment selected, which will indicate the size and level of training of the person or team. Finally, the available budget will have an influence on the detail of outcome, as well as the intensity of the inventory and the error of the result.

This section will focus on an overview of methods used with references to texts that provide detailed discussions on each of the methods.

The most extensive undifferentiated woodlands are the teak and acacia woodlands. The so called Zambezi teak woodland is dominated by the Baikiaea plurijuga
that occurs in the Kalahari sands especially associated with head waters of the Upper Zambezi and Okavango rivers (Timberlake et al. 2010). Other species associated with Baikiaea include Pterocarpus angolensis, Guibourtia coleosperma and Schinziophyton rautanenii (mungongo). Within the Zambezi teak forest, are five woodland sub-types distinct in species composition; (i) Guibourtia woodland, (ii) Burkea-Erythrophleum woodland (iii) Burkea-Diplorhynchus scrub (iv) Diplorhynchus scrub and (v) Parinari suffrutex savanna. The dominance of species varies from one sub-type to another. However, Amblygonocapus andongesis, Baikiaea plurijuga, Brachystegia floribunda, B. longifolia, B. spiciformis, Burkea africana, Combretum spp, Cryptosepalum exfoliatum ssp. pseudotaxus, Dialium engleranum, Erythrophleum africanum, Guibourtia coleosperma, Isoberlinia angolensis and Parinari curatellifolia seem to be associated with dominance from one sub-type to another. In the drier southeastern parts of the warm dry forest region, open mixed acacia woodlands, dominated by Acacia species (A. nigrescens, A. nilotica, and A. gerrardii) and Combretum are found. Other species include Burkea africana, Terminalia sericea, Kirkia acuminata, Pseudolachnostylis maprouneifolia, Sclerocarya birrea and Zizyphus mucronata. It is floristically richer than either miombo or mopane woodland and are more easily defined by the absence of miombo or mopane dominants (Geldenhuys and Golding 2008).

When applying mechanised processing, residues (i. e., branches and tops) should be dropped in piles that can be collected easily and efficiently. Although over consid-

eration of this can decrease harvester productivity as trees have to be turned and positioned over the pile (Nurmi 2007). Fewer larger piles also reduces the degree of contamination. While piles can be left on site for a winter (i. e., summer rainfall zone) to promote nutrient recycling through foliage loss, it is more rational to extract the residues to roadside landing while the forwarder is on site. For guidelines on the potential impact on the nutrient status of sites through this practice and the potential nutrient content of the various portions of forest residues, refer to Chap. 5.

Efficient extraction is highly dependent on load density, which has led to the development of extendable load beds on forwarders. Even so, achievable loads are under 50 % of mass pay-load capacity of the forwarder and longer extraction distances make collection infeasible. Laitila et al. (2005) showed a cost reduction of 10 % using an innovative combination of simultaneous residue recovery and site preparation by utilizing a forwarder fitted with disk scarifiers.

The compression of harvesting residues into bundles (e. g., slash bundling) in the stand remains in use to a limited degree but hasn’t realized the expected economic benefits (Karha and Vartiamaki 2006). In-field bundling does require a specialized base machine (e. g., forwarder) on which the bundling unit (e. g., the John Deere B380) is mounted. In an Australian study, slash was windrowed with an excavator, which resulted in good bundler productivity (21 bundles of 570 kg per productive machine hour), but was expensive and resulted in a high level of soil contamination (8.9 %) (Ghaffariyan et al. 2011). In-field bundling also requires forwarding to roadside, implying that it needs to be carried out in conjunction with the extraction of roundwood, or a forwarder must return to the site. Bundling units can also be mounted on trucks, giving greater mobility but requiring residues to be brought to roadside. When FT harvesting is done using skidders or cable yarders, this material is simultaneously extracted to roadside. Mobile truck mounted bundlers show good potential in serving numerous production points (Spinelli and Magagnotti 2009). These units are however restricted to roadside operations.

Following pretreatment, hydrolysis and transformation of sugars into biofuels is carried out, generally by fermentation. As mentioned before, enzyme-based processes are preferred due to their high specificity under milder conditions with no formation of toxic compounds. The main enzymes involved in the hydrolysis of polysaccharides are cellulases and hemicellulases, which belong to the glycosyl hydrolase family (http://www. cazy. org/).

Cellulases, mainly derived from fungi such as Trichoderma reesei, consist of a mixture of several enzymes that act synergistically to facilitate cellulose degradation. The core enzymes of cellulases are endoglucanase (EG, endo-1,4-"- glucanohydrolase, or EC 3.2.1.4), exoglucanase (CBH, 1,4-"-glucan cellobiohydro — lase) and "-glucosidase (EC 3.2.1.21) and decompose the substrate in a stepwise manner. EG acts on amorphous regions of cellulose, creating free chain-ends that are further hydrolysed by CBH releasing cellobiose units, which are cleaved into glucose by the "-glucosidase.

Hemicelluloses are normally solubilised during pretreatment into monomers and oligomers with different degrees of polymerization. In other pretreatments such as AFEX, both celluloses and hemicelluloses remain in the pretreated material. Therefore, hemicellulases are necessary for conversion into monomeric sugars. Furthermore, these enzymes enhance cellulose hydrolysis by removing residual hemicelluloses from the fibres and reducing the inhibitory effect of the xylo — oligosaccharides (Qing et al. 2010). The complex structure of hemicellulose requires several enzymes to complete its hydrolysis, but they can be broadly classified as xylanases and mannanases (Gfrio et al. 2010).

The addition of other enzymes that affect lignin (peroxidases, oxidases, and laccases) have been also recommended as part of biochemical pretreatment to reduce lignin content (Wang et al. 2012) or to facilitate detoxification of pretreated materials prior to enzymatic hydrolysis and fermentation (Moreno et al. 2012).

Enzyme production and application has been estimated to be one of the main con­tributors to the cost of second generation ethanol production (Klein-Marcuschamer et al. 2012). Cellulases have lower specific activity than amylases used in first generation ethanol production, thus increasing enzyme dosage requirements. The enzyme loading for optimal conversion is determined by the type of feedstock used, pretreatment technology applied, pretreatment severity and solid concentration. Apart from optimization of pretreatment, different strategies are implemented to reduce enzyme loadings. These strategies include the development of robust enzyme producers, the improvement of existing enzyme systems and bioprospecting of new enzymes (Banerjee et al. 2010; Huang et al. 2011). Regarding the enzymatic process, the construction of tailor-made enzyme combinations adapted to feedstock and pretreatment and/or the addition of additives such as surfactants enhances the yield of enzymatic hydrolysis while reducing cellulase requirements. Moreover, surfactant addition could favour enzyme recycling (Tu and Saddler 2010).

Fuelwood is still the predominant source of primary energy in most of the developing world. It is estimated that only 10 % of wood removals in Africa are used for industrial roundwood, while the rest is used as fuelwood. Africa accounts

for 33 % of the global fuelwood removals and only 5 % of the global industrial wood removals (FAO 2011). In Ethiopia for example, 93 % of households use open fires for cooking, while burning firewood, charcoal, crop residue and animal dung (Friends of the Earth 2010).

It is predicted that by 2030 biomass energy will still account for more than 75 % of total residential energy in Africa and that the region will have surpassed China and South Asia in terms of quantities of fuelwood used. More than 500 million people in Africa were relying on biomass as a primary source of energy in 2000 and it is projected that this number will rise to more than 800 million by 2030 as seen in Table 9.1 (IEA 2002, ex Arnold et al. 2003).

The high rate of fuelwood use in developing countries as described above can be linked to poverty and the cost of alternative fuels. In many countries fuelwood collection is the only affordable energy option and can also serve as a source of income for the poor. Despite the link between fuelwood use and income, it is interesting to note that fuelwood shortages and associated increases in collection efforts are not seen as priority problems amongst rural people and that they are more concerned with aspects related to income, health and food security (Arnold et al. 2003). It is therefore necessary to look at how people combine fuelwood and other energy sources in areas where there is a transition from traditional fuelwood to alternative energy, to understand new energy adoption patters and processes.

Especially when assessing the environmental burdens associated with the produc­tion of bioenergy and related products, particular focus should be given to the impact due to land-use change.

Land-use, depending on the land management practices, can be accepted as the main cause of soil degradation. Perennial crop systems, such as SRC plantation systems, tend to accumulate soil organic carbon and can serve to remediate contaminated soil (Brandao et al. 2010). Land-use change to bioenergy production can occur in two ways: (i) directly, when uncultivated land and pasture are converted to produce energy crops, or (ii) indirectly, through displacing food and feed crop production to new land areas previously not used for cultivation. From an LCA perspective, direct land-use change is often straightforward and easy to include in the assessment (Reijnders and Huijbregts 2008), although there are often uncertainties in the levels of carbon stock changes due to variations in local conditions and a lack of reliable field trial data (Fig. 11.2).

Mills et al. (2005) define six factors affecting the accumulation of carbon within an ecosystem:

• Carbon (C) storage is a function of mean annual precipitation (MAP) and temperature. Soil carbon and tends to increase with an increase in mean annual precipitation (Dalal and Mayer 1987; Hontoria et al. 1999). This is most likely due to primary productivition being a function of rainfall (Knapp and Smith 2001) and organic matter inputs into the soil tend to be greater in mesic than in arid regions.

• Carbon storage will increase with an increase in woody biomass.

Cs : permanent C loss in living biomass

Cs : permanent C loss in litter and soil

• Frequent fires will lead to a decrease in Carbon storage in both biomass (Tilman et al. 2000) and soils (Bird et al. 2000).

• Tillage will reduce Carbon storage in biomass and soils (Tiessen et al. 1992; Gregorich et al. 1994; Aslam et al. 2000; Francis et al. 2001).

• The establishment or maintenance of a permanent cover of vegetation (e. g. pasture, thicket) will maintain or increase soil Carbon (Dalal and Chan 2001; Dominy and Haynes 2002). The effect of pasture establishment on the organic carbon storage capacity depends on the structure of the natural vegetation. Pastures may accumulate more carbon than natural grassland if a dense grass sward is established, but will have less carbon than woody systems.

• Any of the above effects will be dependent on changes to, and the inherent chemical and physical properties of the soil (Oades 1993; Zech et al. 1997; Percifal et al. 2000). The establishment of plantations on former grassland, for example, may be expected to reduce soil water content, improve soil aeration, and therefore reduce soil carbon storage (Birch 1958).

The possible change of carbon storage pools in the forest (i. e. trees, soil and litter) brought about by removing wood from forests should be considered, at least as a qualitative description (Schlamadinger et al. 1997). The most important carbon source in forest ecosystems are living vegetation (trees and other vegetation), dead organic matter and the forest soil (Jungmeier et al. 2003). In interpreting the carbon cycle, it is important to consider the following aspects: assumed rotation period of the forest ecosystem, changes to carbon storage pools, landfill by wood-based waste, and recycling (Fig. 11.3).

Increasing applications of combined remote sensing techniques are evidence that integrated approaches are viable options if good accuracies in biomass estimation should be combined with high efficiency. Due to the increasing need for and importance of fusion of multi-modal remote sensing (LiDAR and multispectral imagery) to improve and scale estimates, we present a case study for forest plantations. The selection of an appropriate LiDAR canopy height sample, as representative of the entire study area, was a central focus of this study. The proposed scheme would use LiDAR transects instead of a blanket coverage with the aim of reducing costs and processing time, while maintaining prescribed levels of accuracy and precisions (Hudak et al. 2002). The remainder of the forest area to be inventoried would then be assessed using IKONOS imagery, based on established LiDAR-IKONOS height relationships.

The study was conducted in the Kwazulu-Natal province located in eastern South Africa. The sampled plantation stands are located approximately 50 km south of the town of Pietermaritzburg. The area is known locally as the southern Natal midlands. Rain falls predominantly in the summer months with cold dry winters and warm wet summers.

Mean annual rainfall ranges from 746-1,100 mm (Schulze 1997) and is associ­ated with either frontal systems originating from the south or from thunderstorms generated from convection activity. Temperatures range from 20 ° C in summer to below 10 °C in the winter.

Extreme temperature changes are a function of altitude and proximity to the warm Indian Ocean. Soils in the area are characterized by fine sandy clay and humic topsoils, underlain by yellow or red apedal subsoils. The topography of the study area is flat with undulating hills and is classified by Schulze (1997) as being low mountains. Altitude ranges from 362 m aml to over 1,500 m aml with an average altitude of approximately 874 m aml.

This silvicultural system is appropriate when harvesting firewood for the charcoal industries (Shackleton and Clarke 2007). Since a large area is cleared the system results in the highest rate of regrowth of the three systems. This is because the stumps of most miombo trees have the ability to produce coppice shoots once they are cut (Boaler and Sciwale 1966; Strang 1974). It tends to produce rapid regeneration that can be managed according to the product requirement. Additionally, the system provides for maximum light for light woodland demanding species. However, the system will yield very low levels of shade tolerant species in the early stages of woodland recovery. In Malawi, research has shown that the best woody regrowth after felling is obtained after clear cutting (Werren et al. 1995). This is therefore the best way of encouraging regeneration from stumps and suppressed saplings. However, this management technique is unsuitable for large areas, steep slopes, or in riverine vegetation because of the increased erosion which occurs in the first years after cutting. Chidumayo et al. (1996) have advocated the use of shelterbelts in sensitive areas that are especially demarcated across the slope. Once leaf-area development in coupes reaches the pre-felling level, which usually takes 10 years or more, the shelterbelts may be cleared while the regrowth strips act as shelterbelts.

The choice of an ‘optimal’ form of transport for a planned bioenergy plant is not always straightforward, and will depend on whether the enterprise already transports, e. g., pulp chips, whether all transport is to be outsourced, and whether a small or large scale operation is planned. However, some consistencies in making a rudimentary evaluation do exist. If the conversion plant is to be located alongside an existing sawmill in a plantation area, it could be acceptable to use an off-road agricultural tractor/trailer system where the typical distance is under 15 km, while if the intention is to supply a central heating plant in the next city, sophisticated haulers are required. Transport distance is not the only important factor in making the decision on how to invest. In the case below, we will show how factors like loading and unloading (terminal time), load capacity, moisture content, delivered energy price, and investment costs bear influence on a good economic solution. One solution can never be optimal for the diversity of sites encountered in forestry; however, a good solution should perform well on average.