Reconocimiento estadístico de patrones

By and large, the environmental impacts of certification have been more extensively studied than other kind of impacts. In this regard, we can distinguish five common data- collection methods to carry out such studies: analysis of corrective action requests (CARs), surveys, interviews, public databases, extensive reviews of the literature, direct field surveys, and empirical evidence. Importantly, these techniques are also employed to study social and

economic impacts, as well as other effects. As described below, each of these methods has both strengths and weaknesses.

From those abovementioned, CARs analysis is perhaps one of the most widely employed (and reasonably accessible) techniques to collect data. CARs are operational changes that firms have to engage in to meet the requirements to be certified by an independent third party. They provide considerable quantitative and qualitative information about the operational changes that companies have had to face to meet a particular certification scheme. Romero et al.

(2013), believe that CARs can provide valuable information about the nature of a problem and its evolution over time. Therefore, a number of studies employing CARs have been conducted in developed countries (Newsom et al., 2006; Masters et al., 2010; Cubbage et al., 2010; Hirschberger, 2005d; Hirschberger, 2005e), in developing countries (Schulze et al., 2008; Roberge et al., 2011a) and in transitioning countries (Hirschberger, 2005a; Hirschberger, 2005b; Hirschberger, 2005c). Other authors (Peña-Claros and Bongers, 2010; Newsom and Hewitt, 2005; Auld et al., 2008b) have also used the analysis of CARs to gather evidence about the global impacts of certification.

However, CARs have some limitations. They can only provide indirect evidence of the positive impacts of certification, and this evidence largely relies on the interpretation of certification auditors’ findings (Romero et al., 2013) and on the consistency of each assessment process (Masters et al., 2010; Rametsteiner and Simula, 2003). In addition, CARs may provide only a narrow view about what is really happening on the ground because they focus on changes in practices rather than on providing a comprehensive picture entailing other dimensions of forest certification impacts (e.g. its problem solving capacity or its effectiveness as a policy instrument). A limitation of CAR analysis is that it only easily applied to FSC audit reports, since the FSC process sets conditions or CARs after certification; in contrast, many PEFC- endorsed schemes (e.g. the Sustainable Forestry Initiative [SFI] in North America) require instead that all their requirements be met prior to certification being awarded; and they differ from the FSC both in number and focus of requirements (Moore et al., 2012). Other PEFC- endorsed standards, like the Chilean CERTFOR, have audit reports that are not easily accessible to the general public and, when available, they often miss some reporting periods. These factors mean that CAR analysis is not necessarily equivalent between FSC and PEFC-endorsed schemes. Hence, CAR analysis should not be used as a “stand-alone” tool to evaluate the impacts of certification; instead, they should be complemented with other data-collection methods.

Surveys and public databases are common quantitative tools when collecting data concerning the impacts of forest certification on different types of forestry enterprises. They have been employed both in developed (see for example Newsom et al., 2003; Auld et al., 2003; Moore et al., 2012), transitioning (Golovina, 2009) and developing countries (see Alves

et al., 2011; Basso et al., 2011), particularly at the landowner and managerial level. At a larger scale, Marx and Cuypers (2010) analysed the macro-effectiveness of the FSC for 221 countries, employing a set of public world databases from different global organizations (namely, FAO, UNDP, the World Bank and FSC). Of course, surveys and public databases provide useful information about certain, very specific impacts (e.g. percentage of certified forestlands or some perceptions about certification), but do not provide much context as to how or why these impacts (public databases) or experiences (surveys), came about and in this respect they are constrained by the questionnaire framework itself. Also, Neuman (2011) highlights several limitations concerning the accuracy and respondent rate of surveys, which is especially important when relevant information over a wide range of different stakeholders is needed.

Literature reviews and in-depth interviews have been used in a number of studies as a means to collect relevant information about environmental impacts of certification, providing significant amounts of detailed qualitative information. Different reviews of the literature have paid more attention to particular issues than others. Some have focused on biodiversity implications of certification (Rametsteiner and Simula, 2003; Johansson et al., 2013), constraints for certification uptake (Leslie, 2004), as well as meta-analysis comparing the different (theoretical) performance of forest certification schemes (Clark and Kozar, 2011; Masiero et al., 2015). In contrast, interviews can provide richer data on, for instance, awareness of environmental issues among landowners (De Lima et al., 2008) and influence (in different aspects) of certification on the environmental performance of forestry enterprises (Cubbage et al., 2010; Roberge et al., 2011a; Gomez-Zamalloa et al., 2011; Hain and Ahas, 2007). Interestingly, some of those studies have narrowed the scope of their interviews using, for example, a variation of the Delphi method (that is, by using semi-structured interviews on a number of experts in forest issues) (Gomez-Zamalloa et al., 2011). All of the abovementioned approaches give rich descriptions about certification impacts, but they should be complemented with other data-collection methods (e.g. public databases and statistics); and, importantly, researchers need to be aware of methodological constraints (discussed in section 2.5.5) when employing them.

Direct field surveys and empirical evidence have also been employed to assess certification impacts. This has been approached by an increasing number of studies since Hagan

et al. (2005)’s assessment on biodiversity practices by using a structured field questionnaire in SFI- and FSC- certified North American forests. For instance, Hain and Ahas (2007) used field

visits, along with surveys and interviews, to assess forest management in FSC-certified Estonian forests. Sverdrup-Thygeson et al. (2008) compared biodiversity values before and after certification under the Norwegian “Living Forests” scheme by measuring the number of retention trees and mean width of buffer-strips along rivers; this was similar to Foster et al.

(2008)’s assessment on forest structure in FSC-certified and non-certified forest stands in the US. Likewise, Johansson and Lidestav (2011) used indicators for “enhanced biological diversity” such as quantities of dead wood, broad-leaved trees and old forests in FSC- and PEFC- certified Swedish forests. Others (Dias et al., 2013) estimated biodiversity values (viz. richness and irreplaceability) for vertebrate species in FSC-certified and non-certified areas in Portugal and, at a larger scale, Elbakidze et al. (2011) compared biodiversity conservation in Sweden and Russia by evaluating the structural habitat connectivity in FSC-certified areas. Overall, such studies have focused their attention on either specific environmental issues (in this case, biodiversity) or at limited spatial scales.

Finally, some authors emphasize the need for appropriate measures to assess the environmental impacts of certification, particularly when evaluating biodiversity issues. To illustrate this point, some researchers (Mekembom, 2010; Rodríguez and Cubas, 2010; De Iongh and Persoon, 2010) suggest that it is useful to complement professional monitoring (which is expensive and clearly not sufficient) of biodiversity impacts with those performed by – properly trained – local and Indigenous communities. Other authors such as Schulze et al.

(2010) and Price (2010) recommend drawing up better guidelines to measure the impact of harvest operations on biodiversity, and evaluating different scenarios (with and without conservation measures given by forest certification), respectively. Notwithstanding the relevance of such measures, we must be aware of time constraints and other practicalities affecting their implementation.

To recap, a range of different approaches and methods have been used to assess the environmental impacts of certification. Most of them have proved useful in obtaining accurate estimations of such impacts. However, many fail in obtaining a comprehensive view of the phenomenon, because they adopt a narrow approach to measuring environmental impacts. Hence, a more comprehensive approach should consider a mix of different techniques complemented with an appropriate research design.