1 INTRODUCTION

The threat that protected areas across different ecosystems in Africa face from illegal activity is not new and is widely accepted (Davies & Brown, 2007; Ripple et al., 2016; Taylor & Dunstone, 1996). Such activity can take different forms, including encroachment for settlement and agriculture, which cause habitat loss (Caro & Sherman, 2011; Hofer, Campbell, East, & Huish, 1996; Wittemyer et al., 2008), and the illegal harvest of wildlife, plants and other forest-based resources for subsistence and commercial purposes (Harrison, Baker, Twinamatsiko, & Milner-Gulland, 2015; Lawson, 2014; Poulsen, Clark, Mavah, & Elkan, 2009). These have become central challenges faced by conservationists in Africa. For example, unauthorised timber harvesting threatens the sustainability of the miombo ecosystems of Tanzania and elsewhere in Africa (Jew, Dougill, Sallu, O'Connell, & Benton, 2016), and bushmeat hunting is the leading cause of wildlife population declines in many African ecosystems (e.g., Milner-Gulland & Bennett, 2003; Ripple et al., 2016). Law enforcement, principally in the form of ranger patrols, is the most common method used to deter illegal activities in protected areas (Gandiwa, Heitkönig, Lokhorst, Prins, & Leeuwis, 2013).

A number of studies have evaluated the effectiveness of law enforcement patrols, and how these can be improved (e.g., Holmern, Muya, & Roskaft, 2007; Gandiwa et al., 2013; Johnson et al., 2016). Ranger-collected data are increasingly used to evaluate and analyse patrol efficiencies in order to improve law enforcement (Critchlow et al., 2016; Keane, Jones, & Milner-Gulland, 2011; Moore et al., 2018). One contemporary software package used to collect, manage and process these data is the Spatial Monitoring and Reporting Tool (SMART; http://smartconservationtools.org; see also Critchlow et al., 2016; Hötte et al., 2016). SMART is a science-based conservation technology that has been developed in recognition that “traditional tools, technologies and resources are not stemming the illegal use of wildlife resources and the resulting loss of biodiversity” (ZSL, 2018). It makes use of a geographical information system (GIS) that enables rangers to conveniently collect and organise spatial information about illegal activities while on patrol (Sintov, Seyranian, & Lyet, 2018). This information is entered into the SMART database for later use in patrol planning and monitoring (ZSL, 2018). A database in this context is a set of data stored in a computer that is electronically accessible for various uses. SMART has been reported to be effective in reducing illegal activities in Russia (Hötte et al., 2016); presently, it is used throughout Ugandan protected areas (e.g., Critchlow et al., 2016), and other Africa's protected areas, such as Gonarezhou National Park in Zimbabwe, and North Luangwa ecosystem in Zambia (Henson, Malpas, & D'Udine, 2016).

In Tanzania, SMART has been introduced in some game reserves (trophy hunting areas) and national parks (strictly protected, no trophy hunting; SMART, 2017). In order for SMART to achieve a sustainable impact and improve conservation, it is crucial that challenges that could potentially affect the introduction of such a technology are understood and taken into account (Sintov et al., 2018). However, to the best of our knowledge, there has been no attempt to assess the challenges in using SMART effectively faced by game officers and rangers since its introduction to Tanzania's game reserves. Given this, we applied qualitative methods to investigate the experiences of game officers and rangers in a game reserve in western Tanzania.

Ugalla Game Reserve (hereafter Ugalla), in western Tanzania, experiences high levels of illegal activity (Wilfred, Milner-Gulland, & Travers, 2017). Logging and the killing of elephants (Loxodonta africana, [Anonymous, 1827]) and other species of conservation importance are widespread in the area (Wilfred & MacColl, 2014). Law enforcement has been the predominant deterrent to illegal activities, where anti-poaching patrols are conducted on a monthly basis in the reserve. Nevertheless, illegal resource use remains a significant problem (Wilfred et al., 2017). Consequently, the management of Ugalla is gradually incorporating and applying SMART technology to enable efficient and effective measurement and improvement of patrol efforts for the purpose of controlling poaching. As an essential step in meeting this goal, our study aimed to determine the challenges that could affect the use of SMART in the reserve based on their initial 2-year experience of SMART-based ranger patrols.

2 METHODS

2.1 Study area

Ugalla (approximately 5,000 sq. km., Figure 1) was gazetted as a game reserve in 1965 (Fisher, 2002). The reserve experiences a tropical climate, defined by a single dry season (July–December) and a single wet season (January–June). The annual rainfall ranges between 700 and 1,000 mm, and mean maximum and minimum temperatures range between 28–30°C and 15–21°C, respectively (Hazelhurst & Milner, 2007; Mbwambo, 2003). The management of Ugalla is administered by the newly formed Tanzania Wildlife Management Authority (TAWA) through Ugalla's main office in Tabora. Ugalla mainly consists of miombo woodland with commercially valuable timber tree species (UGR, 2006) and supports a wide variety of wildlife, including African elephant and endangered African wild dogs (Lycaon pictus, [Temminck, 1820]; Wilfred & MacColl, 2016). The reserve is also an important bird area (BirdLife International, 2018) and is part of the Malagarasi-Muyovozi Ramsar Site (Kalumanga, 2015) that protects habitat for the vulnerable shoebill (Balaeniceps rex, [Gould, 1850]) and wattled crane (Bugeranus carunculatus, [Gmelin, 1789]; John, Nahonyo, Lee, & Msuya, 2013). The area also hosts a diverse range of fish (UGR, 2006).

The main legal activity in Ugalla is trophy hunting, which is administered by trophy hunting companies each year between June and December in three hunting blocks: East Ugalla, South Ugalla and North Ugalla (Figure 1). East Ugalla is leased to Game Frontiers of Tanzania Ltd, with the two other hunting blocks leased to Tanzania Game Trackers Safaris (TGTS). The concessionaires are also responsible for conducting anti-poaching patrols in collaboration with Ugalla rangers (Baraka, B., pers. comm.). Each company hires game scouts on a part-time basis to conduct patrols in their hunting blocks. These scouts are local people, who are unarmed and relatively poorly trained. While Ugalla rangers have their own patrol teams, two to three of them are normally assigned to guide and supervise each of the trophy hunting companies' patrols, as the primary responsibility (Baraka, B., pers. comm.). The Ugalla manager and other game officers, in addition to participating in patrols, perform administrative tasks, including patrol planning, compiling reports from patrol leaders, and preparing evidence for court cases.

3 RESULTS

4 DISCUSSION

Our intention has been to draw attention to factors that might influence the use of SMART in a protected area, rather than assessing the efficiency of SMART as a conservation tool. SMART is undoubtedly effective in improving law enforcement in protected areas (Critchlow et al., 2016; Hötte et al., 2016). However, effective use of such a conservation tool depends on a thorough understanding of local factors likely to affect its adoption (Sintov et al., 2018). We presented challenges that can potentially affect the use of SMART in law enforcement ranger patrols in Ugalla. Our findings indicate that SMART patrols are affected by the lack of motivation for using the technology, resource shortages and limited coverage of ranger patrols.

We found that game rangers felt demotivated to adhere to SMART-based patrol plans because of the belief that their leaders benefited from the project. This could be because the rangers perceived SMART as an additional responsibility over and above their traditional patrolling activities that deserves motivation. Lack of motivation is known to affect the efficiency of anti-poaching patrols and is a leading cause of misconduct among law enforcement rangers (Moreto, Brunson, & Braga, 2015). Poor knowledge about SMART among patrol staff was also considered one of the contributors to lack of motivation to use it. Study participants realised that some rangers were not good at SMART, partly because they were transferred to other protected areas and their replacements were usually either poorly trained or knew nothing about SMART. In addition, although the trophy hunting companies' game scouts were supervised by Ugalla rangers, it was challenging for them to learn and participate in the SMART process (e.g., feedback meetings and patrol planning) not only because they were not conversant with SMART, but also because they performed their duties as directed and controlled by the hunting companies. This may result from the primary objective of hunting company game scouts in Tanzania being to serve the interests of the hunting outfitters, as is commonly seen in conservation areas where trophy hunting is permitted (Lindsey, 2008).

Study participants suggested that the use of SMART in Ugalla is affected chiefly by inadequate resources, namely patrollers, patrol vehicles and equipment like GPS units. Ineffective law enforcement as a result of insufficient resources is a common problem in Tanzania's protected areas (e.g., Carpaneto & Fusari, 2000; Nahonyo, 2005; Holmern et al., 2007). Discussions about human resources were salient. For instance, focus groups were concerned that game rangers were relatively few and that, as a result, their law enforcement efforts relied on the support of the trophy hunting companies. Other literature suggests that Tanzania relies largely on trophy hunting companies to control illegal activities in game reserves (Brink, Smith, Skinner, & Leader-Williams, 2016). Considering the number of rangers working per month in Ugalla, their workload was high, as each of them was supposed to patrol around 200 sq. km (i.e. 5,000 sq. km/25 patrollers). This is more than Ruaha National Park, and the recommended ratio of 50 sq. km. ranger⁻¹ (see Nahonyo, 2005). The patrol data suggest that Ugalla ranger patrols tend to focus their limited efforts on places least patrolled by trophy hunting companies. For example, they mostly patrolled the eastern part of the reserve, while the northern and western parts were patrolled by TGTS. Key informants argued that Game Frontiers of Tanzania Ltd rarely conducted patrols, which is probably why Ugalla rangers were forced to spend considerable effort to patrol the East Ugalla hunting block. This may complicate the interpretation of the patrol results as SMART data managers may be forced to integrate differences in patrol efforts to realistically determine the pattern of illegal activity across the reserve. Wilfred (2012) found that TGTS patrol teams at Ugalla were more effective than Ugalla rangers, which again supports our observation that the hunting company patrols spent more effort in terms of the number of effective patrol days than Ugalla rangers.

The data presented here show patrol coverage is reduced in hard-to-reach areas regardless of whether they are SMART-informed. The wet season was shown to be problematic. We found that patrols encountered more obstacles during this period than the dry season, corroborating a previous study in Ruaha National Park (Nahonyo, 2005). Patrol staff appeared to over-patrol some areas of Ugalla in the wet season and avoided others, especially the southern sections. This may lead to unrealistic measures of patrol efforts by SMART, and the conclusion that the southern part of the reserve experiences lower levels of illegal activities, particularly as previous studies show that illegal activity is widespread across the reserve (e.g., Wilfred, 2015). Elsewhere in Uganda, Critchlow et al., (2016) recommend the use of SMART in the planning and monitoring of ranger patrols only if the patrol effort is fairly distributed across the protected area.

We suggest introducing a variety of incentives to encourage and motivate game rangers to use SMART. For example, in Russia, Hötte et al., (2016) reported the importance of improving patroller motivation through rewarding patrol efforts and observations, but cautioned that this should be done only if ranger morale is low, and the initiative can be sustained in the long term. Because some rangers were perceived to be far less conversant with the usage of SMART technology, regular refresher training could be conducted to enable them to keep pace with advances in SMART, improve their capacity and prevent the discontinued use of the SMART knowledge. Trophy hunting companies could have a training programme to equip their game scouts with the necessary knowledge to effectively and fully participate in the SMART-based anti-poaching patrols. Training patrol staff on the use of advanced functionalities in SMART, in conjunction with the utilisation of specialist smartphones for data collection, could enable them to collect data faster and accurately and thus overcome the limitations of the basic equipment (e.g., Lotter et al., 2016). Increasing the number of game rangers could increase the size of the area the rangers patrol, but this should be accompanied with improving the accessibility of patrol roads to remote parts of Ugalla during the rainy seasons. Although SMART is currently being implemented in Tanzania's game reserves, site-specific assessments of the local factors that may impact the success of the intervention are of paramount importance.