856 D. Barcelos et al.
FIG. 1 Study area and locations of the camera traps (dots) deployed to survey tourist and non-tourist trails in Cavernas do Peruaçu National Park, Brazil. A tourism timeline is represented in the bottom right.
TABLE 1 Details of the camera-trap surveys conducted in Cavernas do Peruaçu National Park, Brazil (Fig. 1). Survey period
July 2011–Feb. 2012 June 2013–Aug. 2013 Oct. 2014–Jan. 2015 July 2015–Mar. 2016 July 2016–Mar. 2017 Total
Tourism Before
Before
Before & after After After
Season
Dry & wet Dry Wet
Dry & wet Dry & wet
10 (4/6) 12 (4/8) 16 (5/11) 16 (5/11) 16 (5/11)
No. of sites (tourist/non-tourist trails)
Survey effort (days)
1,457 429
1,672 4,148 3,970
11,676
cards and batteries and to clear vegetation at 45–60 day in- tervals. We did not use baits or lures to attract animals.
Data analysis
We used four metrics derived from camera-trap data to as- sess the potential impacts of tourist visitation on the mam- mal community in the Park: species richness, probability of using trails, overall activity level and daily activity pattern. We based these metrics on records of medium- and large-sized mammal species .1.0 kg and included one smaller rodent, the rock cavy Kerodon rupestris, which is reliably identifiable in camera-trap records. We classified camera-trap data according to visitation period: 2011–2014 as before tourismand 2015–2017 as after tourism. We assumed that the incipient tourism activity before the Park officially opened to tourism would have a negligible or much weaker impact than after official visitation started and the number of visitors increased substantially. Finally, we classified the trails where camera traps were deployed as tourist (n = 5) or non-tourist (n = 11; Supplementary Table 2). The unequal number of sites in each trail category was because of the relatively small area where tourismtakes place in the Park, which would not support a larger number of camera-trap sites unless we reduced substantially the distance between neighbouring sampling sites.
We constructed a daily record history for each mammal
species by assigning presence (1) at each camera-trap site where the species was recorded in a survey day (0.00–23.59) or absence (0) otherwise. Thus, one ormore records of a spe- cies at a site within 24 h were considered as one independent record.We compared species richness using rarefaction curves and a jackknife 1 estimatorwithCI values for each camera-trap site before and after tourism under comparable sampling effort (i.e. number of camera-trap days;Colwell et al., 2012). Jackknife 1 is a non-parametric and incidence-based estimator that per- forms well with camera-trap datasets (Tobler et al., 2008). We used binomial generalized linear mixed models to
estimate the effects of tourism on the probability of trail use by six species, each with at least 100 independent records (Supplementary Table 3): ocelot Leopardus pardalis,paca Cuniculus paca, rock cavy, collared peccary (hereafter peccary) Pecari tajacu, grey brocket deer (hereafter deer) Mazama gouazoubira and coati Nasua nasua. We did not include tapeti Sylvilagus brasiliensis, with 128 independent records, in our assessment because models for the species did not converge. The relatively high number of records used as inclusion criteria was necessary for the convergence of models estimating up to seven parameters. The six target species are known to use trails in the Park and encompass a broad range of body sizes, feeding ecologies and behaviours, representing distinct natural history strategies of the local community of medium-sized and large mammals.
Oryx, 2022, 56(6), 854–863 © Crown Copyright, 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605321001472
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