MATERIALS AND METHODS
Study site — The study was conducted in two adjacent areas with
distinct protection categories (Figure 1). The Rio Doce State Park (RD)
is an IUCN protected area category II (National Park) and the largest
remnant of Atlantic Forest of State of Minas Gerais, southeastern
Brazil, with ca. 36,000 ha of stational semi-decidual forest (SOS Mata
Atlântica 2019). The RD has a large lacustrine system composed of 42
natural lakes and it is limited in the eastern part by the Rio Doce
river. In 2010 the RD importance was internationally recognized when it
became a Ramsar site by UNESCOs Convention on Wetlands. Despite being
one of the largest remnants of Atlantic Forest, RD is isolated from
other forest remnants and is surrounded by several types of
human-related habitats, especially a mosaic formed by eucalyptus
plantations, but also native forest fragments.
The second study area (EP) is a private property of ca. 23,000 ha
composed mainly by eucalyptus plantations, but also by fragments of
Atlantic Forest and natural lakes. This area is an IUCN protected area
category VI (Protected area with sustainable use of natural resources)
and during the evaluation time, eucalyptus management and logging were
regularly done. Hunting is prohibited either in RD or in EP, but fishing
is allowed in EP lakes, where fishermen and illegal hunters are common.
The EP area is located at the southern border of the RD buffer zone, and
it is commonly frequented by mammals. The region has a tropical climate
and during this study had an annual precipitation of 1,035 mm and the
average temperature was 25ºC (INMET 2019).
Data collection — Sample period was from April 2014 to January
2015, where camera traps (Bushnell®) where deployed on
man-made trails and game trail in RD and EP, totalizing 30 camera sites
(15 on each area). A minimum distance between camera sites was 1km to
minimize a lack of independence between sampling sites. Camera traps
were deployed 30cm above ground level, allowing the detection of medium-
to large-sized mammals, and operated 24-h.
Activity patterns analysis — We defined an activity sample as
all photographs of the same species detected at a camera site within an
1-h period, thus minimizing the nonindependence of consecutive
photographs. The hour of each activity sample recorded by the camera
traps was transformed into a solar time based on sunrise and sunset
times of our study area. This is important to accurately define the
activity pattern of the species and also to allow comparisons with other
studies (Foster et al . 2013). Sunrise and sunset times were
obtained from the software Moonrise v.3.5 (Romero-Muños et al .
2010; Foster et al . 2013), and we used the following formula
described by Woolf (1968) for solar conversion:
\begin{equation}
\mathrm{LCT\ =\ }\mathrm{t}_{\mathrm{s}}\ \mathrm{-\ }\frac{\mathrm{\text{EOT}}}{\mathrm{60}}\mathrm{\ +\ LC\ +\ D}\nonumber \\
\end{equation}Where LCT is the standard clock time, ts the solar time,
EOT the equation of time, LC the longitudinal correction, and D the
daylight saving time (see Woolf (1968) for further details).
Then, we used the Rao’s spacing test (Rao 1976) to verify whether the
species activity pattern was uniformly distributed (i.e., cathemeral) or
associated with a specific time period (i.e., diurnal, nocturnal or
crepuscular). We categorized the activity pattern of each species into
diurnal (>60% of records between 1h after the sunrise and
1h before the sunset), nocturnal (>60% of records between
1h after the sunset and 1h before the sunrise), crepuscular
(>50% of records occurring 1h before and after sunrise and
sunset) and cathemeral (peaks of activity through the diurnal and
nocturnal period). To compare the 24-h cycles of each species between RD
and EP we used the Mardia-Watson-Wheeler test (W ). When theW test revealed no significant differences (P> 0.05) in the 24-h cycles of a given species between the
studied areas, we combined species data from both areas for the
subsequent analyses. The analyses were performed using the package
“circular” v.0.4-93 (Lund and Agostinelli 2017) in R Software v.3.6.3
(R Development Core Team 2019).
Activity overlap analysis — To evaluate the temporal activity
overlap between predators, as well as between predators and their
potential prey, we calculated the coefficient of overlap (Δ; Ridout and
Linkie 2009) that varies from 0 (no overlap) to 1 (complete overlap). We
used the Δ1 estimator when the number of independent
records of at least one species in the pairwise comparisons was
<75 photographs. Otherwise, we used the Δ4estimator. We calculated the 95% confidence intervals for\(\hat{\Delta}\) from 10,000 bootstrap samples (Ridout and Linkie,
2009). To complement the coefficient of overlap, we compared the 24-h
cycles between species using the W test. To calculate the
coefficient of overlap and the W test statistics we used the
package “overlap” v.0.3.2 (Linkie and Ridout 2011) and the package
“circular” respectively, both available in the R Software.
Potential preys were based on studies of feeding habits for each
predator species (Appendix 1). We considered as potential preys only
those preys found at least once in any study. Rarely, some prey species
that are much larger than the predator were described as a diet item,
but as it was related to a scavenging behavior, we did not consider it
directly as a potential prey. We did not find in any study that the
giant-armadillo (Priodontes maximus ) could be a prey item for
jaguars, but because we believe that this predator can prey upon it, we
included the giant-armadillo as potential prey for jaguars.
We used the study of Oliveira and Pereira (2014) to either verify the
relationships of dominance and subordination among predators or the
possibilities of IGP/IK among them. The analysis of temporal activity
overlap was performed only if either IGP or IK was noticed between the
given predators in this study. Also, according to this study, jaguars
are the top predators with no natural predators. The puma has the jaguar
as a potential predator, and ocelots have jaguars and pumas as potential
predators. These three felids are potential predators for crab-eating
foxes, tayras, and coatis, and there were no records of IGP or IK
between these latter species.