The circadian activity pattern is an important component of the ecological niche of any species (Schoener Reference SCHOENER1974) and helps in the understanding of local interactions that structure communities (Gómez et al. Reference GÓMEZ, WALLACE, AYALA and TEJADA2005). Despite physiological restrictions, some species have a flexible activity pattern (Lodé Reference LODÉ1995). Some mammals can shift activity patterns in response to environmental factors such as weather and the quality, abundance and spatio-temporal distribution of resources (Lodé Reference LODÉ1995, Zhou et al. Reference ZHOU, WEI, HUANG, LI, REN and LUO2007) or life cycle needs. Differences in activity times of the Eurasian otter Lutra lutra between habitats (Lodé Reference LODÉ1995) and seasons (Kruuk Reference KRUUK2006) are known to occur potentially due to differences in prey availability. Also, some carnivores can change their activities to periods with less human activity (Riley et al. Reference RILEY, SAUVAJOT, FULLER, YORK, KAMRADT, BROMLEY and WAYNE2008) or due to introduced or native competitors (Gerber et al. Reference GERBER, KARPANTY and RANDRIANANTENAINA2012).
Camera traps are an efficient non-invasive technique to study mammal activity (O'Connell et al. Reference O'CONNELL, NICHOLS and KARANTH2010, Rowcliffe et al. Reference ROWCLIFFE, KAYS, KRANSTAUBER, CARBONE and JANSEN2014). However, studies using this technique in semi-aquatic mammals are still scarce (Lerone et al. Reference LERONE, CARPANETO and LOY2015, Leuchtenberger et al. Reference LEUCHTENBERGER, ZUCCO, RIBAS, MAGNUSSON and MOURÃO2014, Pickles et al. Reference PICKLES, ZAMBRANA, JORDAN, HOFFMANN, SALINAS, GROOMBRIDGE and VAN DAMME2011). This may be due to the difficulty of finding dry places near aquatic environments to deploy camera traps and to the problems associated with the detection of a wet animal by infrared sensors (Lerone et al. Reference LERONE, CARPANETO and LOY2015). Therefore, knowledge of the activity patterns of the Neotropical otter Lontra longicaudis (Olfers 1818) remains anecdotal.
In this study, we aimed to describe and compare the activity patterns of the Neotropical otter in two distinct areas, Pantanal and Atlantic Forest, characterized by different ecological and landscape features. We also aimed to test if the Neotropical otter selects some part of the diel cycle in its activity in each area.
The Pantanal is a seasonally flooded plain of about 160000 km2. In this region, the rainy season usually occurs from November to March, and flooding occurs from December to April. This is an area with low human density, covered by primary riparian forest. Our study area included a stretch of the Negro River (19°34′S, 56°09′W; more details in Leuchtenberger et al. Reference LEUCHTENBERGER, ZUCCO, RIBAS, MAGNUSSON and MOURÃO2014). The Atlantic Forest is a highly diverse but extremely threatened ecoregion, with more than 80% of its original area deforested (Metzger Reference METZGER2009). Our study area was the Águas Claras watershed (22°30′S, 42°30′W; more details in Galliez et al. Reference GALLIEZ, LEITE, QUEIROZ and FERNANDEZ2009). The upper course of this river crosses well-preserved forests, while its lower course flows through agricultural fields and pastures, without riparian forests.
Between May and September 2011 (7–31 d mo−1) and in December 2012 (30 d mo−1), we set one to four digital camera traps in the Pantanal (Bushnell® Trophy Cam) at the entrance of six previously known Neotropical otter holts. Distance between adjacent camera traps ranged from 29 m to 3970 m. In the Atlantic Forest, between April 2010 and January 2011 (5–31 d mo−1) we set one to four digital camera traps (Tigrinus® 6.0D) at eight previously known holts of Neotropical otter. Distance between adjacent camera traps ranged from 122 m to 1280 m.
We placed the camera traps (active 24 h) in front of previously known holts of Neotropical otter, facing their entrance. We used 1-h intervals as an independence criterion among photographic records obtained from the same sample site, similar to or more conservative than the majority of similar studies (Di Bitetti et al. Reference DI BITETTI, DE ANGELO, DI BLANCO and PAVIOLO2010, Gómez et al. Reference GÓMEZ, WALLACE, AYALA and TEJADA2005, Leuchtenberger et al. Reference LEUCHTENBERGER, ZUCCO, RIBAS, MAGNUSSON and MOURÃO2014).
We set a standardized circadian scale to the sunrise and sunset times at 6h00 and 18h00 respectively. The raw time information of each record was rescaled to this standardized scale through interpolation, considering the sunrise and the sunset at the site in the date of the record. We described activity patterns using circular kernel density estimations (Oliveira-Santos et al. Reference OLIVEIRA-SANTOS, ZUCCO and AGOSTINELLI2013), which have the advantage of recognizing the continuous and circular nature of the data. We estimated activity by using isopleths of 95% and 50%. To test the similarity of activity between areas, we evaluated the overlap between distributions, assessing the significance of the difference between them through Monte-Carlo simulations resampling each 100000 times.
We evaluated the selection of four periods of the diel cycle (dawn, day, dusk and night) by otters using the Ivlev's Electivity Index (EI, Ivlev Reference IVLEV1961). We defined dawn and dusk as the periods when the sun height is below –12° and +12°. We measured availability as the proportion of the diel cycle encompassed by each period. The use of each period was estimated as the proportion of the kernel activity density located within that period. We tested the hypothesis of period selection by otters by resampling (bootstrap with replacement) capture events 1000 times using the same number of records of the original sample (Pantanal or Atlantic Forest). We rejected the EI selection or rejection when the zero value lay within the 2.5% and 97.5% quantiles of the distribution of simulated Electivity index values. We ran all analyses in R version 3.1.1 using the circular and maptools packages.
We obtained 46 independent records in the Pantanal (2–18 photos per holt, average = 15.1 ± 10.7 photos per100 camera trap-days; effort of 300 camera trap-days) and 58 in the Atlantic Forest (3–17 photos per holt, average = 22.9 ± 9.2 photos per 100 camera trap-days; effort of 273 camera trap-days). The kernel density functions of the two sites overlapped 45.6% and 14.1% for the 95% and 50% isopleths respectively (Figure 1). In the Pantanal, we observed a selection of the daylight period (EI = 0.23) and avoidance of the night (EI = −0.44) (Figure 2a). Ivlev values for dusk and dawn were not significantly different from zero (Figure 2a). In the Atlantic Forest, we observed a selection of the dawn (EI = 0.24), and the night (EI = 0.14) periods (Figure 2b). We also observed an avoidance of the daylight period (EI = −0.33, Figure 2b). The EI for dusk did not differ from zero (Figure 2b).
Figure 1. Circadian distribution of kernel density probabilities (continuous lines) of the Neotropical otter Lontra longicaudis activity in the Pantanal (a) and in the Atlantic Forest (b) based in camera trap photos. Sampling in Pantanal was conducted between May and September 2011 and in December 2012 and in Atlantic Forest between April 2010 and January 2011. The light blue area in the graph indicates the crepuscular periods (the first represents the dawn period and the second represents the dusk). The dark blue area represents night. The dark red area represents the 50% kernel density probability. Each tick in the bottom of each ecoregion's graphic represents an independent photo used in our analyses.
Figure 2. Estimates of Ivlev Electivity Index (EI) for Neotropical otter Lontra longicaudis in the Pantanal (a) and in the Atlantic Forest (b) sites based in camera trap photos. Sampling in Pantanal was conducted between May and September 2011 and in December 2012 and in the Atlantic Forest between April 2010 and January 2011. Each white dot represents the EI for each period. The light blue area represents the density distribution of all simulated indexes through Monte-Carlo. The black traces are the 0.025 and 0.975 quantiles of the Monte-Carlo simulation values.
Camera trapping is an efficient method to estimate Neotropical otter activity. Even with active cameras facing the holts, we observed frequent reuse of the holts in both areas, which suggests low interference on the animals’ behaviour. Although camera trapping has low susceptibility to environmental variation (Rowcliffe et al. Reference ROWCLIFFE, FIELD, TURVEY and CARBONE2008), its application in otter studies has some limitations. High humidity and occasional flooding in the Atlantic Forest damaged some of our cameras. The infrared sensors of the models used in our study can fail to detect semi-aquatic mammals, because the low surface temperature of a wet animal may preclude thermal detection (Lerone et al. Reference LERONE, CARPANETO and LOY2015). However, considering the number of records we obtained, we suggest that this method can be used satisfactorily to study semi-aquatic mammals, as also shown by Leuchtenberger et al. (Reference LEUCHTENBERGER, ZUCCO, RIBAS, MAGNUSSON and MOURÃO2014) for the giant otter. Also, the use of video capturing instead of photos might provide more detailed information on activity and behaviour of these animals. As we observed simultaneous occurrence of adults and cubs in two consecutive photos, this method may also provide a good tool to investigate the poorly known reproductive behaviour of the otter.
The activity patterns of L. longicaudis differed between the two distinct ecoregions. We suggest three hypotheses that could explain this difference. (1) Anthropogenic activities can affect otter activity, as previously shown for other carnivores (McClennen et al. Reference MCCLENNEN, WIGGLESWORTH and ANDERSON2001). The Atlantic Forest is the most densely occupied region of Brazil and is intensively disturbed by human activity (Metzger Reference METZGER2009). In our study area, we observed domestic dogs and human settlements very close to the river, which can drive otter to become nocturnal. The Pantanal has 80% of its area well preserved (Junk & Cunha Reference JUNK and CUNHA2005), which can explain the observed diurnal pattern in the area. (2) The shift of activity pattern could be due to competitors. In Pantanal, the Neotropical otter occurs sympatrically with the giant otter Pteronura brasiliensis, which is mainly diurnal (Leuchtenberger et al. Reference LEUCHTENBERGER, ZUCCO, RIBAS, MAGNUSSON and MOURÃO2014). Although we could expect the change in activity time for one of them, there seems to be little competition between the two species, probably due to differences in habitat preferences and prey sizes (Silva et al. Reference SILVA, ROSAS and ZUANON2014). (3) Lontra longicaudis is a generalist predator that can change prey preferences according with abundance and occurrence of food resources (Rheingantz et al. Reference RHEINGANTZ, OLIVEIRA-SANTOS, WALDEMARIN and CARAMASCHI2012). This could force the otter to change its activity due to the different activity patterns of their prey. In the Atlantic Forest area, the main prey items of L. longicaudis are nocturnal or crepuscular species such as armoured and low-eye catfish, freshwater prawn and cane toad (unpubl. data). Therefore, the activity selection of dawn and night periods by otters can also be due to synchronization with their prey. In the Pantanal, although we have not carried out a systematic study on L. longicaudis feeding habits, we witnessed otter predation in the field several times during the day, with preference for suckers, catfishes and cichlids. Cichlids are mainly diurnal and the other two, although mostly crepuscular/nocturnal, can be active during the day in darker waters (Britski et al. Reference BRITSKI, SILIMON and BALZAC1999) as the Negro River.
The placement of camera traps facing the holts is an efficient method to study semi-aquatic carnivores and it can be applied to other species with elusive habits. Factors that determined the activity period differences observed in this study are not yet clear. To fill this gap we recommend that future studies should address the level of anthropogenic impact and foraging strategies related with prey activity.
ACKNOWLEDGEMENTS
We acknowledge the Brazilian Agricultural Research Corporation (Embrapa-Pantanal) and Barranco Alto Farm for financial and logistic support in the Pantanal biome. We also acknowledge Reserva Botânica Águas Claras, Universidade Federal do Rio de Janeiro, Fundação Grupo Boticário and CNPq for financial and logistical support in the Atlantic Forest biome. CL was recipient of CNPq scholarship. Lucas Leuzinger helped us with camera trap survey at the Pantanal area. We also acknowledge Bernardo Araujo for the English review.