Biodiversity Data Journal 11: e98119 OO)
doi: 10.3897/BDJ.11.e98119 open access
Research Article

First insights in terrestrial mammals monitoring in
the Candelaria and Machay Reserves in the
Ecuadorian Tropical Andes

Juan Pablo Reyes-Puig*!, Carolina Reyes-Puig!S:*, Jessica Pacheco-Esquivel”, Santiago
Recalde+, Fausto Recaldet, Darwin Recaldet, Jordy Salazar+, Eduardo Pefiat, Silvia Paredes‘,
Marina Robalino*, Fernanda Flores“, Vladimir Paredes‘, Edelina Sailema‘, Gorky Rios-Alvear|”

+ Ecominga Foundation, Bahos, Ecuador

§ Instituto Nacional de Biodiversidad, Unidad de Investigacion, Quito, Ecuador

| Fundacion Oscar Efrén Reyes, Bafios de Agua Santa, Ecuador

| Universidad San Francisco de Quito, Colegio de Ciencias Bioldgicas y Ambientales COCIBA, Museo de Zoologia &
Laboratorio de Zoologia Terrestre, Instituto de Biodiversidad Tropical iBIOTROP, Quito, Ecuador

# Universidad San Francisco de Quito, Instituto BIOSFERA, Quito, Ecuador

x WWF, Quito, Ecuador

« Asociacion de Turismo Comunitario Quinde Warmi, Banos - El Placer, Ecuador

» CIBIO Centro de Investigaci6n em Biodiversidade e Recursos Genéticos, Porto, Portugal

“ Grupo de Biogeografia y Ecologia Espacial (BioGeoE2), Facultad de Ciencias de la Vida, Universidad Regional Amazonica
Ikiam, Tena, Ecuador

Corresponding author: Gorky Rios-Alvear (gork_dan@hotmail.com)
Academic editor: Ricardo Moratelli
Received: 28 Nov 2022 | Accepted: 14 Feb 2023 | Published: 27 Feb 2023

Citation: Reyes-Puig JP, Reyes-Puig C, Pacheco-Esquivel J, Recalde S, Recalde F, Recalde D, Salazar J, Pena
E, Paredes S, Robalino M, Flores F, Paredes V, Sailema E, Rios-Alvear G (2023) First insights in terrestrial
mammals monitoring in the Candelaria and Machay Reserves in the Ecuadorian Tropical Andes. Biodiversity
Data Journal 11: e98119. https://doi.org/10.3897/BDJ.11.e98119

Abstract

Habitat disturbance leads to biodiversity decline and modifications in the landscape
structure and composition, affecting both dispersal movements and ecological processes
at different temporal and spatial scales. The Ecuadorian Tropical Andes harbour suitable
habitats for the distribution of a wide variety of species; however, there is a lack of studies
focused on mammal diversity and its association with the habitat attributes in the central-
eastern slopes. Here, we reported the diversity of terrestrial mammals recorded between
2019 and 2021 in a camera-trap monitoring study in the Candelaria and Machay reserves

© Reyes-Puig J et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC
BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are
credited.

2 Reyes-Puig J et al

in the upper basin of the Pastaza River, Ecuador. We performed site-occupancy probability
analysis to assess the influence of spatial variables in the species’ occurrence and also,
based on natural marks, we reported preliminary findings in Andean bear individual
identification. We detected 22 species of terrestrial mammals. Alpha diversity was similar
between reserves with slightly higher species richness in Machay. Evenness indices
showed unequal species distribution, with the Andean bear and domestic dogs exhibiting
greater dominance. In addition, species composition was dissimilar between reserves,
where the species turnover mostly explained the beta diversity. We observed that Andean
bear and puma detections increased according to the natural vegetation cover. Conversely,
domestic dogs were frequently detected in cells with an increasing proportion of pastures
and crops. Additionally, we identified 26 Andean bears and six individuals recaptured
during our study. Our results caution about the disturbance derived from human activities
since we recorded unprecedented detections of domestic dogs in wild habitats.
Nonetheless, it highlights the importance of private conservation areas (e.g. Candelaria,
Machay and others) for supporting the occurrence and dispersal of terrestrial mammal
species between larger areas in the upper basin of the Pastaza River.

Keywords

ecological corridors, CELS, landscape ecology, mammal diversity, photo identification

Introduction

The main causes for the global biodiversity decline include forest clearing, natural
resources overexploitation, habitat change, invasive alien species, hunting, climate
change, fires and pollution (Pereira et al. 2012, Newbold et al. 2015). Accordingly, land-use
change modifies the spatial structure and composition of landscapes and decreases
habitat connectivity by reducing suitable habitat patches for wildlife dispersal within the
landscape, which ultimately impacts the species’ population viability (Metzger and
Decamps 1997, Goodwin and Fahrig 2002, Beier et al. 2011, Lawler et al. 2013, Leonard
et al. 2017, Marrotte et al. 2017). However, its effects vary according to the matrix features,
the target species and scale of analysis (Krausman 1999, Zeller et al. 2012, Marrotte et al.
2017). For instance, species with broad habitat range take advantage of the interpatch
distances and use small area patches as stepping-stones to travel between core areas,
whereas species with small habitat range benefit from the small area patches’ contribution
to intrapatch connectivity (Goodwin and Fahrig 2002, Herrera et al. 2017). Additionally,
habitat loss and fragmentation impact differentially, the former being more negative for
connectivity due to its effects on the habitat amount and patch isolation (Goodwin and
Fahrig 2002). Similarly, road development is the primary cause of habitat fragmentation
and constitutes a barrier to the movement of several species, preventing their dispersal
ability to travel and access resources within the landscape (Laurance et al. 2009, Seidler et
al. 2015, Beyer et al. 2016, Medrano-Vizcaino and Espinosa 2021). Thus, increasing
habitat connectivity networks (i.e. the availability of routes to support the species’
physiological, behavioural and dispersal requirements within the landscape) is a common

First insights in terrestrial mammals monitoring in the Candelaria and ... 3

strategy to improve wildlife conservation planning (Beier and Noss 1998, Belote et al.
2016, Albert et al. 2017).

The tropical Andes are biodiversity hotspots critical for the provision of ecosystem services
(Myers et al. 2000, Gaglio et al. 2017). Nonetheless, poor land management and intensive
land-use change in anthropogenic landscapes impacts on the species survival rate, either
by reducing the habitat availability, species movement capacity or due to the increase in
the mortality risk of species occurring close to human features (Nielsen et al. 2010,
Cavelier et al. 2011, Fletcher et al. 2019). The foothills and eastern slopes of Ecuador are
characterised by rugged topography and dense vegetation that creates montane cloud
forests and paramos (Simpson 1975, Sanchez et al. 2018). These ecosystems, typical of
the tropical Andes, provide suitable habitats for the distribution of a wide variety of species,
many of them with restricted distributions and endemic to the area (Gradstein et al. 2004,
Jost and Shepard 2017, Reyes-Puig et al. 2022), but also large and medium-sized
mammal species with much larger territory requirements due to their nature and dispersal
ability. In this context, studies focused on mammal monitoring on the central-eastern
slopes of Ecuador are scarce, as well as those attempting to address the variables
affecting the species' site occupancy. Similarly, updated richness and diversity analyses of
medium- and large-sized terrestrial mammals through standardised monitoring is not yet
available.

In this paper, we present the first results of a two-year pilot camera-trap monitoring study of
medium- and large-sized mammals in which we identified the richness and diversity of
species of two reserves located in the east-central Andes of Ecuador (Machay and
Candelaria), in the upper basin of the Pastaza River. In addition, we estimated the
occupancy and detection probability of this group and its association with spatial variables
and finally we took advantage of the methodology to recognise unique individuals of
spectacled bears that allow us to warn about the importance of the region for habitat
connectivity, conservation and management of landscape species.

Material and methods
Study area

We conducted the study in the eastern slopes of the Andes in Ecuador, in the Cerro
Candelaria and Machay Reserves of the Fundacion Ecominga (Fig. 1). The study area
comprehends 74 km2 (defined as the minimum convex polygon around the camera
stations). It is part of the so-called Llanganates — Sangay Ecological corridor (hereafter
CELS) which encompasses public and private lands with important remnants of natural
habitats between two National Parks, Llanganates to the north and Sangay to the south
(Rios-Alvear and Reyes-Puig 2015). CELS possesses’ geological and_ climatic

characteristics which have favoured high levels of endemism and species diversification
within a narrow territory (Jost 2004). Its strategic location is essential for promoting habitat
connectivity (Lessmann et al. 2014, Rios-Alvear and Reyes-Puig 2015, Cuesta et al.
2017), linking protected areas and well-preserved habitat remnants critical for the

4 Reyes-Puig J et al

conservation of species with different habitat requirements (Reyes Puig and Rios Alvear
2013, Rios Alvear and Reyes Puig 2013, Lopez de Vargas Machuca 2014, Reyes-Puig et
al. 2015). The study area includes cloud forests and paramos ranging from 1527 to 3710 m
in elevation devoted to strict conservation management, embedded in a human-dominated
landscape with different degrees of disturbance. The precipitation regime extends from
April to July and October to December, with rains up to 5000 mm (Crespo et al. 2011,
llbay-Yupa et al. 2021). The average annual temperature ranges between 12.3°C and
27.6°C (INAMHI, National Institute of Meteorology and Hydrology- Ecuador 2022).

Venezuela

wes ?
Colombia ;
< Bolivia
Chile

78°30°W 78°20'W 78°10°W 78°O'wW

LLanganates

Legend

E30 Highway

Sangay

Machay Reserve

Candelaria Reserve

78°30 W 78°20'W 78°10'W 78°0'W

Figure 1. EES]

Study area. Large map shows the Machay Reserve in the north and the Candelaria Reserve in
the south. Grey squares represent the sampling areas. The bottom right map shows the
Llanganates and Sangay National Parks and the study area within the CELS (blue line).

Camera trap survey

We conducted a camera-trap survey consisting of four sampling campaigns, from late 2019
to 2021. We defined 15 cells of 1 km? at each Reserve. Each sampling cell was surveyed
twice a year with one camera trap active during the dry and rainy seasons. Effective
sampling days varied from 12 - 65 due to the camera’s performance and the lockdown and
mobility restrictions caused by the COVID-19 pandemic outbreak (Table 1). Sampling cells
were selected according to accessibility. WWe placed one camera per cell at 1 km apart from
each other, following wildlife trails to improve species detectability, particularly in areas that
potentially favour connectivity between the reserves. Cameras were deployed in the same
spot during the entire study. We set a minimum 60-minute interval between each detection

First insights in terrestrial mammals monitoring in the Candelaria and ... 5

(video or photo) as an independent record of the same species (Rovero and Marshall 2009
). We defined this range to prevent the bias caused by overcounting the detected species.
We used Bushnell Trophy Cam HD Aggressor (model 119875). Cameras were active 24
hours a day, set at normal sensitivity in hybrid mode to record three pictures and one video
of 30 seconds per detection event. No attractants were used during sampling.

Table 1.
Sampling effort.

Sampling Date Active cameras Effective sampling days
campaign Mean (+ SD)
Start End Cerro Machay Cerro Machay
Candelaria Candelaria
F1 December April 2020 12 9 58.66 (+ 37.7) 58.3 (+ 60)
2019
F2 October 2020 December 14 12 49 (+ 17.4) 36.2 (+
2020 25.2)
F3 April 2021 July 2021 9 9 34.1 (+ 34.8) 36.6 (+
33.7)
F4 August 2021 October 2021 14 11 45.87(+ 29) 46.1(+
31.8)

Data analysis

Species relative abundance

We computed the species relative abundance, based on the average number of
independent camera trap records during 100 trap-nights in each Reserve during our study
(Rovero and Marshall 2009).

Diversity analysis

We estimated alpha and beta diversity for each Reserve. Diversity analyses were
conducted following the Hill numbers approach (i.e. the effective number of species) (Jost
2006, Chao et al. 2014). The first four Hill numbers were used: namely HO as species
richness, H1 derived from the Shannon-Wiener exponential index, H2 derived from
Simpson’s inverse index and H3 from the Berger-Parker index for species dominance.
However, we also included the standard indices from which Hill numbers are derived for
comparison. For dominance we applied the Berger-Parker index (d) and for evenness, we
used Simpson’s index |, Pielou’s index (J) and Smith & Wilson’s index (Smith and Wilson
1996). In order to compare whether there were significant differences between the alpha
diversity of the two localities, we performed a Dunn’s post hoc test. For beta diversity, we
took into account the beta partitioning approach, considering the contribution to differences
in beta diversity due to species replacement and richness difference (Carvalho et al. 2012,
Cardoso et al. 2014). We used Jaccard’s similarity index to assess this pattern. We used

6 Reyes-Puig J et al

interpolation and extrapolation curves to estimate diversity (Chao et al. 2014). For
extrapolation, we calculated non-parametric estimators, Chao1 which provide a lower
bound on the true diversity of the community, based on abundance data, Chao2 that allows
correct sample size using incidence data and Jackknife estimators that reduce the bias for
observed richness (Gotelli and Chao 2013). The model used for diversity estimators is
derived from sample-based data (incidence data). Here, we did not consider the individuals
(abundance data), but the sampling units, which in our case, are camera traps. In this
regard, presences are treated as incidences and absences as non-detections for each
species within each sampling unit. An incidence matrix is generated and the sum of the
rows is used to obtain the incidence-based frequency of a species. Hill numbers are
estimated, based on the Bernoulli distribution (Chao et al. 2014b). We performed our
analyses with the packages “vegan” (Oksanen et al. 2007), “BAT” (Cardoso et al. 2015),
“INEXT” (Hsieh et al. 2016) and “dunn.test” (Dinno and Dinno 2017) in R.

Site-occupancy modelling

We modelled the site-occupancy probability, defined as the proportion of habitat occupied
by a particular species under the assumptions of closed population within, but not between
seasons, sampling independence and equal probability of occupancy and detection across
sampling sites and surveys (MacKenzie et al. 2018). Occupancy models take into account
imperfect detection, preventing naive estimations derived from not detecting the species
even when it is present at a site, but also assess the effects of variables as triggers for
occupancy and detection probabilities (MacKenzie et al. 2002). We performed multi-
season occupancy models to assess the effects of habitat covariates in the occurrence of
the terrestrial mammal species in the study area, taking into account the effects of rain
seasonality and the presence of domestic dogs as factors leading to changes in occupancy
patterns between seasons. We hypothesised the effects of vegetation coverage, protected
areas, human accessibility and topography as site attributes affecting occupancy, whereas
sampling effort, topography and presence of dogs as sampling variables that influence the
probability of detection of wildlife species (MacKenzie and Bailey 2004) (Table 2). We
compiled site covariates from Ecuador’s National Thematic Cartography repository and a
satellite image classification of a Sentinel 2 image. The site variables were calculated from
the location of the camera traps, except the vegetation cover, which corresponds to the
average proportion at 1 km? and 250 m of buffer for each camera. Sampling covariates and
the presence of dogs were collected from the camera trap records. We estimated site-
occupancy probability with the package "unmarked" (Fiske and Chandler 2011).

We assessed the spatial arrangement of detections according to the spatial features within
the study area to identify potential characteristics influencing the occurrence of the
modelled species. We applied the Wilcoxon-Mann-Whitney test to assess the differences
between detections and non-detections within the study area and summarised the results
through the “ggstatsplot” R package (Patil 2021).

First insights in terrestrial mammals monitoring in the Candelaria and ...

Table 2.

Hypothesis for site-occupancy probability estimates. wy (Occupancy probability) and p (Detection
probability) y (Colonisation probability), € (extinction probability). For j = sites, i = species and Kj =
surveys at each site.

Variable

Vegetation (Veg)

Distance to
Protected Areas
(PAdist)

Distance to
creeks (Cdist)

Distance to roads
(Rdist)

Human
accessibility
(Acces)

Rugosity (Rugos)

Forest loss
(Floss)

Forest gain
(Fgain)

Ecological
integrity index
(Ell)

Rain seasonality
(Rain)

Model

logit (i)= B
o + mean
Veg;

logit (wi)= B
o + PAdist,

logit (wi)= B
ot G

logit (wi)= B
o + Rdist,

logit (wi)= B
o + Acces;

logit (wi)= B
o + Rugos;
logit (wi)= a
o + Rugos;

logit (wi)= B
o + Floss;

logit (wi)= B
o + Fgain;

logit (Wi)= B
ot Ell;

logit (¥i)= B
ot Rain;
logit (€)= B
ot Rain;

Description

Proportion of vegetation within the 1 km?

sampling cell and at 250 m buffer

surrounding each camera trap. We defined

three classes:

1. Natural vegetation

2. Pastures and crops

3. Areas without vegetation.

The nearest Euclidean distance from the
camera trap to the border of the protected

areas.

The nearest Euclidean distance from the

camera trap to creeks.

The nearest Euclidean distance from the

camera trap to roads.

Probability of human access to a pixel as a
function of the existence of roads, vicinity to
human settlements and navigable rivers (

Rios-Franco et al. 2013).

Raster obtained from the MODIS satellite
computed as a function of elevation, shape

and topographic slope.

Rate of tree canopy removal from 2000 -

2018 (RAISG 2020).

The establishment of tree canopy from
a non-forest state from 2000 — 2012 (Hansen

et al. 2013).

Forest condition determined by the degree of
human pressures and loss of habitat

connectivity (Grantham et al. 2020)

Indicator variable to reflect the rain regime
during the sampling campaign (Crespo et al.

2011, llbay-Yupa et al. 2021)

Conceptual model

1. The occupancy of wildlife
species increases at high
proportions of

natural vegetation.

2. The occupancy of wildlife
species increases at low
proportions of

pastures and crops.

3. The occupancy increases at
low proportions of areas without
vegetation.

The occupancy of wildlife species
increases closer to the protected
areas.

The occupancy of wildlife species
increases closer to creeks as
they provide natural corridors for
dispersal.

The occupancy of wildlife species
increases at a high distance from
roads.

The occupancy probability
increases at a low probability of
human accessibility.

The occupancy probability
increases at high levels of
rugosity as a proxy of less
disturbed areas.

The detection probability
decreases as rugosity increases.

The occupancy probability is
higher in areas with low rates of
forest loss.

The occupancy probability
increases in areas with high rates
of forest gain.

The occupancy probability
increases in areas with high
ecological integrity.

The occupancy changes between
sampling seasons according to
the rain regime.

8 Reyes-Puig J et al

Variable Model Description Conceptual model
Occurrence of logit (wi)= 8 Occurrence of domestic dogs recorded by The occupancy and detection
domestic dogs o + Dogs; the camera traps during the sampling probabilities are higher in areas
(Dogs) logit (wi)= a campaign where domestic dogs are absent.
o + Dogs; The occurrence of domestic dogs
logit (y¥i)= B leads to changes in occupancy
ot Dogs; between seasons.
logit (€)= B
o + Dogs;

Sampling effort logit (zj p) = Effective sampling days of the camera traps Detection probability increases as
(eff) Qo + eff Kj) more sampling effort devoted.

Photo-identification

We performed a photo identification only for Andean bears, based on their facial marks
(Garcia-Rangel 2012, Horn et al. 2014) (Fig. 2). We selected the camera-trap records
containing Andean bears with facial scenes subject for identification (i.e. clearly visible
facial marks). We classified the pictures according to the scene captured (e.g. right-side
face, left-side face, front scene, throat) and compared them according to the natural marks
photographed. We performed three independent reviews of the photographs between
sampling campaigns. In addition, due to the broad home range of the species (Rodriguez
et al. 2021), we identified the individuals recaptured between sample campaigns only. We
excluded the poor-resolution Andean bear pictures to prevent mistakes and ambiguities in
the identification.

Figure 2. EES

Colouring pattern used for individual identification of Andean bears. Picture by Santiago
Recalde.

First insights in terrestrial mammals monitoring in the Candelaria and ... g

Results

We documented 284 independent camera-trap records of medium and large-size terrestrial
mammals in 2814 sampling days at the Candelaria Reserve and 218 records in 2658
sampling days at the Machay Reserve. Species’ relative abundance ranged from 0.03 to

3.13 camera records per 100 sampling days (Table 3).

Table 3.

Photographic rate of the species recorded in the camera trapping monitoring at the Candelaria and
Machay Reserves during 2019 — 2021. We compared our findings with a previous study in the
Llanganates National Park.

Relative abundance (+ 90% Cl)

Our study Palacios et al. (2018)
Order Family Species Candelaria Machay
Artiodactyla Cervidae Mazama rufina 0.33 (0.38) 0.62 (0.95) 0.82 (0.81)
Pudu mephistophiles 0.16 (0.25) 0.69 (0.70)
Tayassuidae Tayassu pecari 0.04 (0.09)
Didelphimorphia Didelphidae Didelphis albiventris 0.3 (0.7) 0.1 (0.23)
Didelphis pernigra 0.15(0.28) 0.46 (0.4) 0.39 (0.35)
Carnivora Canidae Canis familiaris 1.42 (1.61) 0.76 (0.6)
Felidae Leopardus tigrinus 0.76 (0.77) 0.68 (0.43) 0.30 (0.26)
Puma concolor 0.8 (0.43) 0.99 (1.2) 0.65 (0.35)
Mustelidae Eira barbara 0.33 (0.3) 0.37 (0.33)
Mustela frenata 0.03 (0.08) 0.17 (0.41)
Procyonidae Nasua nasua 0.27 (0.27) 0.74 (0.26)
Nasua olivacea 0.24 (0.46) 0.07 (0.1) 0.26 (0.22)
Ursidae Tremarctos ornatus 3.13 (1.58) 2.32 (3.24) 0.86 (0.48)
Perissodactyla Tapiridae Tapirus pinchaque 0.4 (0.68) 1.64 (1.22)
Pilosa Myrmecophagidae Tamandua tetradactyla 0.3 (0.36)
Primates Cebidae Cebus yuracus 0.03 (0.06)
Rodentia Cuniculidae Cuniculus paca 0.04 (0.09)
Cuniculus taczanowskii 0.1 (0.25) 0.34 (0.28)
Dasyproctidae Dasyprocta fuliginosa 0.67 (0.71) 0.4 (0.56)
Leporidae Sylvilagus andinus 0.07 (0.16)
Sciuridae Microsciurus flaviventer 0.41 (0.97) 0.03 (0.08)

Syntheosciurus granatensis 0.05 (0.06)

0.44 (0.88)

10 Reyes-Puig J et al

Diversity analysis

We detected a total of 22 species of terrestrial mammals in 502 independent camera-trap
records. We recorded 17 species at the Candelaria and 19 at the Machay Reserve. Alpha
diversity appears to be similar between Reserves with a slight increase in the number of
species in Machay (Table 3). H3 showed some degree of dominant species in the two
localities (Table 4). This was corroborated by the total number of independent records
detected during sampling campaigns (Fig. 3), where the Andean bear and domestic dogs
exhibited the highest number of records. The Pieleu, Simpson and Smith & Wilson
Evenness indices showed, as a general trend, that the species relative abundances are not
equally distributed, with some degree of variation between sampling campaigns (Table 4).
We identified similar values for the Hill numbers in both localities (Table 4). Jaccard
Similarity index (Biota; = 0.64) suggested that the species composition is dissimilar, with
some species recorded either in Candelaria or Machay (Suppl. material 1) (Table 3, Fig. 3
B). Most of the beta diversity was explained by beta richness difference rather than by beta
replacement (Brep = 0.17, Brich = 0.47).

The estimated diversity for Candelaria and Machay communities through rarefaction and
extrapolation curves indicated the same trend showed by alpha diversity, identifying
Machay as the more diverse locality (Fig. 4, Table 4). The extrapolation to reach the
asymptote in species diversity within localities can be reached at 20 sampling units (Fig. 4
A). The completeness or sample coverage was high in both locations, reaching the
asymptote already at rarefaction (Fig. 4B). First-order Jackknife and Chao estimators were
congruent in their estimates, identifying the potential addition of at least two more species
in Candelaria and Machay; however, Machay would increase the larger number of species
(Table 5).

Table 4.

Summary of medium- and large-size mammal’s diversity indices and Hill numbers. HO: species
richness, H1: Shannon-Wiener exponential, H2: the reciprocal of Simpson and H3: Berger-Parker
index, J: Pielou’s index, E: Simpson's index.

Index Candelaria Machay

F1 F2 F3 F4 Total F1 F2 F3 F4 Total
HO (S) 13 12 7 12 17 13 11 14 12 19
H1 (exp H') 8.62 9.23 3.65 4.76 10.15 6.34 6.04 10.69 10.31 11.31
H2 (1/D)) 6.12 7.76 247 2.86 7.28 3.91 3.88 8.69 9.29 8.40
H3 (d) 4.85 6.93 2.09 2.37 590 3.14 3.15 7.63 7.61 6.90
J 0.83 0.89 067 063 082 0.72 0.74 089 094 0.82
E 0.47 0.65 0.35 0.24 0.43 0.30 0.35 0.62 0.77 0.44

Smith & Wilson index 0.60 065 0.76 0.42 0.40 0.64 0.61 0.69 0.71 0.40

First insights in terrestrial mammals monitoring in the Candelaria and ... 11

Locality
1 candetana
By vecnay

Species

100°

Sampie

e * 2
ee e re 3 s a és ef ro Pa ar,
& & ' vr er ew ot oe ¢ s . »
A 6” @ o* Ye ¢ 9 fe ~ a a oa x
a)

Species

Figure 3. EES

Documented independent records for medium and large-size terrestrial mammal species. A
By family; B By species; C By sampling campaign.

Table 5.

Diversity estimators of medium- and large-size mammals in the Candelaria and Machay Reserves.
Obs: Observed species richness, S1: singletones, S2: doubletones, Jack1ab: first order Jackknife,
Jack2ab: second-order Jackknife, Chao 1: Chao estimator based on abundance and their bias-
corrected complements (Jack1abp, Jack2abp, Chao1P).

Obs $1 $2 Jacklab Jacklabp Jack2ab Jack2abp Chao1 Chao1P

Candelaria Fi 13 2 0 15 15.36 17 17.4 14 14.33
F2 12 2 1 14 14.39 15 15.42 12.5 12.85
F3 7 3 1 10 11.84 12 14.2 8.5 10.06
F4 12 7 1 19 25.47 25 33.51 22.5 30.16
Machay F1 13 3 3 16 16.85 16 16.85 13.75 14.48
F2 11 7 1 18 25.29 24 33.72 21.5 30.21
F3 14 7 2 21 26.25 26 32.5 21 26.25

F4 12 1 1 13 13.09 13 13.09 12 12.08

12 Reyes-Puig J et al

A
>
a7) aaa oes"
@ 20; 6S
———————— Ct ti‘ (ie,
& LS.
”
@
Oo
a 10; f_- interpolated == extrapolated
”
~*~ Candelaria Machay
0 10 20 30
Number of sampling units
B
1.0) et
r :
Le?)
© 0.8-
o>)
>
fe}
Oo
® 0.6-
Qa
E
is)
204
0 10 20 30
Number of sampling units
C
Py
= ad
5 20: *
2 ,
ne)
i
o
® ,
10° _
0.4 0.6 0.8 1:0
Sample coverage
Figure 4. EES]

Rarefaction (solid lines) and extrapolation (dashed lines) curves for the medium- and large-
size mammal communities in the Candelaria and Machay Reserves. A Estimated species
diversity according to the sampling units; B Estimated sample coverage according to the
sampling units; C Estimated species diversity according to the sample coverage.

Site-occupancy modelling

We estimated the occupancy probability for the Andean bear, puma, oncilla and domestic
dogs since they exhibited the highest number of detections recorded during the study (Fig.
3C). Occupancy probability was higher for the Andean bear and puma (VY = 0.6 and Y =
0.4, respectively), while detection probability was higher for the Andean bear and domestic
dogs (p = 0.27 and p = 0.22, respectively) (Table 6). However, we did not find any
significant effect of the candidate variables in the occupancy probability for the species
modelled (Suppl. material 2).

First insights in terrestrial mammals monitoring in the Candelaria and ... 13

Table 6.

Average occupancy (w) and detection probabilities (p), based on the null models (w(.)p(.)) for the
Andean bear, puma, oncilla and dogs in the Candelaria and Machay Reserves.

Delta AIC w (+ SE) p (=SE)
Andean bear 4.59 0.6 (0.1) 0.27 (0.06)
Puma 3.34 0.4 (0.1) 0.17 (0.08)
Oncilla 0 0.33 (0.1) 0.1 (0.08)
Domestic dogs 0 0.2 (0.1) 0.22 (0.2)

According to the camera traps placement, we observed that 78%, 93% and 74% of Andean
bear detections were significantly more frequent in cells with a high proportion of natural
vegetation, at very low levels of vegetation absence at a 1 km? scale and in areas with low
levels of rugosity, respectively (rugosity index range = 1.05-1.3) (Fig. 5). Pumas were
recorded significantly more frequently in cells where the proportion of natural vegetation
was high both at 1 km? (78% of detections) and at the buffer scale (87% of detections), but
also when the proportion of vegetation absence was low at both scales (Fig. 6). On the
contrary, 87% and 73% of domestic dog detections were more frequent in cells with a
decreasing proportion of natural vegetation and with an increasing percentage of pastures
and crops at the buffer scale (Fig. 7). We did not find any relationship between the
detections of Oncilla and the spatial variables evaluated.

A B

Wtann-Wheney = 780.50, p = 6.74e-03, PA | = -0.32, Close, [-0.51, -0.10], Move = 96 W\tann-wniney = 1582.50, p = 1.09€-03, P2% = 0.38, Close, (0.16, 0.56], Mop, = 96

®

a
i

Percentage of Natural vegetation at 1 Km2
.
Percentage without vegetation cover at 1 Km2

.
- Fame) —
median =

ot o-
Not detected Detected Detected
(n = 50) (n= 46) (n = 46)
Detections Detections
Wyrann-Whitney = 1642,00, p =3,08e-04, 72%. = 0.43, Closs, (0.22, 0.60], Man. = 96
1.3
1.2:
>» 1.20-
BE [Brean 1.18
>
s
eit
1.1
1.05- .
t cted D tected
= 46)
Detections
Figure 5. EE

Arrangement of detections of Andean bears according to the spatial variables in the
Candelaria and Machay Reserves. A Detections according to the percentage of natural
vegetation at 1 km; B Detections according to the percentage of the area without vegetation
at 1 km?; C Detections according to the rugosity index.

14 Reyes-Puig J et al

Whtann-Whiney = 540.00, p = 0.01, 72% |, = -0.36, Closy, [-0.57, -0.10], Mong = 96 Wyrann-Wneney = 577.50, p = 0.02, 72°, = -0.31, Class, [-0.53, -0.05], Moog = 96
100- = ms =
¢ = 5 ii... =99.20
7 E
= 8
= a
- °
§ 0- . S 90- —
= :
3 z ta
$ o
> a
= 30- 8
2 ope
; i
] z
$70 5
=: & 70-
: z”
5 5
* 60 ome 3 ae
Not detected Detected Not detected Detected
(n= 73) (n= 23) (n= 73) (n= 23)
Detections Detections
Wtann-wniney = 1272.50, p = 1.30€-04, 72% | = 0.52, Close, (0.29, 0.69]. Moo = 96 «_ Watann-ivninay = 1099.00, p = 6.182-03, 72%... = 0.31, Close, (0.05, 0.53), Mp5 =96
12- €
Ps _* 2 ~-
= =
5 & 15° eos
> 9- a
3 e 3
Le 2
s 8
= g
3 2 10-
S 6 3
$ oe 3
2 $
= * 3 ao
3 3. B s-
2 | =
= o
5 :
& 0- $ o-
: S
Not detected Detected =
(n =73) (n= 23)
Detections Detections

Figure 6. EES]

Arrangement of detections of Pumas according to the spatial variables in the Candelaria and
Machay Reserves. A Detections according to the percentage of natural vegetation at 1 km2; B
Detections according to the percentage of natural vegetation at 250 m buffer; C Detections
according to the percentage of the area without vegetation at 1 km?; D Detections according to
the percentage of the area without vegetation at 250 m buffer.

A B

Whrann-wnitney = 808.50, p = 0.04, 2K. = 0.33, Closo, (0.02, 0.58], Mops = 96 Wtonn-whitney =413.00, p = 0.04, 722° | = -0.32, Clos [-0.57, -0.01], Movs = 96

100- ——— ——— . “ +
- [finedan = 98.40
°, ~ [Finwtan = 94.55 |

90-

70-

Percentage of Natural vegetation at 250m buffer
.
+

Percentage of pastures and crops at 250m buffer

ooms 0- Cage. 07

Not detected Detected Not detected Detected
(n = 81) (n= 15) (n = 81) (n = 15)

Detections Detections
Figure 7. EES

Arrangement of detections of domestic dogs according to the spatial variables in the
Candelaria and Machay Reserves. A Detections according to the percentage of natural
vegetation at 250 m buffer; B Detections according to the percentage of pastures and crops at
250 m buffer.

Photo-identification

We reviewed 756 camera-trap records of Andean bears collected during the study, 72.5%
of which correspond to the Candelaria Reserve and 27.5% to the Machay Reserve,
comprising 135 independent records. We identified at least 26 Andean bears during the

First insights in terrestrial mammals monitoring in the Candelaria and ... 15

study, 15 in the Candelaria and 11 in the Machay Reserve (Figs 8, 9). According to the
sexual dimorphism, marking behaviour and body size, at least 53% of the individuals
identified in the Candelaria and 45% in the Machay Reserve corresponded to adult males,
while in the latter, only 27% of the individuals identified corresponded to subadults.
Nevertheless, we were unable to identify females. In addition, we recorded seven
recapture events of four individuals at the Candelaria (Fig. 10) and two recaptures of two
individuals at the Machay Reserve between sampling campaigns (Fig. 11). We did not
record recaptures of bears between Reserves during the study.

Figure 8. EES]

Andean bears identified at the Candelaria Reserve, based on their natural facial marks.
Letters correspond to different individuals identified during the study.

Figure 9. EES]

Andean bears identified at the Machay Reserve, based on their natural facial marks. Letters
correspond to different individuals identified during the study.

16 Reyes-Puig J et al

Legend

ia) 1 Km2 cells

E30 Highway
fea Candelaria Reserve

Figure 10. EES
Andean bears recaptured in different sampling campaigns at the Candelaria Reserve.

Legend

Sampling campaign
A Fi

m F2

@ F3

* OFS

Machay Reserve
sy Bolivia C_] 1 Km2 cells
ye — £30 Highway

1°22'0"S

Brazil

1°24'0°S
4

78°18'0°W 78°16'0°(W

Figure 11. EES

Andean bears recaptured in different sampling campaigns at the Machay Reserve.

Discussion

The Andes of Ecuador, Peru and Bolivia are amongst the areas with the highest diversity
and endemism of terrestrial mammals in the Neotropics (Ojeda 2013, Noguera-Urbano and

First insights in terrestrial mammals monitoring in the Candelaria and ... 17

Escalante 2015). Our study constitutes the first long-term camera-trap monitoring study
conducted in a strategic area that promotes the habitat connectivity between the
Llanganates and Sangay National Parks in the eastern slopes of the Andes of Ecuador (i.e.
CELS) (Lessmann et al. 2014, Cuesta et al. 2017). Our results reflected that the species
richness of terrestrial mammals documented at the Candelaria and Machay Reserves is
almost twice that of those recorded in a larger area in the Llanganates National Park
(Palacios et al. 2018), although the sampling effort devoted in our study was greater (2320
trap-nights vs. 5232 trap-nights in our study) (Table 3). The diversity analysis showed that
the species compositions recorded were moderately different in each Reserve, mainly due
to species turnover, which may be a consequence of the species' ecological tolerance
(Legendre 2014). For instance, we detected three unique species at the Candelaria
Reserve, whereas five species were only detected at the Machay Reserve (Table 3). Our
results revealed the dominance of Andean bears and domestic dogs in the study area (Fig.
3C). Accordingly, the relative abundance of Andean bears in our study greatly exceeded
those reported by Palacios et al. (2018). We documented unprecedented detections of
domestic dogs in the study area (Rios Alvear and Reyes Puig 2013, Palacios et al. 2018),
warning about the increasing human-associated disturbances and the negative interactions
between wildlife and dogs (Lenth et al. 2008, Zapata-Rios and Branch 2016). Similarly, this
could have influenced the non-detection of other terrestrial mammals occurring in the study
area (e.g. stripped hog-nosed skunk and Andean fox (Palacios et al. 2018)). In this regard,
the lack of detections of mountain tapirs in camera traps during our study at the Candelaria
Reserve is intriguing. This is not new, since previous camera-trap studies in Candelaria did
not detect the species (Rios Alvear and Reyes Puig 2013), even when there were identified
eight different individuals at a 10 km distance in a smaller area and with less sampling
effort than the current study (Reyes Puig and Rios Alvear 2013). According to the species
richness expected, we have recorded approximately 73% of the terrestrial mammal
species in the area. We expect greater true species richness in the Machay Reserve since
42% of the species recorded are either rare (i.e. singletons and doubletons) or unique
species (i.e. species recorded only in one Reserve) (Table 5).

The number of detections conditioned the species occupancy estimation since four of the
22 species documented contained 53% of the total detections during the study, while the
18 species remaining contributed between 0.2 and 6.6% of detections individually (Fig. 3
C). Additionally, due to the low sampling size, we were unable to identify covariate effects
in the occupancy of the species modelled. However, the null model (i.e. which includes no
covariates for detection and occupancy probabilities) revealed that the puma, oncilla and
the Andean bear use between 30% and 60% of sampling units in the Candelaria and
Machay Reserves, with the Andean bear the species with the highest detection probability
(p = 0.27). The occupancy probability estimated for Andean bears in the Candelaria and
Machay Reserves is similar to that observed by Springer (2018) in the Chocd-Andean
region (Y = 0.6 our study vs. Y = 0.63) as well as the apparent positive effects of natural
forests in the frequency of Andean bear detections within CELS. However, we surveyed a
smaller area (78 km2 vs. 804.77 km2) and deployed half the number of camera traps (30
vs. 70 cameras). Our results suggest the occurrence of Andean bears in the Candelaria
and Machay Reserves is not affected by the presence of humans and dogs (Springer 2018

18 Reyes-Puig J et al

, Rojas-VeraPinto et al. 2022), since we detected Andean bears close to human-associated
features (e.g. roads, pastures and crops) and in camera-traps where we previously
documented domestic dogs. However, this must be tested explicitly by, for example,
assessing changes in the activity patterns which allows elucidating changes in the bear
occurrence as a response to domestic dogs' presence (Zapata-Rios and Branch 2016,
Zapata-Rios and Branch 2018). Moreover, the high frequency of detections in cells with a
low proportion of vegetation absence may reflect the species’ preference for areas that
provide natural cover (Garcia-Rangel 2012). However, inhabitants of El Placer, near the
Candelaria Reserve, have observed Andean bears roaming through abandoned pastures
and feeding on naranjilla crops (Solanum quitoense). In addition, we observed more
detections in low rugosity areas, opposite to that reported by Rojas-VeraPinto et al. (2022),
possibly due to the species exploiting crops for feeding resources (Garcia-Rangel 2012).
Detections of pumas were common in cells with almost complete natural vegetation cover
and without open areas, suggesting the species evade human disturbance, opposite to
what was observed by Figel et al. (2021). On the contrary, our observations suggest that
domestic dogs roam in natural habitats close to areas associated with human presence
(e.g. pastures and crops) (Paschoal et al. 2018, Zapata-Rios and Branch 2018). Thus,
even though we did not identify explicit effects of the presence of domestic dogs on the
probability of pumas occupancy, the spatial arrangement of puma detections does not
coincide with the areas where domestic dogs were more frequently detected, suggesting
puma's avoidance behaviour of dogs (Zapata-Rios and Branch 2018).

The number of Andean bears identified in our study exceeds that documented by Molina et
al. (2017) in the Choco-Andean region and doubles that observed in a previous study at
the Candelaria Reserve (Rios Alvear and Reyes Puig 2013), although our sampling effort
was greater (1224, 1050 and 5232 trap-nights, respectively). We are convinced that the
true number of bears in the study area is larger than the observed number since we
excluded the poor-resolution camera trap records of Andean bears to prevent uncertainty
in the photo identification. We recaptured six Andean bears during our study, both in
consecutive sampling campaigns and throughout the entire fieldwork (Figs 10, 11). In
addition, we suspect the individual C, recorded at the Candelaria Reserve, was previously
detected in a survey at the Chamanapamba Natural Reserve in 2011, 10 km to the west of
our study area (Rios Alvear and Reyes Puig 2013) (Fig. 12). To our knowledge, this record
depicts the oldest recapture of an Andean bear after eleven years. Due to the individuals
identified, our study suggests that Candelaria, Machay and Chamanapamba Reserves, as
well as many other natural vegetation remnants within CELS, support the occurrence of
landscape species (e.g. Andean bear) and would potentially contribute to the wildlife
dispersal between protected areas (Sanderson et al. 2002, Crespo-Gascon and Guerrero-
Casado 2019). Additionally, these areas are important refuges of suitable habitats that
provide resting and foraging areas for terrestrial mammals within CELS and are critical for
managing the habitat connectivity between the Llanganates and Sangay National Parks
(Reyes Puig and Rios Alvear 2013, Rios Alvear and Reyes Puig 2013, Lessmann et al.
2014, Reyes-Puig et al. 2015, Rios-Alvear and Reyes-Puig 2015, Cuesta et al. 2017).

First insights in terrestrial mammals monitoring in the Candelaria and ... 19

Our study highlights the importance of the Candelaria and Machay Reserves as highly
diverse areas encroaching in a human-dominated landscape. We expect our results serve
as a Starting point for establishing a participative landscape scale monitoring network
promoting the involvement of conservationists and private stakeholders in CELS. We
expect our results to contribute to strengthening the management capacity in the
Llanganates and Sangay National Parks, allowing park managers to capitalise on
conservation outcomes through coordinated work with local conservationists. In addition,
we expect local governments to take advantage of our information to make informed
decisions regarding the land-use change and management taking into account the
importance of private reserves for strenghthening the habitat connectivity and supporting
the endeavour of local conservationists within CELS.

Figure 12. EES)

Recapture of an Andean bear recorded in 2011 at the Chamanapamba Natural Reserve (Rios
Alvear and Reyes Puig 2013) (left) and the individual C recorded at the Candelaria Reserve in
our study (right).

Acknowledgements

We thank WWF Ecuador for supporting our fieldwork campaigns and the Asociacion de
Turismo Comunitario Quinde Warmi and Rolando Pena for their support and assistance
during the fieldwork. We thank Lou Jost, Heitor Bissoli-Silva and one anonymous reviewer
for their valuable comments and suggestions to improve the manuscript. We thank World
Land Trust, Rainforest Trust, Puro Coffee, Naturetrek and the Orchid Conservation Alliance
for their help in the conservation of Fundacion EcoMinga's reserves in CELS. We highlight
our partners' conservation efforts in CELS since their commitment makes this labour
possible. This research was supported by Universidad San Francisco de Quito USFQ,
Museo de Zoologia & Laboratorio de Zoologia Terrestre and Instituto iBIOTROP. CRP work

20 Reyes-Puig J et al

is supported by COCIBA grants (HUBI ID: 12267), USFQ. We thank the Ministry of
Environment of Ecuador for the framework agreement MAE-DNB-CM-2018-0106-USFQ.

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Supplementary materials

Suppl. material 1: SM1 EE

Authors: Carolina Reyes-Puig, Gorky Rios Alvear, and Juan Pablo Reyes Puig

Data type: Beta diversity coefficients

Brief description: Accumulated beta diversity considering the beta diversity partitioning
approach.

Download file (13.81 kb)

Suppl. material 2: Detailed outcomes of the occupancy models assessed. [5]

Authors: Gorky Rios-Alvear
Data type: Occupancy modelling outcomes
Download file (186.24 kb)