Revista de Biología Tropical, ISSN: 2215-2075, Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

Unveiling activity patterns of the deer Odocoileus virginianus

(Artiodactyla: Cervidae) and its predators in Mexico’s Arid Region

Fernando X. Plata-Pérez1*; https://orcid.org/0000-0003-0728-7510

Diana P. Urbina-Flores1; https://orcid.org/0000-0001-6512-5742

Brenda Duana Hernández1; https://orcid.org/0009-0000-7521-2321

Oscar A. Villarreal-Espino-Barros2; https://orcid.org/0000-0002-2588-1436

Adrián Gloria-Trujillo1; https://orcid.org/0000-0002-2588-1436

German D. Mendoza-Martínez3; https://orcid.org/0000-0002-8613-6464

1. Departamento de Producción Agrícola y Animal, Universidad Autónoma Metropolitana, Unidad Xochimilco.

Calzada del hueso 1100, Villa quietud, alcaldía Coyoacán, Ciudad de México, Mexico; ppfx2221@correo.xoc.uam.mx

(*Correspondence), dian.urbina.flores@gmail.com, agloria@correo.xoc.uam.mx

2. Facultad de Medicina Veterinaria y Zootecnia, Benemérita Universidad Autónoma de Puebla. km. 7.5 Carretera

Cañada Morelos. El Salado, Tecamachalco, Puebla; oscar.villarrealeb@hotmail.com

3. Doctorado en Ciencias Agropecuarias, Universidad Autónoma Metropolitana, Unidad Xochimilco. Calzada del hueso

1100, Villa quietud, alcaldía Coyoacán, Ciudad de México, Mexico; gmendoza@correo.xoc.uam.mx

Received 04-VIII-2023. Corrected 01-XI-2023. Accepted 21-III-2024.

ABSTRACT

Introduction: Size, predator presence, and habitat nutritional quality influence herbivorous species’ activity pat-

terns and resource utilization.

Objective: To determine the relative abundance and activity patterns of white-tailed deer (Odocoileus virginia-

nus) and their main predators.

Methods: The study was conducted in the WMU “Bienes Comunales Santa Cruz Nuevo” in Totoltepec de

Guerrero, Puebla, Mexico. Twenty-two quadrants were randomly selected, and camera traps were installed. Over

two years (2018-2020), wildlife visits were recorded to estimate the relative abundance index (RAI), activity pat-

terns, and overlap coefficient (Dhat1) of white-tailed deer and their predators based on their activity schedule.

Results: The estimated RAI for deer was 7.2 %, while it was 3.4 % for coyotes (Canis latrans), 2.3 % for bobcats

(Lynx rufus), and 0.14 % for pumas (Puma concolor). White-tailed deer were observed in 31 % of the camera

traps, while coyotes were captured in 68 % of them. The overlap of the activity schedule, Dhat1, between deer and

coyotes was 0.18. In contrast, the activity overlap between foxes and deer was higher (Dhat1: 0.2979; EE 0.037)

based on the analysis of variance. The activity pattern of coyotes indicated they were crepuscular, with increased

activity during the afternoon and night. However, an increase in activity synchronized with deer’s patterns was

also observed. The bobcat coincided with deer in 10 % of the cameras, but due to the limited number of observa-

tions, it was not possible to estimate the activity overlap between these species.

Conclusions: The activity overlap between white-tailed deer and foxes is more significant than that of deer and

coyotes in this region. The activity overlap between deer and coyotes is lower compared to other parts of the

world.

Key words: abundance; camera traps; deer habitat use; Tehuacán-Cuicatlán valley; Lynx rufus.

https://doi.org/10.15517/rev.biol.trop..v72i1.55515

TERRESTRIAL ECOLOGY

2Revista de Biología Tropical, ISSN: 2215-2075 Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

INTRODUCTION

The Mixtec is a mountainous area between

Puebla and Oaxaca in Southeastern Mexico.

There converges a chain of mountains named

the “Sierra Madre Oriental,” the Neo volcanic

Axis, and another chain of mountains named

the “Sierra Madre del Sur.” Its elevation ranges

from 167 to 3 347 meters above sea level,

making it an area with a predominance of

mountains interspersed with canyons, ravines,

valleys, and plateaus (Hernández-Aguilar et al.,

2017). One of the essential valleys within this

zone is the Tehuacán-Cuicatlán valley, located

Southeast of Puebla. This valley is the arid or

semi-arid zone with North America’s most

extraordinary biological diversity. It has the

densest columnar cacti forests on the planet,

which form a unique landscape associated with

agaves, yuccas, holm oaks, bromeliads, and

burserae (UNESCO, 2018). Under these con-

ditions, accurately estimating deer habitat use

and abundance can be difficult because they are

in ecosystems with dense vegetation, thus mak-

ing detection difficult (Urbanek et al., 2012).

However, obtaining reliable estimates of

terrestrial herbivore abundance can be used

to assess the management of wild species with

ecological and economic value. Within these

estimates, abundance makes it possible to eval-

uate conservation efforts, establish hunting

quotas, estimate prey availability for carnivores,

and evaluate the management of the area in

question (Palmer et al., 2018). Under these

conditions, camera traps are used in wildlife

estimates due to their objectivity, ease of use,

and ability to generate information on large

numbers of species. Camera traps are primar-

ily designed to document species richness,

occupancy, and abundance indices; estimate

the abundance of individually identifiable spe-

cies in a capture-recapture framework; and

determine their activity patterns (Tanwar et

al., 2021). A central issue in wildlife manage-

ment is understanding how species respond to

environmental changes. Their distribution is

RESUMEN

Revelando patrones de actividad del venado Odocoileus virginianus (Artiodactyla: Cervidae)

y sus depredadores en la región árida de México

Introducción: El tamaño, la presencia de depredadores y la calidad nutricional del hábitat influyen en los patro-

nes de actividad y utilización de recursos de las especies herbívoras.

Objetivos: Determinar la abundancia relativa y los patrones de actividad del venado cola blanca (Odocoileus

virginianus) y sus principales depredadores.

Métodos: El estudio se realizó en la UMA “Bienes Comunales Santa Cruz Nuevo” en Totoltepec de Guerrero,

Puebla, México. Se seleccionaron al azar 22 cuadrantes y se instalaron cámaras trampa. Durante dos años (2018-

2020), se registraron las visitas de fauna silvestre para estimar el índice de abundancia relativa (IAR), los patrones

de actividad y el coeficiente de superposición (Dhat1) del venado cola blanca y sus depredadores en función de

su horario de actividad.

Resultados: El IAR estimado para venado fue de 7.2 %, mientras que para coyote (Canis latrans) de 3.4 %, el

gato montés (Lynx rufus) 2.3 % y puma (Puma concolor) 0.14 %. Se observaron venados cola blanca en el 31 %

de las cámaras trampa, mientras que se capturaron coyotes en el 68 % de ellas. La superposición del programa de

actividad, Dhat1, entre venados y coyotes fue de 0.18. En contraste, la superposición de actividad entre zorros y

venados fue mayor (Dhat1: 0.2979; EE 0.037). El patrón de actividad de los coyotes indicó que eran crepusculares,

con mayor actividad durante la tarde y la noche. Sin embargo, también se observó un aumento en la actividad sin-

cronizada con los patrones de los venados. El gato montés coincidió con el venado en el 10 % de las cámaras, pero

debido al limitado número de observaciones, no fue posible estimar el traslape de actividad entre estas especies.

Conclusiones: La superposición de actividades entre venados cola blanca y zorros es más significativa que entre

venados y coyotes en esta región. El traslape de actividad entre venados y coyotes es menor en comparación con

otras partes del mundo.

Palabras clave: abundancia; cámaras trampa; uso de hábitat del venado; valle Tehuacán-Cuicatlán; Lynx rufus.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

increasingly affected by anthropogenic stress-

ors as habitat fragmentation, urban develop-

ment, and accelerating global climate change

(Combe et al., 2022). These alterations, togeth-

er with the presence of predators (Higdon et

al., 2019) and the nutritional quality of the

habitat, have shown that the activity patterns

and the use that a herbivorous species makes

of this resource change depending on its size

(Roque et al., 2021).

Regarding activity patterns, there is exten-

sive research on white-tailed deer in tem-

perate and cold ecosystems (Michel et al.,

2020; Pustilnik et al., 2021). In these habitats,

the activity pattern of the white-tailed deer

(Odocoileus virginianus, var. texanus) is asso-

ciated with the presence of the coyote (Canis

latrans), which is considered the predator par

excellence of this species in the United States

(Crawford et al., 2021). In South America, the

habitat use, and abundance of white-tailed

deer vary widely. However, habitat use patterns

generally reflect the quality and abundance of

resources in focal areas, influencing variations

in habitat use and deer fitness in a landscape

(Duquette et al., 2020).

In Mexico, some researchers evaluated the

activity patterns in the country’s north and

south (Gallina & Bello Gutierrez, 2014; Retana

Guascón et al., 2015). However, they did not

describe the interaction of the activity pattern

concerning the presence of predators. It is

likely that because the size of the white-tailed

deer (Odocoileus virginianus var. mexicanus)

is smaller than that of the Texanus (Villarreal-

Espino et al., 2011), the type of predator with

which this pattern is associated in the center of

the country may be different from the coyotes.

Additionally, and due to the physiographic

characteristics of the Mixtec, the activity pat-

terns of white-tailed deer are likely different;

thus, the work aimed to determine the effect

of the presence of predators on the pattern of

activity in white-tailed deer and the relative

abundance of mammals and birds in the area.

MATERIALS AND METHODS

Study area: We carried out this research at

the Wildlife Management Unit (WMU) at Santa

Cruz Nuevo, in Totoltepec de Guerrero, Puebla

(18°17’44” N & 97°48’35” W). The prevailing

climates are semi-warm sub-humid with sum-

mer rains (Aw -Köppen classification; INEGI,

2021) and temperate sub-humid with summer

rains (Cfa-Köppen classification; INEGI, 2021).

The area is part of the Balsas River hydro-

logical region (Villarreal-Espino et al., 2011),

presenting a marked seasonality. The range of

inclination of the slope is between 20 and 70 %,

with shallow soils from 0 to 25 cm (INEGI,

2021). The types of vegetation present are low

deciduous forest, xeric scrub, Central Mexi-

can submontane mixed desert scrub, medium

scrub, and medium thorny sub deciduous forest

(Barrera-Salazar et al., 2015).

Wildlife monitoring: We randomly select-

ed twenty-two sites and established 50 m2 plots

(Anderson et al., 2013). We recorded the Alti-

tude (Meters above sea level; masl) and quanti-

fied basal and escape coverage within these

areas. In each of them, we installed a camera

trap and recorded through the programming

of the equipment, the location, date, and time;

with the recorded ecological data, we esti-

mated the sampling duration (Effort) (Bowler

et al., 2017). We checked the cameras every

16 weeks for approximately two years (2018

to 2020). We carefully observed each photo-

graphic sequence to determine the independent

captures. When we could not identify with cer-

tainty the gender, class, age, and unique body

markings of the photographed animals, we

considered successive captures (with an interval

of fewer than five minutes) of the same species

a single event. Also, we considered an inde-

pendent capture if another individual of a dif-

ferent species appeared within two continuous

sequences of less than five minutes. We used

the free access software Wild.ID (Mandujano

4Revista de Biología Tropical, ISSN: 2215-2075 Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

& Morteo-Montiel, 2018) to facilitate order-

ing the photographic folders derived from the

sampling. Also, we determined the presence-

absence (number of individuals and species) by

observing the captured images.

Data analysis: We realized these analyses

using R software version 4.3.1 (Crawley, 2013)

and we estimated the activity patterns of deer

and predators (coyote, fox, and bobcat) and

graphed based on the activity hours. We used

the overlap Plot and overlap Est package to

graph them in RStudio (Meredith & Ridout,

2009) using the “Kernel density estimator,”

which is a non-parametric method that allows

for estimating the probability density function

of a random variable from a finite number of

observations (samples) and for modeling the

habitat use curve throughout a day. This pro-

gram estimates the overlap coefficient (Dhat1);

the delta value goes from 0 to 1, where 1 implies

a significant coincidence of schedules and 0

implies that the activity patterns are entirely

different (Mandujano, 2019). With the estimat-

ed Dhat1 values for each site where the overlap

of deer with foxes or coyotes occurred and the

mean obtained from the resampling (bootstrap)

carried out by the same subprogram, we carried

out an analysis of variance with a completely

random model using both determined and esti-

mated values of Dhat1 for each type of overlap

as repetitions and deer-fox (T1) and deer-coy-

ote (T2) overlap as treatments. We performed

Stepwise Discriminant Analysis considering the

escape cover, the basal cover of the area, and the

altitude. We carried out these last analyses with

the JMP8 program from SAS (Sall et al., 2017).

The relative abundance index (RAI) esti-

mate was derived from recording the presence

and absence of all species caught, assuming

that estimates of observed abundance are pro-

portional to the number of detections per site

and that variation between sites is unknown

(Duquette et al., 2020). Therefore, the RAI of

each species was calculated as the number of

independent photo-capture events of the same,

divided by the sum of the total sampling effort

of all the cameras multiplied by 100 (Gronwald

& Russell, 2021), under the following consid-

erations: the RAI considers a positive linear

relationship between the abundance of the

population and the same index; it assumes that

individuals of the same species behave similarly

in different localities and seasons of the year;

and it assumes a constant probability of detec-

tion and that it is not affected by the location of

the cameras (Mandujano, 2019).

RESULTS

A total of 347 Urocyon cinereoargente-

us (gray fox records), 105 white-tailed deer

records, fifty coyote records, thirty-four bobcat

records, and two cougar records were obtained.

White-tailed deer were present in 36 % of the

camera traps (Fig. 1), while predators had a

greater distribution in the area: the coyote was

captured in 68 %, the bobcat in 54 %, the puma

only in 4.5 %, and the fox in 90 % of them.

The gray fox converged in 48.2 % of the

sites with the coyote and in 24 % of the sites

with the white-tailed deer; it is important to

point out that in all the places where the gray

fox and the white-tailed deer converged, either

the coyote or the bobcat was always present.

The results of this work show a greater abun-

dance of foxes than coyotes in a ratio of 1.6:1.

Estimation of the RAI of deer and preda-

tors: Table 1 shows the RAI and the frequency

of occurrence in camera traps. The RAI esti-

mate for white-tailed deer was 6.06 %. Rabbits

and rodents have a higher abundance (53.17

and 21.92 % on average). Rodents are common-

ly distributed in disturbed natural ecosystems

or have changed their homogeneous landscape

matrix by activities derived from land use

change, mainly by agricultural activities.

The analysis of variance showed that the

activity overlaps between fox and deer is higher

than that between deer and coyote (Dhat1;

0.2979, SE 0.037 vs Dhat1; 0.1869 SE 0.034;

α < 0.05). Fig. 2 shows the activity overlaps

between the white-tailed deer and the gray fox:

it can be observed that the behavior of the gray

fox is very similar at both elevation levels. In

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

Fig. 1. Distribution of white-tailed deer and potential predators in camera traps.

Table 1

Relative abundance index and frequency of appearance in camera traps.

Genus / Species Common name No. of observations RAI % No. of cameras Frequency %

Oryctolagus cuniculus Rabbit 824 56.63 7 86.36

Rattus novaeguineae Rat 366 25.15 2 22.73

Peromyscus mekisturus Mouse 354 24.33 26 63.64

Urocyon cinereoargenteus Grey Fox 347 23.85 1 90.91

Bos primigenius Cow 154 10.58 3 36.36

Odocoileus virginianus White-tail deer 105 7.22 4 31.82

Canis lupus familiaris Dog 66 4.54 15 9.09

Procyon lotor Raccoon 54 3.71 14 45.45

Mephitis mephitis skunk 52 3.57 5 77.27

Canis latrans Coyote 50 3.44 8 68.18

Lynx rufus Bobcat 34 2.34 2 54.55

Didelphis virginiana opossum 9 0.62 2 9.09

Homo sapiens Man 6 0.41 12 22.73

Bassariscus astutus Ringtails 5 0.34 3 13.64

Nasua narica coati 5 0.34 17 18.18

Herpailurus yagouaroundi jaguarundi 3 0.21 25 4.55

Spilogale angustifrons Southern skunk 2 0.14 5 4.55

6Revista de Biología Tropical, ISSN: 2215-2075 Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

contrast, the white-tailed deer shows very dif-

ferent behaviors related to the elevation. Due

to these changes in white-tailed deer activity,

activity overlap was less when MBSL was low

and increased when elevation was higher, at

1 650 m (Dhat1 1 600 = 0.18 vs. Dhat1 1 750 =

0.29, EE 0.03; α 0.05; t =2.08).

Stepwise Discriminant Analysis revealed

that basal cover (amount of plant material

covering the ground) was one of the essen-

tial components of the variance; this analysis

showed that it modifies (P < 0.02; Table 2) the

overlap of activity patterns of white-tailed deer

and coyote.

Fig. 3A shows that the activity pattern

when the deer is around 1 600 masl has differ-

ent peaks of activity approximately every six

hours, while at a higher altitude (1 750 masl;

Fig. 3B), it shows a higher diurnal activity (6:00

to 12:00). These activity patterns are entirely

contrasting and only match about 25 %.

Fig. 4A and Fig. 4B show that both coyote

and white-tailed deer tend to modify their

activity depending on elevation; however, they

Fig. 2. Activity schedule of Odocoileus virginianus in WMU Santa Cruz Nuevo, Totoltepec de Guerrero, Puebla.

Table 2

Stepwise Discriminant Analysis between the habitat variables and activity overlap.

Overlap: White-tailed deer:coyote (Dhat1)

Variable F Ratio P value Test Value Exact F Prob > F

Altitude 207.098 0.00001 Wilks’ Lambda 0.046 111.53 0.0001*

Escape Cover 1.180 0.302 Pillai’s Trace 0.953 111.53 0.0001*

Basal Cover 6.958 0.023 Hotelling-Lawley 20.279 111.53 0.0001*

Roy’s Max Root 20.279 111.53 0.0001*

Overlap: White-tailed deer:gray fox (Dhat1)

Variable F Ratio P value Test Value Exact F Prob > F

Altitude 35.303 0.0003 Wilks’ Lambda 0.184 35.303 0.0003*

Escape Cover 0.420 0.537 Pillai’s Trace 0.815 35.303 0.0003*

Basal Cover 0.604 0.462 Hotelling-Lawley 4.412 35.303 0.0003*

Roy’s Max Root 4.412 35.303 0.0003*

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

always maintain a shallow level of overlap.

When confidence intervals were estimated

using the bootstrap function, they were 0.1016

to 0.3837 for activity overlap of these species at

1 600 masl and -0.00274 to 0.11380 when found

at more than 1 750 masl.

DISCUSSION

Estimation of the RAI of deer and preda-

tors: It is important to note that the RAI is

modified mainly by the number of captures in

such a way where if there are many sightings in

a relatively low number of camera traps, it will

result in a high RAI (Mandujano & Morteo-

Montiel, 2018), which is what happens in the

particular case of the white-tailed deer.

Among the potential predators that inter-

act with the white-tailed deer, based on the

body size of the prey, the coyote (Canis latrans;

3.32 % RAI), the bobcat (Lynx rufus; 2.52 %

RAI), and the cougar (Puma concolor; 0.14 %

RAI) are expected. The abundance of Urocyon

cinereoargenteus (gray fox) in the habitat is the

highest of the carnivores (24.71 %); although

this predator probably does not attack adult

deer, the young white-tailed deer could be

targets of their predation. In contrast to the

work of, Cruz-Jácome et al. (2015) where nei-

ther the presence of cattle nor people were

reported and they only mentioned the puma,

in this work, the effect of changes in habitat use

was manifested in the presence of cattle, dogs,

and people. This is relatively expected because

generally in the diversified livestock system,

cattle are expected to contribute a part of the

economic income (Villarreal Espino-Barros et

al., 2008). The greater abundance of the gray

fox can be explained by the high number of

rodents and rabbits in the area and by the

habitat preferences of this species. Gallina et al.

(2016) reported that this species prefers habitats

with a low density of people and that dirt roads

positively improve the presence of this species

because they can consume poultry and waste;

additionally, the data suggest that the puma

stayed away from the core of the population.

Overlap of deer and predator activity

schedules: As previously mentioned, the gray

fox converged in 48.2 % of the sites with the

coyote and in 24 % of the sites with the white-

tailed deer; it is important to point out that

in all the places where the gray fox and the

Fig. 3. A. Activity overlap (Dhat1) between the deer and the coyote at 1 600 MASL. B. Activity overlap (Dhat1) between the

deer and the coyote at 1 750 masl.

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white-tailed deer converged, either the coyote

or the bobcat was always present. The coexis-

tence of these three species has already been

reported and is considered normal because

the fox is omnivorous, so there is no direct

competition between them and other predators

(Veals et al., 2021). As previously mentioned,

this carnivore was the most abundant in the

area. However, many studies show a negative

interaction between the coyote and this species

and that the presence of the coyote reduces its

abundance (Egan et al., 2021). The coexistence

Fig. 4. A. Activity overlap (Dhat1) between the deer and the gray fox at 1 600 MASL. B. Activity overlap (Dhat1) between the

deer and the gray fox at 1 750 MASL.

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between the three species can be explained

based on the presence of trees in the sampling

areas, which the fox can use due to its ability to

climb trees to seek refuge from potential preda-

tors (Deuel et al., 2017). The results of this work

show a greater abundance of foxes than coyotes

in a ratio of 1.6:1.

The analysis of variance showed that the

activity overlap between fox and deer (Dhat1;

0.2979, EE 0.037) is higher than that between

deer and coyote (Dhat1; 0.1869 EE 0.034; α <

0.05). Fig. 2 shows the activity overlaps between

the white-tailed deer and the gray fox; it can

be observed that the behavior of the gray fox

is very similar at both altitude levels, while the

white-tailed deer shows very different behav-

iors. Of these changes in white-tailed deer

activity, activity overlap was less when MASL

was low and increased when MASL was higher,

at 1 750 m (Dhat1 1600 = 0.18 vs. Dhat1 1750

= 0.29, EE 0.03; α 0.05; t = 2.08). It is essential

to point out that the gray fox is considered a

generalist species with very marked prefer-

ences in its diet, so it is assumed that, at least

in the Northern part of the country, it does

not consume any species of the Artiodactyl

category; therefore, it does not consume deer

(Rodríguez-Luna et al., 2021). The fact that

deer do not form part of the fox’s diet could

explain the increased daytime activity of both

species, when both are dedicated to foraging.

The activity overlap between deer and coyote

in this work is much lower than that reported

by Higdon et al. (2019); they showed an over-

lap from 0.68 to 0.72 depending on the size

or gender of the animal. The reduction in

activity overlap between coyotes and deer can

be explained by how the prey can minimize

predation risk through behavioral changes that

reduce the probability that the predator will

find it (Smith et al., 2019).

Spatially, prey species can alter habitat

use and minimize exposure to predation risk.

However, the reports on changes in deer behav-

ior in the presence of predators are variable:

some authors have reported that deer change

the spatial use of their habitat when the coy-

ote spread their hair (Seamans et al., 2002) or

bobcat urine repeatedly (Swihart et al., 1991).

In contrast, more recent work has shown that

the presence of predators such as wolves may

not have a significant impact on deer behavior,

since deer may mistake them for domestic dogs

(van Ginkel et al., 2019). White-tailed deer

and coyote have a confluence in 20.6 % of the

sites, which suggests that deer avoid the same

sites as coyotes, or they modify their hours of

activity in such a way as to reduce the chances

of capture further. The bobcat coincided with

the deer in 10 % of the cameras; however, due

to the low number of observations in them, it

was not possible to estimate the activity overlap

between this species and the white-tailed deer.

Apparently, the white-tailed deer avoids this

species more than the coyote, which can be

explained by how although the bobcat is con-

sidered a general carnivore, recently published

studies show that, at least in the Northern

hemisphere, deer and opossum are two essen-

tial components of its diet (Landry et al., 2022).

Stepwise discriminant analysis revealed

that basal cover was one of the most critical

components of the variance; pairwise correla-

tion showed that it modifies (P < 0.02; Table 2)

the overlap of activity patterns of white-tailed

deer and coyotes. This result is different from

Henderson et al. (2020), who showed that the

deer select their hiding areas based on the

height and thickness of the vegetation. How-

ever, in their case, the basal cover modified

the preference of the deer in those areas. The

explanation for the negative correlation can be

found in the field of deer herbivory; it has been

reported that one of the effects of deer browsing

is the reduction of both basal cover and plant

richness (Royo et al., 2017). According to these

authors, a more significant presence of deer

would reduce plant cover.

The altitude modify the Dhat1 of the deer

with the coyote (P < 0.00001); this effect is

reflected in Fig. 3, which shows that the pattern

of activity when the deer is around 1 600 m,

they have different peaks of activity approxi-

mately every six hours, while at a higher alti-

tude (1 750 MASL), they show more significant

daytime activity (6:00 a.m. to 12:00 p.m.) so

10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 72: e55515, enero-diciembre 2024 (Publicado Abr. 09, 2024)

that these activity patterns are entirely contrast-

ing and only coincide in approximately 25 %.

Fig. 4 shows that both coyote and white-

tailed deer modify their activity depending on

altitude; however, they always maintain a shal-

low level of overlap. When confidence intervals

were estimated using the bootstrap function,

they were 0.1016 to 0.3837 for activity overlap

of these species at 1 600 MASL and -0.00274 to

0.11380 when found at more than 1 750 MASL.

In contrast, the works published by Dellinger

et al. (2019) and Hinton et al. (2022) show

that this variable modifies the use of white-

tailed deer habitat due to the mechanisms they

develop to escape from predators (maximum

speed races); they consequently prefer areas

with lower MASL. In this work, the effect of

altitude was only manifested as an inverse

trend, suggesting that the coyote is more abun-

dant in areas with lower altitudes because it is

in that area where the primary water sources

are located. Works published long ago showed

that the coyote stayed close to water sources

and kept the deer away from them (Villarreal-

Espino-Barros et al., 2012).

The activity overlaps between the white-

tailed deer and the fox are greater than that of

the white-tailed deer and the coyote. In this

region, the activity overlap between the deer

and the coyote is much less than that reported

in other parts of the world. This variable is

modified by basal cover but not by escape cover

or altitude. However, the activity patterns of O.

virginianus are modified by MASL.

Ethical statement: the authors declare that

they all agree with this publication and made

significant contributions; that there is no con-

flict of interest of any kind; and that we fol-

lowed all pertinent ethical and legal procedures

and requirements. All financial sources are fully

and clearly stated in the acknowledgments sec-

tion. A signed document has been filed in the

journal archives.

This study complied with all the per-

mits required by the ethics committee of the

Universidad Autónoma Metropolitana and

the Secretary of the Environment and Natural

Resources of Mexico.

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