Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

Conservation priority sites for reptiles in the Sierra Madre del Sur

with a perspective for the future

Diana L. Fuentes-de la Rosa1; https://orcid.org/0000-0002-9224-8753

Daniel G. Ramírez-Arce1,2, https://orcid.org/0000-0002-3076-4373

Leticia M. Ochoa-Ochoa1*; https://orcid.org/0000-0002-9846-4596

1. Museo de Zoología “Alfonso L. Herrera”, Facultad de Ciencias, Universidad Nacional Autónoma de México, 04510,

Ciudad de México, México; leticia.ochoa@ciencias.unam.mx (*Correspondence), dianafr@ciencias.unam.mx

2. Posgrado en Ciencias Biológicas, Instituto de Geología, Universidad Nacional Autónoma de México, 04510, Ciudad de

México, México; daniel.ramiz10@gmail.com

Received 16-V-2024. Corrected 27-II-2025. Accepted 03-VII-2025.

ABSTRACT

Introduction: Reptiles are often overlooked when planning for conservation, as they are typically perceived as a

persistent or tolerant group. Nonetheless, recent studies have shown their vulnerability. Identifying priority areas

is crucial, and spatial prioritization is an essential analysis to optimize the scarce available resources for conserva-

tion. Furthermore, it is of the utmost importance to establish protected area networks that would keep their use-

fulness in the future, especially considering the enormous environmental changes that are currently occurring.

Objectives: To evaluate the performance of the current protected area network (PA) and to identify potential

areas for expansion, considering their persistence in time.

Methods: We estimated species distributions for 177 reptiles on the Sierra Madre del Sur in Southeastern Mexico.

The species were weighed according to their international conservation status, and future land use scenarios were

incorporated to identify priority areas with Zonation software.

Results: We found coincidences between priority areas for reptiles and zones previously identified for other

groups. However, most regions with top priority rankings remain unprotected, considering the current estab-

lished PA. Federal PA protects the highest percentage of priority areas, followed by areas voluntarily dedicated to

conservation and state PA. We emphasize conserving natural land uses since they are the only ones that constitute

the highest priority zones for reptiles.

Conclusions: Our prioritization for reptile conservation entails efficient outcomes in terms of temporal per-

manence, amount of area to be protected, and coverage of species distribution, especially for small percentages

of expansions to the current network of PA, making it an affordable proposal for implementation. Nonetheless,

it is crucial to recognize that it is also important to consider social factors, possible conflicts of interest, and to

evaluate the effectiveness of PA over time.

Key words: land use, Mexico, protected areas, spatial conservation, species distribution models, Zonation.

RESUMEN

Prioridad de sitios de conservación para reptiles en Sierra Madre del Sur

con una perspectiva hacia el futuro

Introducción: Los reptiles suelen ser olvidados cuando se planifica la conservación, ya que son considerados

un grupo persistente o tolerante. Sin embargo, estudios recientes han demostrado su vulnerabilidad. Identificar

https://doi.org/10.15517/rev.biol.trop..v73i1.60000

CONSERVATION

2Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

INTRODUCTION

Reptiles are usually forgotten when plan-

ning for conservation as they are normally

seen as a persistent or tolerant group (Vitt &

Caldwell, 2014). Nonetheless, recent studies

have shown their vulnerability not only to

climate change (Sinervo et al., 2010) but also

to land use change (Cox et al., 2022). Reptiles

are considered to be the second most abundant

vertebrate group in tropical environments after

amphibians (de Miranda, 2017). Therefore,

given their ecological importance in the eco-

systems (e.g., nutrient cycling, seed dispersal,

energy flow; Cortés-Gomez et al., 2015), it is

of crucial importance to conserve them (de

Miranda, 2017).

Mexico is the second country with the

highest reptile species richness in the world

after Australia, with 1 073 species, and has high

levels of reptile endemism, since above 50 % of

the species are endemic (558 species; Suazo-

Ortuño et al., 2023). Curiously it also has been

shown, that are least for Mexico, reptile species

have smaller distribution ranges than amphib-

ians (Koleff et al., 2008) and that mountains

harbor the highest reptile richness in the coun-

try (Ochoa-Ochoa et al., 2014). The latter is not

a new concept since, for a long time, mountain-

ous regions have been considered as reservoirs

for biodiversity not only for reptiles but in

general for all terrestrial organisms, probably

due to their topographic and environmental

heterogeneity (Perrigo et al., 2020; Rahbek et

al., 2019). The Sierra Madre del Sur (SMS) is a

complex mountainous region in the Southeast

portion of the country, and it is expected to

have up to 280 species of reptiles, with approxi-

mately 211 being endemic to Mexico (Flores-

Villela & Ochoa-Ochoa, 2016; Johnson et al.,

2017; García-Padilla et al., 2020; Ríos-Solís et

al., 2022; Ramírez-Arce et al., under review;

see SMT1 and SMT2). This region, neverthe-

less, has been affected by land use change and

it is expected to have large deforestation rates

in the near future, with reptiles being highly

vulnerable to these changes (Mendoza-Ponce

et al., 2020).

In terms of species diversity, geographical-

temporal knowledge of the species is still scarce

(Hortal et al., 2015), and in the SMS the knowl-

edge is particularly scarce as can be seen in the

áreas prioritarias es crucial, y la priorización espacial es un análisis esencial para optimizar los escasos recursos

disponibles para la conservación. Además, es de suma importancia establecer redes de áreas protegidas que man-

tengan su funcionalidad en el futuro, especialmente considerando los enormes cambios ambientales que se están

presentando en la actualidad.

Objetivos: Evaluar el desempeño de la red actual de áreas protegidas (AP) e identificar áreas potenciales de

expansión contemplando su persistencia en el tiempo.

Métodos: Estimamos la distribución de 177 especies de reptiles en la Sierra Madre del Sur, en el sur de México.

Las especies fueron ponderadas según su estado de conservación nacional e internacional, y se incorporaron

escenarios futuros de uso del suelo para identificar áreas prioritarias con el software Zonation.

Resultados: Encontramos coincidencias entre áreas prioritarias para reptiles y zonas previamente identificadas

para otros grupos. Sin embargo, la mayoría de las regiones con clasificación de máxima prioridad siguen despro-

tegidas considerando las AP actualmente establecidas. Las AP federales protegen el mayor porcentaje de áreas

prioritarias, seguidas por las áreas dedicadas voluntariamente a la conservación y las AP estatales. Hacemos énfa-

sis en conservar los usos naturales del suelo ya que son los únicos que constituyen las zonas de mayor prioridad

para los reptiles.

Conclusiones: Nuestra priorización para la conservación de reptiles implica resultados eficientes en términos de

permanencia temporal, cantidad de área a proteger y cobertura de distribución de especies, especialmente para

pequeños porcentajes de expansiones de la red actual de AP, lo que la convierte en una propuesta asequible para su

implementación. Es crucial reconocer que también es importante considerar factores sociales, posibles conflictos

de intereses y evaluar la efectividad de las AP a lo largo del tiempo.

Palabras clave: uso del suelo, México, áreas protegidas, conservación espacial, modelos de distribución de espe-

cies, Zonation.

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locality records that exist for the zone and the

few studies listing species list or inventories

in the region (SMT1 and SMT2). Therefore, a

large part of the SMS area does not have any

biological records, or it is under-sampled (i.e.,

has very few, and in general, opportunistic

records). For this reason, the estimation of

distribution areas is a fundamental resource to

fill existing information gaps particularly when

developing conservation plans (see for example

Camarena-Hérnandez et al., 2023). Therefore,

species distribution modeling (SDM) has been

widely used to account for the lack of sam-

pling in order to estimate species distribu-

tion, since its beginnings in the mid-1980s

(Peterson et al., 2011).

The modeling process has been accompa-

nied by the development of ecological niche

theory and methodological strategies (Peterson

& Soberón, 2012; Soberón et al., 2017) to try

to reproduce the complex interactions (e.g.,

biological, historical) that actually shape the

species distribution areas. Several algorithms

have been developed trying to reproduce those

interactions (Elith & Graham, 2009; Elith &

Leathwick, 2009). In this sense, the SDM gen-

eration process consists of the association of

ecological variables to the records of the spe-

cies and their projection in geographical space

to recognize where the conditions are suitable

for them (Ochoa-Ochoa & Ríos-Muñoz, 2019;

Ríos-Muñoz & Espinosa-Martínez, 2019). It

is important to stress that there is no consen-

sus, to our knowledge, of which is the best

algorithm or the best procedure to generate an

SDM. However, to explore potential areas for

conservation it is essential to fill those distri-

butional gaps.

In the year 2000, the National Commission

of Protected Natural Areas (Comisión Nacional

de Áreas Naturales Protegidas, CONANP) was

created, as an institution aimed at consolidating

protected areas (PA) (Comisión Nacional de

Áreas Naturales Protegidas, [CONANP], 2018).

In Mexico, as in many other countries, there are

different categories of PA, governmental and

private PA. The first ones include Federal, State,

and Municipal PA whose characteristic is that

they are established by the government (hence

their name) and, in general, there is a hierar-

chy not only in terms of area but also in terms

of assigned resources, with the federal ones

being the largest and with the most resources.

The private areas are named Areas Voluntarily

Designated for Conservation (AVDC), in this

case any landowner can declare and register

her or his land to be under protection, however,

these areas do not receive government funds.

It is worth emphasizing that all the PAs are

acknowledged by CONANP.

The establishment of the Aichi 2011-2020

goals of the Convention on Biological Diversity

(Convention on Biological Diversity, [CBD],

2010; CBD, 2021) highlighted PA as a funda-

mental mechanism in conservation (CONANP,

2018). Although, in recent years, a significant

number of PA have still been decreed, the para-

digms that underlie their application and man-

agement face new socioeconomic contexts. The

SMS is no exception and despite the enormous

biological diversity and endemic species it has,

there are few established PA, with only eight

(CONANP, 2024) with a coverage percentage of

less than 10 %, although it is also important to

highlight that there has recently been decreed

another large PA, Sierra de Tecuani. Neverthe-

less, not only is it essential to establish new

protected areas to conserve biodiversity in the

long term but also to assess the value, as tools

for conservation, of the current PA, particularly

when facing enormous environmental changes

that are currently occurring and will continue

to occur in the near future (IPCC., 2023).

Spatial prioritization for species diversity

conservation is the most important objective

within systematic conservation planning (SCP),

because the allocation of resources must be

truly efficient (Margules & Pressey, 2000). SCP

can also assist in locating other land uses, based

on computational tools, but the key aspect is

that such prioritization must be ecologically

informed (Pressey et al., 2007). SPC methods

have evolved to organize various cost factors

and increase ecological reality by implementing

methods to address species-specific connectiv-

ity and uncertainty, and also by implementing

4Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

more complex computer programs that can

address larger landscapes and a wide variety of

data types (Kukkala & Moilanen, 2013), as well

as the possibility of including the permanence

over time of selected areas given a projection of

change, whether climatic or coupled with land

use changes (Moilanen et al., 2022).

In this work we set out to find the most

priority sites for reptile conservation within

the SMS taking into account the current estab-

lished network of protected areas and establish-

ing a network of priority conservation sites

using different threat layers as costs, therefore

penalizing areas with many threats, and tak-

ing also into account land use change models

to project possible scenarios into the future

with different socioeconomic pathways trajec-

tories. Finally, we evaluated the coincidence

of the priority sites with the protected areas

in Mexico by performing a gap analysis. Since

priority analysis is based on species richness

and rarity, we hypothesize that priority sites

will occur in the areas with the highest reptile

species occurrence.

MATERIAL AND METHODS

Estimation of species distribution areas

and conservation status. A list of reptile spe-

cies was compiled through a bibliographic data-

base search (SMT1 and SMT2). All species

names were taxonomically refined to avoid

counting twice the same species that have been

classified in different ways in the literature

consulted and in biological collections. This

depuration consisted of updating the taxonomy

of each species according to the criteria of Uetz

et al. (2024). Additionally, we classified species

according to their IUCN conservation category

(IUCN, 2023) as follows: Critically Endangered

(CR), Endangered (EN), Vulnerable (VU), Near

Threatened (NT), Least concern (LC), Data

Deficient (DD), and Not Evaluated (NE); and

by its conservation category according to the

Norma Oficial Mexicana NOM-059-SEMAR-

NAT-2010 (SMT1).

Maxent algorithm (Phillips et al., 2006)

was used to generate the SDM, and only those

species with at least 10 presence data were taken

into account in the models (Guisan et al., 2017).

The data was divided into training data (70 %)

and internal validation data (30 %) (Beck et

al., 2014). The kuenm R package (Cobos et al.,

2019) was used, which generates several candi-

date models using all the possible parameter-

izations from different sets of environmental

variables, different regularization multipliers,

and different combinations of features such

as linear, quadratic, and product, among oth-

ers. We used the 19 bioclimatic variables from

CHELSA (Karger et al., 2017) between the

period of 1979 and 2013 at a resolution of ~1

km 2 as predictor variables, and from these,

three data sets were used: 1) variables chosen

from correlation analysis, 2) variables chosen

from VIF analysis, and 3) variables presenting

a cumulative importance value of 95 % from an

initial model run with default settings in Max-

ent using all 19 bioclimatic variables (Sillero et

al., 2021; Simões et al., 2020). Eight regulariza-

tion values: 0.1, 0.4, 0.7, 1, 2, 3, 4, 5; and five

combinations of features were used, using only

linear, quadratic and hinge, because most spe-

cies had less than 80 presence data (Elith et al.,

2011; González-Fernández et al., 2018; Merow

et al., 2013): linear, quadratic, hinge, linear

x quadratic, and linear x quadratic x hinge.

This generated a total of 120 candidate models

per species. The choice of the best model was

made using the following criteria: 1) significant

models (using partial ROC) with omission rates

≤ 5 %, and 2) models with ΔAICc values ≤ 2

(Cobos et al., 2019). The best models for some

species were significant, but with an omission

rate > 5 %, therefore best models used were

those with the lower omission rate and ΔAICc

≤ 2, acknowledging that the latter metric is not

the most reliable (Velasco & González-

Salazar, 2019).

The final models were built with the

parameterization of the best model, using

logistic output for better interpretation. From

the suitability maps obtained with the final

models, binary presence/absence maps were

obtained to use them in subsequent analyses.

For this, a convergence threshold of 10-5 and

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

500 iterations for each species was used (Phil-

lips et al., 2006), and the ‘Maximum training

sensitivity plus specificity’ was used as a con-

vergence rule since it is a convergence threshold

suitable when only presence data is available

(Liu et al., 2013, Liu et al., 2016). All models

were generated in R 3.5.0 (R Core Team, 2018).

Spatial prioritization. To select priority

conservation areas, the Zonation 5 software

was used as the most updated version of the

software (Moilanen et al., 2022). This software

produces a balanced and complementary cate-

gorization of areas, maximizing the occurrence

of species and considering different “penalty”

variables (Di Minin & Moilanen, 2014). Zona-

tion 5 produces a hierarchical prioritization

of the landscape, as it iteratively classifies and

eliminates cells according to the presence of

species, connectivity, and complementarity of

areas (Moilanen et al., 2022). The prioritization

was made considering the entire SMS area to

evaluate the performance of PAs in protect-

ing reptiles. The marginal loss rule, Core Area

Zonation 2 (CAZ2), was used, which empha-

sizes the high average cover of species, tending

to improve the cover of species with the worst

performance (Moilanen et al., 2022).

For prioritization analyses, 177 reptile spe-

cies, and a 2016 land use cover layer (1:250

000) (INEGI, 2016), were included. To ensure

the persistence over time of the priority areas,

we also incorporated three models of land use

change projected for 2060: “Business As Usual”

(BAU), the green, and the worst-case scenario.

The BAU scenario uses Shared Socioeconom-

ic Pathway 2 (SSP2) assumptions defined as

‘middle of the road’, in which social, economic,

and technological trends do not change mark-

edly from historical patterns, and climate data

from gas concentration path 4.5 (RCP4.5); the

green scenario considers a sustainable path

and uses socioeconomic data from SSP1 and

climate variables RCP4.5 and RCP2.6. Finally,

the worst scenario, considering the highest his-

torical deforestation rates, as well as consum-

erist and unequal social trends, combines the

data from SSP3 and RCP8.5 (Mendoza-Ponce

et al., 2018). Land use layers were reclassified

into two classes, natural and anthropogenic.

Anthropogenic land use layers were negatively

weighed to remove those cells first in the pri-

oritization process while allowing those sites to

still be considered during the planning process.

We simultaneously use the current land use

layer and the three future scenarios to obtain a

conservative priority area estimation. In other

words, we wanted to ensure that in any given

scenario of land use change or socioeconomic

pathway, the selected priority areas were sup-

posed to persist, therefore if a site is selected in

the prioritization, it is due that in any scenario

(BAU, green or worse) said area will remain

with a natural land use, ensuring reptile diver-

sity conservation in the long-term.

Species layers were weighted according to

their IUCN category (IUCN, 2023) as follows:

CR, 5; EN, 4; VU, 3; NT, 2; LC, 0; DD, 1; and

NE, 1. We used only the IUCN categoriza-

tion as most species were not included in the

Norma Official Mexicana NOM-059-SEMAR-

NAT-2010 (SMT1). Weight values were assigned

so that the sum of the negative and positive

weights equals zero, allowing a balanced solu-

tion for prioritization (Moilanen et al., 2011;

Ramírez-Albores et al., 2016). A priority map

and performance curves were made (Fig. 1 and

Fig. 2, respectively), to explore the results.

Protected areas network evaluation. For

the evaluation of the PAs, we estimated the

proportion of the highest priority areas that are

under current protection (Table 1). We also cal-

culated the prevalence of land use types present

in the highest priority areas accounting for

different scenarios (Table 2). This was done to

identify important land uses for the conserva-

tion of reptiles within the SMS. We considered

17 % of Aichi goal 11 (CBD, 2010) given that

within the SMS, several PAs are still far from

that goal. We also considered 30 % to reduce

threats to biodiversity by 2030 (CBD, 2021)

because these targets must be seen to increase

areas towards a higher long-term global target

(Larsen et al., 2015), and because Mexico is a

signatory country of those agreements.

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Fig. 1. Priority rank map for reptile conservation. The map is the result of one Zonation run with CAZ2 as a marginal loss

rule considering the entire area of the SMS. The current PA have red borders to visualize their coincidence with the most

important priority areas for reptiles.

Fig. 2. Zonation performance curves illustrate the relationship between the loss of priority rank areas across the landscape

(x-axis) and the corresponding decrease in species distribution coverage (y-axis).

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

The first four correspond to natural land

use types and the last three to anthropized

environments.

RESULTS

Estimation of species distribution areas

and conservation status. We generated binary

maps of 177 species from two orders: four Tes-

tudines and 173 Squamata. Regarding the risk

status of the species, according to the IUCN,

21 species are classified as Threatened (VU = 6,

EN = 3, CR = 12), only two as Near Threatened

(NT), 148 as Least Concern (LC) and 5 as Data

Deficient (DD).

Spatial prioritization. The priority rank

map (Fig. 1) displays the following top prior-

ity areas: 30, 17, 10, 5, and 2. The latter were

selected through CAZ2 as a marginal loss rule,

allowing for the identification of areas that bet-

ter account for reptile conservation, emphasiz-

ing high average coverage of all species even

with the worst-off ones (Moilanen et al., 2022).

The top priority areas are in or near the follow-

ing mountain chains: Sierra de Ixtlán, Sierra de

Tlaxiaco, Sierra de Coalcomán, and Sierra de

Valadez. The Northeast, Southeast (Oaxaca),

and a small fraction of the Southwest (Jalisco)

of the SMS also stand out. Interestingly, most of

Table 1

Protected Area network evaluation. Percentages of areas under protection are shown for each priority range.

Top Priority

(%)

Total area

(km2)

Area

inside

FPAs (km2)

Area

inside

SPAs (km2)

Area

inside

AVDCs

(km2)

Area under

protection

(km2)

Percentage

inside

FPAs (%)

Percentage

inside

SPAs (%)

Percentage

inside

AVDCs (%)

Total

percentage

under

protection (%)

2 875 87.6 2.4 52.2 142.2 10 0.3 5.9 16.2

52 204.1 281.2 3.2 149.4 433.9 12.7 0.1 6.7 19.6

10 4 466.1 503.8 8.8 216.1 728.8 11.2 0.2 4.8 16.3

17 7 741.4 757.7 15.2 226.6 999.6 9.7 0.2 2.9 12.9

30 1 4214.8 1225.4 17.6 331.06 1574.1 8.6 0.1 2.3 11.07

50 25 489.5 2217.8 23.3 646.05 2887.1 8.7 0.09 2.5 11.3

80 48 106.4 4084.4 54.6 940.9 5080 8.4 0.1 1.9 10.5

100 87 024.1 6490.3 106.06 1 436.7 8 033.1 7.4 0.1 1.6 9.2

A distinction is made between Federal Protected Areas (FPAs), State Protected Areas (SPAs) and Areas Voluntarily

Designated for Conservation (AVDC).

Table 2

Land use in top priority areas. Percentages by vegetation types are shown for each priority range.

Land use Top 30 %

percentage

Top 17 %

percentage

Top 10 %

percentage

Top 5 %

percentage

Top 2 %

percentage

Temperate forest 52.3 51.5 57 59.2 36.3

Cloud forest 12.8 0 0 0 0

Tropical Dry Forest 26 33.6 29.8 40.7 63.6

Other natural vegetation 0.5 0.2 0 0 0

Pasture 4.2 7.2 7.5 0 0

Seasonal Agriculture 3.9 7.2 5.7 0 0

Irrigated Agriculture 0.08 0.2 0 0 0

Land use classification follows Mendoza-Ponce et al. (2018).

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the top priority areas are found near the limits

of the SMS.

Performance curves summarize the con-

servation coverage achieved in each top priority

fraction (Fig. 2) from the priority rank maps.

Specifically, mean performance curves allow

an overall evaluation of prioritization, while

order-level curves enable the detection of the

detailed prioritization behavior by retaining

taxonomic resolution. When considering aver-

age performance, the top 30 areas cover 58

% of the average reptile species distribution.

Protecting the top 17 areas covers over 40 %,

while the top 10 covers more than 29 %, and

the top 5 covers more than 17 %. Notably, the

top 2 areas are the most efficient, covering 8

% of the species distribution with the small-

est area to be protected. If we focus on reptile

orders separately, it is possible to observe that

overall performance curves were slightly better

for turtles. For example, if we consider the top

5 in terms of protection, for testudines, 23 % of

species distribution would be covered, while for

lizards, it would be only 15 %.

Finally, at the species level, Salvadora lem-

niscata demonstrated the best performance

curve in prioritization, requiring the least

amount of protected landscape area to cover

its distribution. Conversely, Aspidocels com-

munis showed the poorest performance, requir-

ing most areas to be protected to cover its

distribution.

Protected areas network evaluation.

Comparing the prioritization areas and the

current PA network (Table 1) revealed that

less than 10 % of the total area of the SMS is

currently protected. Surprisingly the current

PA network protects only 11 % of the top

30 % priority areas, the equivalent of 1 574

km2 out of the entire 87 024.1 km2. In contrast,

if we consider increasingly less inclusive top

areas, we can see that the protection percentage

increases. For example, in the top 17, almost

13 % of the area is protected, for the top 10,

more than 16 % is protected, and for the top 5,

almost 20 % is protected. On the other hand,

this trend is not maintained for the top 2, where

16.2 % of the area is protected. Generally, we

can see that the percentages of PA across the

different areas top are low, with the top 5 being

the best protected in proportion. This indicates

a mismatch between the current PA network

and the priority areas for reptiles in the SMS,

leaving many areas unprotected, which may

lead to negative consequences for the conserva-

tion of this group.

If we take into account the efficiency of

each type of protected area, it can be observed

that their contribution varies for each priority

range of areas, with federal PA protecting the

greatest amount of area, followed by AVDC,

and lastly by state PA. For example, for the top

5 priority sites, the federal PA keeps 12.7 %, the

state PA only 0.1 %, and the AVDC 6.7 %. Fed-

eral PAs contribute the most to the protection

of reptiles, which implies that the organisms are

under the application of the PA management

plans and the administration of CONANP. On

the other hand, we highlight the importance of

the AVDCs in the protection of reptiles, since

it indicates that the people will have a greater

impact on the protection of these areas than

that of the state PA.

From quantifying the proportion of land

use into each priority top area, we can observe

that most of the priority areas are occupied by

natural use types (Table 2). Across almost all

priority thresholds (top 17 to top 2), temper-

ate forests stand out as the most prevalent land

use, accounting for more than 50 % of coverage,

followed by tropical dry forests ranging from

29.8 to 63.6 % and pasture and seasonal agri-

culture covering < 10 %. If we focus on the top

30, we can see that the cloud forest emerges as

the third most important land use. In general,

zones with natural land uses are more prevalent

in priority areas, with the lone exception of

pasture and seasonal agriculture but, as men-

tioned before, with a very low percentage. We

highlight that the top 5 and 2 have only natural

land uses, temperate and tropical dry forests.

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DISCUSSION

Estimation of species distribution areas

and conservation status. Our findings show

that a large proportion of the reptile species in

the SMS are classified as Least Concern, prob-

ably maintaining the idea that reptile species

are indeed tolerant to environmental changes;

however, as mentioned before, this idea is

changing particularly when a view to global

warming is taken into account (e.g., Sinervo et

al., 2010) since the environmental temperature

can affect sex-ratio in reptile populations. For

example, Sinervo et al. (2024) using ecophysio-

logical models showed that a high proportion of

the studied species could be at risk under global

warming scenarios but that extinctions may be

attenuated in forested sites and by the presence

of montane environments in contemporary

ranges. Although a study with a wide-range

desert lizard Dipsosaurus dorsalis, using also

ecophysiological models, showed that this liz-

ard, and probably others, are resilient to global

warming (Lara-Resendiz et al., 2019). Another

aspect that is crucial to take into account is the

habitat preferences of reptile species since it is

evident when sampling conserved versus modi-

fied sites that most reptiles are not generalists

(Doherty et al., 2020; Gardner et al., 2007).

Therefore, it is important to not generalize on

one side or another but also to reconsider all

threats within the conservation assessments

(Arroyo-Rodríguez et al., 2020; Cordier et al.,

2021; Cox et al., 2022). In this sense, many

species may be misclassified as Least Concern

according to the IUCN, when they may be in a

higher category of risk.

Spatial prioritization. It is not surprising

to observe that priority sites (Fig. 1) mostly

coincide with the areas of greatest reptile rich-

ness (Fig. 3), since the algorithm that selects

priority sites is based on species number and

spatial rarity of those species (Lehtomäki &

Moilanen, 2013), thus our hypothesis is par-

tially fulfilled. In the easternmost part of the

SMS only the Southern part was included in

the top priority sites, probably to minimize the

area selected. On the other hand, there is not

much congruence between the priority sites for

amphibians (Fuentes-de la Rosa et al., 2024) and

the ones found for reptiles. This makes sense as

both groups may respond differently to climate

or land use change (e.g., Cordier et al., 2021)

and their diversity distribution may be different

along the SMS region (Fuentes-de la Rosa et al.,

2024). The few priority sites among amphib-

ians and reptiles in the SMS include from west

Fig. 3. Reptile richness pattern for Sierra Madre del Sur (SMS) based on Species Distribution Models.

10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

to East: Sierra de Coalcomán in Michoacán;

Sierra de Tecuani in Guerrero; the area around

Putla de Villa in the limits of Guerrero and

Oaxaca; the area between Sierra de Juárez and

Cerro Yatin, North of the city of Oaxaca; the

area around Juquila and Pluma Hidalgo; and

finally, the area around Santa María Ecatepec

and San Lorenzo Jilotepequillo, in the state of

Oaxaca. Curiously, the most recently decreed

PA Sierra de Tecuani does coincide with the top

priority sites found for amphibians (Fuentes-de

la Rosa et al., 2024) but barely for reptiles, only

a small area belonging to the top 30. Sierra de

Juárez has long been considered a special case

due to the vast richness and the huge number

of range-restricted species that inhabit the area

not only for amphibians and reptiles but in sev-

eral groups (e.g., Hernández-Rojas et al., 2018;

Luis-Martínez et al., 2020; Rovito et al., 2012).

The unique priority areas found for reptiles are,

again from West to East: the area around El

Parotal, in Michoacán; the region West Tierra

Colorada and the mountain range between

Ayutla de los Libres and San Luis Acatlán; and

finally, around Tomatepec in Guerrero.

Protected areas network evaluation. Even

including the newly decreed PA Sierra de Tecu-

ani (Diario Oficial de la Federación, 2024),

there are few coincidences between PA and the

priority areas found for reptiles in the SMS.

It has been long known that SMS was not an

area of much interest in conservation plans

or investment due to various factors such as

drug production problems and social conflicts

(including intentional abandonment by pre-

vious governments, both federal and state),

fortunately, this attitude seems to be changing.

The SMS region is still far from achiev-

ing international conservation agendas (17.30

% of the territory). However, a small propor-

tion of extra conserved areas targeted through

prioritization methods can give more efficient

conservation outcomes in terms of resources

and species protection. But the most important

aspect is that it is affordable for implementation.

Federal protected areas have the greatest

contribution to conserving the priority sites

found in the analysis, highlighting the recent

increase in the protected areas belonging to

this category such as the Sierra Tecuani Bio-

sphere Reserve (Diario Oficial de la Federación,

2024). This is not surprising given the size of

the federal PA. However, it is notorious and of

great importance that private areas or ADVC

are in the second place of protected areas. The

importance of these areas has been previously

noted for amphibians (Ochoa-Ochoa et al.,

2009). Nonetheless, this category of PA is tricky

since it can be withdrawn as the owner of the

land wishes.

Conservation of temperate forests and

tropical dry forests is essential to ensure the

long-term maintenance of the SMS reptiles

since most priority areas were occupied by

these land use covers (Table 2). Additionally, a

recent study suggests that both types of forests

may host high reptile taxonomic and functional

diversity in many areas along the SMS, par-

ticularly temperate forests (Ramírez-Arce et al.,

under review). On the other hand, grasslands or

seasonal crops may seem to be important land

uses for some reptiles, as a small percentage of

priority areas were occupied by these (Table

2). This may be true for some generalist spe-

cies that can adapt and take advantage of these

disturbed environments (e.g., Berriozabal-Islas

et al., 2017; Urbina-Cardona et al., 2006). Addi-

tionally, the incorporation of future layers may

allow the possibility of regeneration of these

environments, which could favor the return

and/or permanence of the reptiles. Neverthe-

less, it is important to take into consideration

that SDMs and spatial prioritization were based

solely on climatic variables, therefore, some

priority areas may be climatically suitable areas,

but with land use covers (i.e. perturbed land

uses) that are harsh for most species.

Most reptiles tend to be vulnerable to land

use change (Cordier et al., 2021; Gardner et al.,

2007). For example, several studies at differ-

ent scales of analysis agree that urbanization

and agricultural intensification reduce overall

reptile diversity (e.g., Barnagaud et al., 2020;

García-Llamas et al., 2019; Leavitt & Fitzgerald,

2013) and that the prevalence of large forested

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e60000, enero-diciembre 2025 (Publicado Jul. 31, 2025)

areas is essential for many species, especially

those with specialized habits (e.g., arboreal or

scansorial; Palmeirim et al., 2021). Land use

change also may reduce the number of func-

tional groups, having negative repercussions on

ecosystem processes and services (Newbold et

al., 2020). Although some studies suggest that

reptiles can respond positively to perturbed

land uses, this may be true only for some gen-

eralist species and for perturbed land uses with

greater structural complexity (Mendenhall et

al., 2014) and less contrast with the natural land

use covers (Deans & Chalcraft, 2017). There-

fore, most reptiles are probably not resistant to

environmental change and may be at high risk

of extinction in several areas of the SMS in the

future (for example, Ramírez-Arce et al., under

review). Given the land use transformation rate

occurring within the SMS, reptiles are probably

disappearing faster than their incorporation

into national conservation agendas without

even considering the description of new spe-

cies. Therefore, conservation of remaining

natural land covers along the SMS, such as

temperate and tropical dry forests, is essential.

Spatial prioritization for conservation is

essential to propose new areas to achieve con-

servation objectives, especially those acquired

as a signatory country of international agree-

ments such as the Aichi goals. However, it is

important to consider the limitations of the

spatial prioritization proposed here and to

explore possible new approaches so that it is

ecologically and socially realistic. Particularly,

considering that as shown previously there

seems to be little overlap among prioritiza-

tions with different biological groups, therefore

implementing each prioritization would result

in unachievable, and second, the grain used

here is around one square kilometer, which

is a huge area to begin with. Therefore, if it is

not possible to protect all priority sites, other

kinds of strategies derived from these results

could be of great importance like small-scale

corridors within the top priority sites. Finally,

it is important to recognize this tool as part

of a larger framework within Systematic Con-

servation Planning. That is why proposals for

implementation, monitoring, and evaluation

must also be considered to achieve conserva-

tion objectives.

Ethical statement: The authors declare

that they all agree with this publication and

made significant contributions; that there is no

conflict 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.

See supplementary material

a42v73n1-suppl1

ACKNOWLEDGMENTS

This project was supported by UNAM-

DGAPA-PAPIIT IN220321 to LMOO. DLFR

and DGRA are grateful to CONACyT for the

master’s (CVU-1084896) and doctorate’s (CVU-

1086112) scholarship respectively, and the Pos-

grado de Ciencias Biológicas at the Universidad

Nacional Autónoma de México for providing

permissions and facilities to DLFR and DGRA

to complete the master and doctoral thesis on

which this manuscript is based. DLFR is also

thankful to UNAM-DGAPA-PAPIIT IN220321

for a month scholarship. We thank Brett O. But-

ler for English proofing the manuscript.

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