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Assessing Extinction Risk for Mexican Dry and Cloud Forest Rodents: A Case Study | OMICS International
ISSN: 2332-2543
Journal of Biodiversity & Endangered Species
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Assessing Extinction Risk for Mexican Dry and Cloud Forest Rodents: A Case Study

Rafael S Ramírez* and Esther Quintero

Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Subcoordinación de especies prioritarias, Liga Periférico - Insurgentes Sur, Núm. 4903, Col. Parques del Pedregal, Delegación Tlalpan, 14010, México

*Corresponding Author:
Ramírez RS
Subcoordinacion de especies prioritarias, CONABIO
Liga Periférico - Insurgentes Sur, Núm. 4903, Col.
Parques del Pedregal, Delegación Tlalpan, 14010, México
Tel: +52 55 5000-5004
E-mail: [email protected]

Received date: August 25, 2016; Accepted date: October 17, 2016; Published date: October 24, 2016

Citation: Ramírez RS, Quintero E (2016) Assessing Extinction Risk for Mexican Dry and Cloud Forest Rodents: A Case Study. J Biodivers Endanger Species 4:169. doi: 10.4172/2332-2543.1000169

Copyright: © 2016 Ramírez RS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Red Lists have been traditionally used as instruments to guide conservation strategies to avoid extinctions. However, there is little consensus in the best way to perform assessments and thus, different countries have developed different methods according to their specific needs. In this study we used a set of ten rodents species, half of them from the cloud forest and halve from the dry forest listed as endangered by the IUCN Red List, but not included in the Mexican red list NOM-059-SEMARNAT-2010. We assessed these 10 species using Mexico´s national Risk Assessment Method (MER) guidelines and then compared the outcomes of these assessments with those from the IUCN Red List evaluations. In addition, in order to support our comparison and to verify if both methods deliver equivalent results, we compared 67 endangered mammals which inhabit in Mexico and have been assessed by both methods. We found that both assessment methods yield equivalent results for the five species of cloud forest rodents. However, it was different for those from the dry forest species, where three had different results. Moreover, we found several discrepancies in the assessment results of the 67 endangered mammals assessed by both methods, suggesting that the assessment methods may be not entirely equivalent. We conclude that the MER in its current form might not be entirely objective, and the assessments could be artificially biased. The method could be an even better assessment instrument if the something is done to account for the lack of objectivity and the bias that the lack of information that we face with many endangered species is taken into account. In this way, the MER could clearly define the conservation status of a given species in a simple and transparent, relevant in terms of impact on conservation actions.

Keywords

Species Risk Assessment; MER; IUCN Red List; Mexican rodents; Biodiversity conservation

Introduction

Red Lists have traditionally guided conservation strategies to avoid extinctions. There is little objection to the idea that categorizing species according to their risk of extinction is a good way to prioritize and implement conservation actions; however, there is little consensus in the best way to perform the actual assessments, and different countries have developed different methods according to their specific needs [1] Here, we analyzed a case study of mice distributed along dry and cloud forests in Mexico, the two most endangered ecosystems in the country, using the national Risk Assessment Method (MER) which is mandatory in order to enlist species into the Mexican Red List [2,3], and contrasted the results to the assessments under IUCN´s standards.

In Mexico the cloud forest, a group of communities distributed along the mountains best known for the presence of clouds at vegetation level [4] and with specific floral structure and species composition [5] is the most threatened ecosystem [6-10] currently occupying less than 1% of the country’s territory (8,809 km2), and with the least surface worldwide [5]. At the same time, this ecosystem has the most diverse flora and fauna in relationship to its area in Mexico [6,11]. Besides its ecological importance, this ecosystem is a source of timber [12], medical products [11,13], and commodities such as shade-grown coffee plantations [11]. Moreover, the cloud forest is a priority for conservation and restoration efforts due to its crucial role in sustaining the water and nutrient cycles [4].

On the other hand, the dry or deciduous forest in Mexico used to occupy 14% of Mexico’s territory (271,750 km2); unfortunately its distribution has been reduced with only 27% of the total remaining today [14]. Just like the cloud forest, the dry forest has unique characteristics: it occurs on the slopes and low hills of the mountains in altitudes between 0 and 2000 m above sea level; precipitation is generally lower than 1600 mm per year taking place in summer [14]; most of the vegetation is comprised of short trees and shrubs with closed canopies that tends to lose their leaves during the dry season [15]. Recent studies have shown that the dry forest is home to 35% of Mexico’s mammals with 23% endemic to it [16]. Currently, the extension of the dry forest is decreasing due to anthropogenic pressures, especially due to the extraction of timber-yielding and nontimber- yielding products such as fibres, food, ornamental flowers, essences for cosmetics, and medical products [14]. Furthermore, the change of land use is another threat as the forest is converted to pastures and crop fields [14]. Combined, these threats have led to a change of the composition and structure of the dry forest; generating serious erosion problems and species lost [14].

As a result to anthropogenic pressure, cloud and dry forest have become fragmented, sustaining only isolated vegetation patches that reduce the quality and quantity of habitat for forest-dependent species [5,11,14,17,18]. Stephens et al. [19] demonstrated that even the smallest fragmentation, such as a road or walk path can change the genetic structure of small species’ populations such as those of rodents. Additionally, edge effect, another consequence of habitat loss and fragmentation [17] is common in landscapes next to disturbed areas. Studies such as those from López-Barrera, Newton & Manson suggest that edge effect in montane forests can change the populations of small mammals causing a change in the patterns of seed consumption and dispersal preventing future regeneration of forest borders. Likewise, Banks and Dickman [20] proposed that a lack of seeds has a direct impact on the population growth and habitat use of small rodents. Thus, both plant and animal populations are affected by changes in microclimates as a result of edge effect, and these effects become more severe the bigger the fragmentation and the smaller the remaining fragments [21-24]. Moreover, according to the metacommunity theory, colonization and extinctions are related to patch size and connectivity [25]. Unfortunately mice from these forests are poorly studied and the information available for them is scant; their assessment and protection is compromised even more as they are not charismatic species. Thus, there is a need to quickly assess their risk status and enlist them in the National Red Lists to advance their conservation. In this exercise, we provide a working example of an assessment of a poorly known group of species in a quickly disappearing habitat in order to compare a qualitative-national method (MER) with a quantitative-global method (IUCN Red List). In addition, we compared the mammals listed in both the Mexican National Red List and the IUCN to pinpoint the discrepancies between the assigned risk categories in order to explore how different methods may reach different outcomes.

Materials and Methods

Selecting species for the assessment

To select the species for this study we performed a search within the mammal IUCN Red List database using the criteria listed in Table 1. We cross-referred the results from this first search to the mammals listed in the IUCN Red list but not in the Mexican Red List (NOM-059-SEMARNAT-2010), and picked a set of ten Mexican endemic frugivorous rodents that had been assessed by the IUCN but have not been assessed by the Mexican Red List. During all searches we checked both lists for misspelled names or synonyms, to avoid biasing the outcome.

MER  IUCN
P CR
EN
A Vu
PR NT
LC

Table 1: Suggested equivalence between MER and IUCN Red List categories (Sánchez et al., 2007).

Finally we gathered collection data points from the National Information System of Biodiversity (SNIB, acronym in Spanish) from CONABIO (National Commission for the Knowledge and Use of Biodiversity, Mexico) to map these species’ occurrence and sought for occurrences within Natural Protected Areas (NPA) within Mexico to find out whether at least some of the non-assessed species were protected by this strategy.

The process of assessing

The MER has four criteria to assess risk categories: Criterion A: distribution; Criterion B, habitat; Criterion C, intrinsic vulnerability; and Criterion D: human impact [2]. Each criterion is evaluated qualitatively, and the total score is calculated by adding the results from the four. The higher the value of the total score, the higher the risk of extinction of the assessed species [2]. For animals and fungi, species with a total score between 12 and 14 points is considered as endangered (P), between 10 and 11 threatened (A), whereas a score lower than 10 can grant special protection status (Pr) providing that evidence for this urgency is given. For comparison sake, it is worth noting that the IUCN method contemplates five criteria: Criterion A: population size reduction; Criterion B: geographic range; Criterion C: small population size and decline; Criterion D: very small or restricted population; Criterion E: quantitative analysis [26]. Contrary to what happens with the MER, the IUCN method does not require all criteria to be completed in order to obtain an assessment, rendering the method especially useful for species with different levels of information (To learn more see IUCN) [26].

To perform the species assessments via the MER we gathered all available bibliographic information from these ten rodents. In the cases where information for the species was scant or inexistent, we used the general data from the genus to complete the assessment, as the majority of the missing data was for the intrinsic vulnerability criterion, comprising the species’ biology, life span, reproduction, diet and behaviour. Although we were aware that using the general information from the genus might bias the final assessment, it was the only way in which the assessments could be completed.

Comparing the risk status of mammals listed in the Mexican Red List and the IUCN Red List

We then broaden our comparison to species already assessed by both methods with the aim to find differences in evaluation results (similar to what Brito et al., [27] proposed). However, it is important to mention that it was only possible to compare the results and not the content of each evaluation, as Mexico’s species assessments are restricted.

We used the mammal data sets from NOM-059-SEMARNAT-2010 and IUCN to find if there were any discrepancies between species risk status. To do this, we first filtered all species occurring in Mexico, whether endemic or not, with a risk status under both lists. We discarded all subspecies included in the Mexican Red List as the IUCN does not evaluate subspecies. We then cross-referred by scientific names, IUCN categories (VU, EN and CR) and MER categories (P, A). It is worth noticing that even though LC and Pr are not risk status, we included both in order to have a broader comparison.

Results

Our search of IUCN’s data base using the parameters in table 1 returned 10 mice species belonging to four different genera (Habromys, Neotoma, Peromyscus, Sigmodon) listed in the IUCN Red List of threatened species V.3.1 under the categories of Vulnerable (VU), Endangered (EN), and Critically Endangered (CR) (Table 2), which are not yet included in the Mexican National Red List. All these species occur in montane habitats (Table 3), and the threats to all them are known and reported in their individual IUCN assessments (Table 3). The most common threat for these species was habitat loss due to anthropogenic pressure, although this threat can vary depending on region and species (Table 4). Out of these 10 species, the five Habromys species are listed as Critically Endangered (CR) and all inhabit the cloud forest, whereas the rest inhabit the dry forest and are listed under different categories: two as Endangered (EN) Peromyscus melanurus and Sigmodon planifrons and three Vulnerable (VU) Neotoma palatina, Sigmodon alleni and Peromyscus Simulus. The distribution for these ten species can be found in Figures 1a-j. Furthermore, only six of these rodents occur within NPAs, which means that only 60% of the species are under indirect protection.

Taxonomy Mammalia
Location modifiers Native
Selected location Mexcio
Selected systems Terrestrial
Threatened categories Vulnerable (VU)
Endangered (EN)
Critically Endangered (CR)

Table 2: Search criteria and parameters (IUCN, 2012 v.3.1)

Species Category Criteria Distribution Vegetation type Threat Natural protected area
Habromys chinanteco CR B1ab(iii) Oaxaca Cloud forest Deforestation No
Habromys delicatulus CR B1ab(iii) Edo. Mex Cloud forest Deforestation No
Habromys ixtlani CR B1ab(iii) Oaxaca Cloud forest Deforestation No
Habromys lepturus CR B1ab(iii) Oaxaca Cloud forest Deforestation No
Habromys schmidlyi CR B1ab(iii) Guerrero Cloud forest Deforestation No
Neotoma palatina VU B1ab(iii) Jalisco Tropical deciduous forest Dam, flood Aguamilpa-El Cajón; Sierra Huicholes
Peromyscus melanurus EN B1ab(iii) Oaxaca Tropical lowland deciduous forest, pine-oak Habitat loss, agriculture No
Peromyscus simulus VU B1ab(iii,v) Nayarit, Sinaloa deciduous forest, Hábitat loss due to agriculture & pesticides Meseta Cacaxtla; Biosphere Reserve Marismas Nacionales
Sigmodon alleni VU A2c+3c+4c Guerrero, Michoacán, Colima, Jalisco, Nayarit, Sinaloa Pine-Oak forest, Deciduous forest Deforestation Biosphere Reserve Manantlán;
Biosphere Reserve Chamela-Cuixmala
Sigmodon planifrons EN B1ab(iii) Oaxaca Deciduous tropical forest Habitat fragmentation, Tourism development No

Table 3: Group of 10 endemic rodents found assessed by IUCN but not by the NOM 059-SEMARNAT-2010.

MER criteria IUCN criteria
A Distribution A Population size reduction
Description (altitude, continue or fragmented, states of the country) Population reduction measured over the longer of 10 years or 3 generations
Map B Geographic range
Mapping method Extent of occurrence
Assessment Area of occupancy
B Habitat Severely fragmented or number of locations
Record (Habitat type which species occupy) Continuing decline of habitat, extent of occurrence or area of occupancy
Diagnosis of the current habitat status Extreme fluctuations of habitat, extent of occurrence or area of occupancy
Evaluation of the current habitat status focusing on the taxon’s needs C Small population size and decline
Assessment Number of mature individuals
C Biological vulnerability Observed, estimate or projected continuing decline of population up to 100 years
Natural history Observed, estimate or projected continuing decline of population of mature individuals in subpopulations or extreme fluctuations in the number of mature individuals
Diagnosis of the current status D Very small and restricted population
Factors that makes the species vulnerable Number of mature individuals
Assessment E Quantitative analysis
D Anthropogenic pressures Indicating the probability of extinction in the wild by numeric analyses
Real and potential risk factors  
Prediction analysis of species trend
Assessment of direct and indirect human impact

Table 4: Criteria required by the MER and the IUCN to assess species.

biodiversity-endangered-species-Rodents-Distribution

Figure 1: Rodents Distribution. (a) Habromys chinanteco. (b) Habromys delicatulus. (c) Habromys ixtlani. (d) Habromys lepturus. (e) Habromys schmidlyi. (f) Neotoma palatina. (g) Peromyscus simulus. (h) Peromyscus melanurus. (i) Sigmodon alleni. (j) Sigmodon planifrons.

The assessment results for each one of these species via the MER (Supplementary Information) place the ten species of mice in the highest risk status of the Mexican National Red List (P, Endangered), which according to Sánchez et al., [2] is equivalent to the IUCN’s Critically Endangered (CR) category.

When we compared all Mexican mammals listed in both the IUCN and the Mexican Red List, we found discrepancies as we did for the five dry forest species assessed in this study. After cross-referring and excluding subspecies, we found that in IUCN´s Red List there are 100 mammals assessed and listed under different risk categories; of them, 44 mammals were both in the IUCN and Mexican lists under a risk category, and 23 were under the Mexican red list precautionary status (Pr). Out of these 23 none were under (LC) or (NT) in IUCN’s Red List (see table 5), whereas the remaining 33 were only assessed by the IUCN. Of these 44, 25 species were listed as threatened (A), and 19 species as Endangered (P).

Species IUCN Red List Category MER Category Species IUCN Red List Category MER Category
Alouatta pigra EN P Peromyscus dickeyi CR Pr
Ateles geoffroyi EN P Peromyscus guardia CR P
Balaenoptera borealis EN Pr Peromyscus sejugis EN A
Balaenoptera musculus EN Pr Peromyscus slevini CR A
Balaenoptera physalus EN Pr Peromyscus stephani CR A
Chaetodipus dalquesti VU Pr Peromyscus winkelmanni EN Pr
Cryptotis magna VU Pr Peromyscus zarhynchus VU Pr
Cryptotis nelsoni CR Pr Phocoena sinus CR P
Cryptotis obscura VU Pr Physeter macrocephalus VU Pr
Cynomys mexicanus EN P Procyon pygmaeus CR P
Dipodomys insularis CR P Reithrodontomys spectabilis CR A
Dipodomys margaritae CR P Rheomys mexicanus EN Pr
Geomys tropicalis CR A Rhogeessa genowaysi EN A
Habromys simulatus EN Pr Rhogeessa mira VU Pr
Heteromys nelsoni EN Pr Romerolagus diazi EN P
Leptonycteris nivalis EN A Sorex macrodon VU A
Lepus flavigularis EN P Sorex milleri VU Pr
Liomys spectabilis EN Pr Sorex sclateri CR A
Megadontomys cryophilus EN A Sorex stizodon CR A
Megadontomys nelsoni EN A Spermophilus perotensis EN A
Megadontomys thomasi EN Pr Spilogale pygmaea VU A
Microtus oaxacensis EN A Sylvilagus graysoni EN P
Microtus umbrosus EN Pr Sylvilagus insonus EN P
Musonycteris harrisoni VU P Sylvilagus mansuetus CR P
Myotis planiceps EN P Tamiasciurus mearnsi EN A
Myotis vivesi VU P Tapirus bairdii EN P
Nelsonia goldmani EN Pr Trichechus manatus VU P
Neotoma bryanti EN A Tylomys bullaris CR A
Notiosorex villai VU A Tylomys tumbalensis CR Pr
Orthogeomys lanius CR A Xenomys nelsoni EN A
Peromyscus bullatus CR Pr Zygogeomys trichopus EN P
Peromyscus caniceps CR Pr      

Table 5: List of threatened Mexican mammals assessed by IUCN Red List and MER. Suggested equivalence CR/EN=P; VU=A; Pr has nonequivalence with CR, EN and VU.

When comparing both lists, we found that for those listed as threatened (A) in the Mexican Red List only three species have an equivalent status for that category under the IUCN [2], whereas the remaining 22 species had a higher risk status in the IUCN list, as 11 were listed as Critically Endangered and the other 11 as Endangered (see table 5). In the case of species listed as Endangered (P) in the Mexican red list, 16 out of the 19 species were equivalent [2] (Table 5). Another three species were listed as Threatened (A) (see table 5). Finally, of the remaining 23 species which are listed Under Special Protection (Pr), a precautionary status that does not denote an immediate risk and is similar to that of Least Concern (LC) and Near Threatened (NT) (Table 1), 5 were listed as CR, 11 as EN and 7 as VU in the IUCN Red List (Table 5).

Discussion

Assessing risk status through the MER and comparing them to IUCN´s assessment

The aim of risk assessments is to convey the conservation status of a given species in a simple, transparent, and objective way in order for it to be relevant in terms of scope and impact for conservation actions. Throughout this case study we were particularly interested in seeing the difference outcome between the IUCN and the Mexican Evaluation of Risk methods; see more arguments at [1,28,29].

The most striking difference that we found between the MER and the IUCN method was the simplicity of the latter to handle the lack of data: while in the MER all criteria have to be completed with a great amount of detail to in order to get a score, IUCN´s method allows the use of whatever criteria is suitable for the information available. In our example, when assessing the ten rodents via the MER, all of them got the highest value in criterion A (4 points, distribution) due to their very restricted area which occupies less than 5% of Mexico’s territory. However, this criterion was the only one that had a quantitative threshold to establish a score. Take for instance criterion C, biological vulnerability; not only is it complicated to have this information for all species, but also, the assessor has to decide among three scores (low, medium and high) without the method guiding the decision through objectively documenting the criteria or quantitative thresholds among the three. In our case study we gave the highest score in this criterion C to dry forest species, as we knew that their reproduction was limited to and by the rainy season [16], however, we did not know the number of individuals per litter, or age at first reproduction among many other biological features needed, so we had to extrapolate information from the genus to the different species in order to perform the evaluation; without doing this, many species could not have achieved a risk category. On the other hand, according to IUCN´s assessment, nine rodents were classified mainly through their small distribution range as follows: Five were classified as Critically Endangered B1ab(iii), (Habormys chinanteco, H. delicatulus, H. ixtlani, H. lepturus, and H. schmidlyi), two as Endangered EN B1ab(iii) (Peromyscus malnurus and Sigmodon planifrons),and two as Vulnerable (Peromyscus simulus) VU B1ab(iii,v) and Neotoma palatine B1ab(iii) due to their extremely reduced extent of occurrence (B1) (<100 km2), the fact that all individuals occur in one location (a), the continuing decline in the extent and quality of their habitats (b(iii)), and a continuing decline of mature individuals(b(v)). Only one species in our case study (Sigmodon alleni) was classified as Vulnerable VU A2c+3c+4c through IUCN´s criterion A, population size reduction, based on a decline in area of occupancy (AOO), extent of occurrence (EOO) and/or habitat quality (c) (more info in IUCN, 2012).

The outcome of our example using the MER, although limited as per the small number of assessments completed, highlights the problematic nature of having to assign a score without a quantitative guideline. Therefore the scores of most criteria tend to be biased by the assessor judgment even when the information is not scant. Although in the past the IUCN used more qualitative criteria, they were changed to quantitative criteria to eliminate assessors’ subjectivity and bias [26]. This change to quantitative criteria proved to diminish errors and bias from assessor, as it is important to achieve the same result no matter who is performing the assessment [27]. Moreover, we found that when using the MER to assess poorly known species, low values due to gaps in knowledge can prevent the listing of any species as the risk status is the result of a sum of all criteria (A+B+C+D). Whereas IUCN’s method overcomes this situation by using whatever, information exists and in a more objective way through a series of guidelines.

For many species like the ones included in this study which inhabit some of the most threatened habitat in Mexico, lack of data is a constant [30] and this situation will not change in the short-term. Thus, using the information available to assess target species is a far better option that has been adopted by IUCN’s assessments, and that should be implemented in the MER. For instance, Raimondo, Staden & Donaldson [31] accomplished the task of assessing and assigning a risk category to all South African plant taxa with very scant information for many of them, showing that the lack of information should not preclude objective assessments. Several authors agree that uncertainty will always be associated to the data used to evaluate species, however, it does not mean that information carrying a certain amount of uncertainty has to be ignored when assessments are performed [1,32] as long as the source and the caveat of the uncertainty is clearly stated in the assessment support information.

Another aspect that needs to change in the assessments performed via the MER assessments is that currently there is no support information that accompanies the risk status; thus, two species in the same risk category and the same score may most likely have different problematic [1,2,28,33] (Table 4). It follows that a justification for each of the four criteria should be included along with the assessment, as this would truly make the assessments relevant for conservation actions. Currently, the MER is not even publicly available. Authors like Brito et al. [27] recommend that all assessments should be publicly available, including results, procedures, decisions, rationale, and data used. No matter the methodology employed or the scale. De Grammont & Cuarón [1] suggested that risk assessments must have support information according to the categories granted, referring to the species’ present condition.

It is important to note that even though risk categories differ between systems (i.e., MER and IUCN), all of them should help decision makers implement the best conservation actions as needed [1]. In this case, both assessment methods agree on the risk status of the five species of cloud forest mice (Habormys chinanteco, H.delicatulus, H. ixtlani, H. lepturus, and H. schmidlyi), but not on the status of the dry forest, as the MER place them as endangered (P), whereas according to the IUCN two are endangered (EN) (P. malnurus and S. planifrons) and the rest are vulnerable (VU) (N. palatina, P. stimulus and S. alleni). There are several examples in which there is no congruence between assessment methods. In a recent study by Armenta-Montero et al. [29] with ferns of the genus Phlegmariurus, these authors found that only one of the nine species in the state of Veracruz, Mexico was included in the NOM-059-SEMARNAT-2010. When they assessed the nine species following IUCN’s method, five of them were classified as Vulnerable, three as Endangered and one, the species listed in the NOM-059-SEMARNAT-2010 under Special Protection (Pr), as Critically Endangered. Five out of ten of our results matched those from the IUCN Red List as they are endemic species and were assessed using IUCN´s Red List criteria B, i.e., restricted distribution. On the other hand, these species achieved the highest score in the MER due also to their restricted distribution and to the fact that they inhabit the cloud forest, the most threatened habitat in Mexico. As for the five species of dry forest assessed, there were discrepancies between the assessments. Three species (N. palatina, P. stimulus and S. alleni), were assessed as endangered (P) in the MER whereas the IUCN Red List placed them as Vulnerable (VU). This discrepancy is recurrent as well in our broader comparison of assessed mammals, as 67 species the categories do not match (Table 5). More importantly, a quick review highlights that 23 (34.32%) of these species fall Under Special Protection (Pr), which is equivalent to IUCN Least Concern (LC) or Near Threatened (NT) (see table 1). Nevertheless these species are listed with some level of threat threatened in the IUCN Red List; 5 CR, 11 EN, and 7 VU. This is a case in which it is clear why having the MER assessment information would be beneficial as it would allow us to clarify the reason for the actual differences between both results.

As we show in this case study we strongly support the idea that it is time to update the MER in order for it to be as useful as possible, especially in the light of the lack of information that we face with endangered species. Just as the issue of how to apply IUCN’s method at the regional level have been addressed widely making its use more prevalent than ever before, we think some adjustments to the MER may transform this instrument profiting from its strengths and overcoming its weaknesses to better reflect our country’s needs.

Conclusion

The most significant difference that we found between the MER and IUCN´s assessment method is the flexibility that IUCN allows, especially for species with lack of information. Even though the MER was specifically conceived to assess species at a local scale, we found the assessment may not always be objective, as the criteria are not well documented, not all of the information is present or may not be relevant for a group of species. As a result, some MER assessments might be biased.

We agree with many other authors [1,3,27,28,31,34] that the main objective of a Red List is to provide warning time and protection to the species in the more accurate way. As species extinction rates are increasing faster than we can assess species, we strongly suggest a review of the MER, with the goal of making it easier to assess species, with independency among criteria due to information gaps, with the use of information which is significant for conservation purposes, and a complete documentation and transparency of the supporting information for each species status. This need is evident for species like those in the genus Habromys which inhabit the most threatened ecosystem in Mexico, the cloud forest [5,11,12] a fact which by itself should be enough to enlist and protect them and that should be easily achieved through the MER assessment.

Acknowledgement

We would like to thank Edgar Saavedra from the Subcoordinación de Especies Prioritarias, at CONABIO for preparing the maps for this study, as well as to all our colleagues that were kind enough to improve this manuscript with valuable comments.

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