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Article

Prediction of Environmentally Suitable Areas for Zephyranthes (Amaryllidaceae) in Mexico

by
Zayner Edin Rodríguez Flores
1,
Yanet Moredia Rosete
2,
Jesús Alejandro Ruiz Valencia
2 and
Yolanda Leticia Fernández Pavía
1,*
1
Department of Soil Science, College of Postgraduates in Agricultural Sciences Campus Montecillo, Montecillo, Texcoco 56264, MX, Mexico
2
Department of Botany, College of Postgraduates in Agricultural Sciences Campus Montecillo, Montecillo, Texcoco 56264, MX, Mexico
*
Author to whom correspondence should be addressed.
Ecologies 2024, 5(4), 571-584; https://doi.org/10.3390/ecologies5040034
Submission received: 17 August 2024 / Revised: 27 September 2024 / Accepted: 4 October 2024 / Published: 16 October 2024
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Abstract

:
The genus Zephyranthes is widely represented in Mexico, with 37 species of ornamental and medical importance. However, basic aspects of the genus, such as the environmental variables that determine its presence in certain sites, have not yet been addressed, which limits the knowledge of its ecology, potential applications and possible conservation strategies. Potential distribution models were generated with data on the presence of 13 species of the genus Zephyranthes, using 28 bioclimatic and edaphic variables with the maximum entropy method (Maxent). Of these variables, the most important and least correlated for each species were chosen by principal component analysis (PCA); the occurrence data were obtained from digital platforms and filtered to reduce spatial autocorrelation. The resulting models, had AUC values > 0.90 and Kappa index values > 0.6, in addition to being significant according to the results of the binomial test applied (p < 0.05). Maximum temperatures and humidity, as well as annual precipitation, are relevant environmental variables for the niche models. Most species are distributed in the biogeographic province of the Transmexican Volcanic Belt. Zephyranthes concolor and Zephyranthes lindleyana were the species with the largest potential range. The species with the most restricted potential distribution were Zephyranthes citrina and Zephyranthes sessilis. The most determinant variables for species with neotropical affinity are different from those identified for Nearctic species, reflecting niche differentiation, congruent with the evolutionary history of Zephyranthes.

1. Introduction

Mexico is considered one of the most diverse countries on the planet, harboring a large number of plant species, with a significant number of native taxa, which generally require further study due to the constant variation of the environment by natural events and anthropogenic activities [1,2,3]. Of the Amaryllidaceae family, there are species of the genera Hymenocallis, Sprekelia and Zephyranthes that are endemic to Mexico and have been identified with high potential for ornamental use [4,5].
The latter genus includes plants that have been used in traditional oriental medicine for their antiviral properties [6] and have recently been studied for their cytotoxic content in pharmaceutically important secondary metabolites such as those of the galanthamine group [7,8,9,10,11,12,13]. These compounds have been employed in palliative Alzheimer’s therapy for several years now, with approval from the U.S. Food and Drug Administration (FDA) [13,14].
There are currently 191 records of putative species for the genus Zephyranthes [15]; however, in World Flora Online [16], only 89 species are under the accepted designation. In Mexico, 37 species of the genus are known to be endemic to Mexico [5]. However, in the national territory, there are only records of the presence of 35 species in data consultation networks such as the Global Biodiversity Information Network (REMIB) (http://www.conabio.gob.mx/remib/doctos/remibnodosdb.html?#), accessed on 19 May 2020 and the Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/). The study of these species is limited, so it is important to generate basic knowledge of the genus. Existing work has focused on generating knowledge in taxonomic [17,18], molecular [19], chemical, pharmacological [20], mineral nutrition and biostimulation aspects [21]. There is no record of studies that focus on aspects related to the ecology of these species.
Given the importance of Zephyranthes in Mexico in terms of biodiversity and uses, as well as the small number of investigations, it is crucial to promote the study of this genus. However, to initiate this process effectively, fundamental aspects of this group of plants, such as their distribution in the Mexican territory, must be understood. This is relevant, since the lack of information on the spatial patterns of a species limits the ability to understand its ecology, conservation and potential applications as an ornamental or cytotoxic product [22,23].
Ecological niche modeling using the maximum entropy method (Maxent) calculates the probability of presence of a species, conditioned by the environment, and generates predictive models of potential distribution with high accuracy [24,25,26]. This approach is particularly useful for understanding differences in ecological niches among species, as it allows the identification of environmental factors that influence their distribution [27]. Maxent has been widely used in several taxonomic groups [28,29,30,31,32,33] to predict species distributions and develop conservation strategies, especially for species with restricted distributions [34,35,36,37,38]. From the results of the models, it is possible to define the geographic range that a species could occupy, if there were no significant restrictions in terms of mobility and available space [25].
This method has been widely used over time and its results have been compared with other models, identifying that Maxent generates reliable results [39,40,41,42,43]. The application of the maximum entropy method in ecological niche models is of particular importance when dealing with endemic species, as Maxent has been shown to generate reliable results for entities with restricted distribution [23,29,30,31].
The objective of this study was to determine the ecological niche distribution of 13 species of Zephyranthes in Mexico, and to determine which environmental variables are most important in predicting the potential distribution. It is assumed that each species has different climatic and edaphic factors that delimit its ecological niche and that these influence its potential geographic distribution. To clarify the above, the following questions will be answered: What are the environmental variables that influence the potential distribution of each of the 13 species of the genus Zephyranthes? What is the potential distribution of each of the species in the country?

2. Materials and Methods

2.1. Database of Species

For the construction of the occurrence database, data from the last 30 years were consulted in the Global Biodiversity Information Facility (GBIF) network (https://www.gbif.org/) and the World Biodiversity Information Network (REMIB) of Conabio (http://www.conabio.gob.mx/remib/doctos/remibnodosdb.html?#).
Occurrence data were found for 35 Zephyranthes species, but only 23 were correctly georeferenced (Table 1). A total of 1418 data were obtained from GBIF and 163 from six REMIB herbaria (Instituto de Ecología (IE-XAL); Instituto Politécnico Nacional (ENCB); Universidad Autónoma Metropolitana (UAM-1); Herbarium of the University of Texas (LL, TEX); Herbarium of the Centro de Investigación Científica de Yucatán (CICY) and Herbarium of Geo. B. Hinton) (Supplementary S1).
All records and their geographic coordinates were subjected to two phases of cleaning. In the first phase, data of species for which the taxonomic identity of the species was unclear and duplicate data were eliminated. Subsequently, atypical data were discarded for each species, i.e., data that were outside the natural distribution of the species. Finally, records were thinned using the spThin v0.2.0 package [44] of the R programming v4.4.1 language [45] within the RStudio v4.4.0 environment [46]. The bias associated with the aggregation of nearby occurrence records was minimized by thinning the records to ensure that the minimum distance between records was 1 km2, and repeating the process five times to obtain an optimal configuration.

2.2. Bioclimatic Variables

For the construction of the models, a total of 28 environmental variables were used (Table 2), including historical data of 19 climate variables from WORLDCLIM v2.1 from the years 1970 to 2000 [47] and a set of 9 edaphic variables detailing the properties of the soils of Mexico performed by Cruz-Cárdenas [48], both sets of variables with a resolution of 1 km2.

2.3. Selection of the Environmental Predictors

To reduce the multicollinearity of the environmental predictors, the number of variables was reduced using principal component analysis (PCA) [49]. The choice of components was made under the Kaiser criterion, which suggests taking only components that reach a value of approximately 80% of the cumulative variance [50]. After the selection of the components, the value of the loadings allowed selecting the factors included in the models, by standardizing the variables [51,52,53,54]. PCA was performed with the FactoMineR v2.11 [55] and factoextra v1.0.7 [56] packages of the R programming language [45] within the RStudio v4.4.0 environment [46]. From each component, the variables with the highest loading value were considered to generate the models [57].

2.4. Construction of Potential Distribution Models

MaxEnt v3.4.4 [58] was used to run the models. Modeling based on the maximum entropy principle generates more reliable results with small sample sizes; however, these are more robust when samples with more than 10 occurrence data points are used [59]. Therefore, only species with more than 10 occurrence records were considered for the construction of the models; models were made for a total of 13 species.
The fitting parameters used in the program were those that came by default in the software, with the exception of the Extrapolate and Do clamping options that were disabled to avoid artificial extrapolations in the extreme values of the ecological variables [25,60], and Hinge and Threshold to avoid overfitting of the response curves. Of the three replicate run types (Subsample, Crossvalidate and Bootstrap), the one that would best fit the sample size was chosen in order to assess the stability and performance of the model [61]. The “Subsample” type was adjusted for models whose occurrence data were greater than 100, for the benefit of randomly dividing the sample in the presence of species of a defined proportion in the training and test samples. For models with fewer than 100 observations, but more than 20 records, “Bootstrap” was used, adjustment-able to extract random samples from the original sample and build models, to finally average the results. Finally, for small samples between 10 and 20 observations, “Crossvalidate” was used, which is ideal for small data sets as it ensures that each data point is used for training as well as for validation, providing a good estimate and less probability of overfitting [61,62,63].
An adjustment of the parameter’s regularization multiplier (1), maximum number of background points (10,000), convergence limit (0.00001) and maximum iterations (1000) was used. A logistic type output was obtained using a minimum presence threshold; in the models where the Bootstrap and Subsample replication type of execution was used, 75% of the randomly distributed records were considered for the training of the models and 25% for their validation. Once the models were obtained, the Jackknife test given by MaxEnt was performed, which allowed detecting the variables with the greatest contribution in each model. The construction of the model was repeated only with the variables of importance for each species.
The models in ASCII format were projected using Quantum GIS v3.26.1 [64] for the representation of a gradient categorized with the suitability for the species studied. Additionally, the calculation of the niche distribution area for each model was performed with the raster package v3.6–26 [65] of the R programming language [45] within the RStudio v4.4.0 environment [46], using the Maximum test sensitivity plus specificity (MTSPS) value given by MaxEnt as a cut-off threshold. For the interpretation of the potential distribution of each species in Mexico, the 14 biogeographic provinces proposed by Morrone [66] were used. This zonation combines climatic, geological and biotic criteria that provide a better classification of the boundaries between ecoregions [66].

2.5. Evaluation of Models

The evaluation of the models was carried out with the results of the Area Under the Curve (AUC) analysis of the Receiver Operating Characteristic (ROC); according to [67], values greater than 0.9 are accepted as very good models and values greater than 0.8 as good [52]. Additionally, a binomial test [68] was performed with the stats package [45] of the R programming language in the RStudio v4.4.0 environment [46]. The analysis was performed using as a criterion the MTSPS cutoff threshold to assess whether the model was better than a random one p < 0.05 [69].
To measure the agreement between the predictions obtained from the model and the data observed in the field, Cohen’s Kappa index [70] was calculated for each model. The MTSPS cutoff threshold was used to convert the continuous probabilities of presence predicted by the model into binary categories of presence or absence. Values greater than 0.4 of the Kappa indexes suggest a level of agreement between model predictions and observed data according to [71]; i.e., the model adequately predicts the distribution of the species.

3. Results

3.1. Layers of Bioclimatic Variables

In 12 species, the components PC1, PC2 and PC3 explained the minimum expected proportion of the cumulative variance, and only in the species Z. fosteri were four components selected (Supplementary S2). The variables that were the most important determinants of species distribution with the highest contribution for most of the distribution models were BIO1, BIO8, BIO10, BIO13 and SMNa (Table S1).

3.2. Evaluation of the Models and Contribution of Bioclimatic Variables

The values of the area under the receiver-operated curve (ROC) obtained in the test models for 12 Zephyranthes species were greater than 0.9 and only 1 had a lower value (Z. lindleyana) (Table S2).
The p-values of the binomial test confirmed the validation given by the AUC of the ROC curve (p-value > 0.05) in all cases demonstrating that all models generated were valid and better than a random one. Likewise, Kappa index values of 0.6 to 0.9 were obtained, indicating that all models adequately predicted the potential distribution of the species (Table S3).

3.3. Known Distribution of the Genus Zephyranthes

The actual distribution observed by the occurrence records of 13 species of the genus Zephyranthes (Figure 1) indicates a wide distribution in the Mexican territory from the north of the country, where species such as Z. lindleyana and Z. morrisclintii are distributed in the northern zone of the Sierra Madre Oriental, to the Yucatan Peninsula, where species such as Z. citrina are distributed. However, Zephyranthes such as Z. brevipes, Z. carinata, Z. concolor, Z. clintiae, Z. fosteri, Z. longifolia and Z. sessilis are concentrated in the central zone of the Mexican territory.
Zephyranthes brevipes. The highest probability of suitability is located in the Trans-Mexican Volcanic Belt province and south of the Chihuahuan Desert province. A medium suitability was observed in the Balsas Basin Province, as well as in the south of the Sierra Madre Oriental province and in the central zone of the Chiapas Highlands. Low suitability was found in the Sierra Madre del Sur Province (Figure 2a).
Zephyranthes carinata. This species has a high potential for habitat suitability in the central region of the national territory. It covers the southern provinces of the Chihuahuan Desert Province, the Transmexican Volcanic Center Province, Balsas Basin, Sierra Madre Oriental, Sierra Madre del Sur and Chiapas Highlands. Low suitability was found in the provinces of the Veracruz Province, Sierra Madre Occidental, Northeastern Chihuahuan Desert Province and Tamaulipas Province (Figure 2b).
Zephyranthes chichimeca. High habitat suitability is concentrated in the northern region of the country, in the Sierra Madre Oriental and southern Chihuahuan Desert provinces. It also presents a medium potential distribution in the provinces of California and Baja California. Low suitability was found in the provinces of the Transmexican Volcanic Belt and the Yucatan Peninsula (Figure 2c).
Zephyranthes chlorosolen. This species has a high potential for geographic suitability in the Tamaulipas Province. Medium suitability was observed in the northern Chihuahuan Desert Province and northern California Province. Low suitability was found in the center of the country (Figure 2d).
Zephyranthes citrina. The areas of greatest geographic distribution of the species are in the Yucatan Peninsula province. In the Veracruz province in the southern zone, it has a medium–low distribution (Figure 3a).
Zephyranthes concolor. For this species, the potential distribution was medium–high in the Transmexican Volcanic Belt and Chihuahuan Desert provinces (Figure 3b).
Zephyranthes drummondii. This species has a medium–high potential for habitat suitability in the Chihuahuan Desert province. A low potential distribution was found in the southern Veracruz province and the Chiapas Highlands (Figure 3c).
Zephyranthes fosteri. This species has a medium–high suitability in the central and southwestern part of the country. Specifically, it has medium–high habitat suitability in the provinces of the Transmexican Volcanic Belt, Balsas Basin, Sierra Madre del Sur and the Chiapas highlands (Figure 3d).
Zephyranthes lindleyana. The highest potential distribution range for the species is in the Transmexican Volcanic Belt and along the Sierra Madre Oriental province and in the Sierra Madre del Sur province, while the medium–low potential distribution is along the Chihuahuan Desert province and the Sierra Madre Occidental (Figure 4a).
Zephyranthes longifolia. A high potential distribution was not found for this species because of habitat suitability, with a medium potential distribution in the Chihuahuan Desert province and the Sierra Madre Oriental, Transmexican Volcanic Belt and Madre del Sur province, in addition to the California and Sonora provinces (Figure 4b).
Zephyranthes minuta. High distribution suitability for this species was found in the central states of the country, in the Transmexican Volcanic Belt province. A medium-low suitability was observed in the Sierra Madre del Sur province and in the Highlands of Chiapas (Figure 4c).
Zephyranthes morrisclintii. The high potential distribution of this species is mainly in the biogeographic provinces of Chihuahuan Desert, Sierra Madre Oriental, Tamaulipas Province and Sierra Madre del Sur. A low potential distribution was found in the provinces of Sonora, and in the Yucatan Peninsula province (Figure 4d).
Zephyranthes sessilis. For this species, a more restricted potential distribution was found in the center of the Transmexican Volcanic Belt (Figure 4e).
Regarding the geographic area for each species, the prediction of the potential distribution area calculated for each model indicates that the species with the highest habitat suitability were Z. carinata and Z. longifolia. And the species Z. brevipes and Z. concolor obtained the lowest area suitability (Table S4).

4. Discussion

The genus Zephyranthes is distributed in both xerophytic and flooded environments [72], where temporal conditions of temperature and water availability are limiting factors. This is congruent with the environmental variables with greater weight in the generated models, since it was identified that the mean and maximum temperature of the warmest (BIO5 and BIO10) and wettest (BIO8) seasons, as well as the mean annual precipitation (BIO12), which are the most important variables in different degrees for the environmental suitability across Zephyranthes.
It has been reported that the start of the rainy season and the oscillation of temperature are fundamental for the reproduction of Zephyranthes, since after the first rains, the flowering of the species of the genus occurs [72]. The duration of flowers produced will be affected by both temperature and sun exposure [5,73]. This implies that precipitation promotes the onset of the reproductive cycle, and temperature is related to the time available for pollination in Zephyranthes. This interpretation is reinforced by the ecological niche models reported in this study.
Previous research on the ecological niche of Amaryllidaceae species reported that variations in values for seasonally temperature and precipitation are the main abiotic factors that determine suitability for Crinum malabaricum and Phaedranassa brevifolia [74,75]. This coincides with what was reported in this research; future work on other taxa of Amaryllidaceae will allow us to determine if there is a niche conservatism with respect to the variables with greater weight in the models in the components of the family. Most of the species are distributed and have greater probability of environmental suitability in the center and south of the country. This maybe explained by the evolutionary origin of the genus; through phylogenetic analysis, it has been determined that Zephyranthes originated in South America and dispersed to Mexico through Central America [76]. This would explain the neotropical affinity of the Zephyranthes species studied. There are also species such as Z. longifolia and Z. morrisclintii that have dispersed to the north of the country. The most important variables for the niche models of these species are different from those relevant for species with neotropical affinity. This may reflect a niche differentiation between widely distributed species and those with more restricted geographic ranges. Several investigations reported that niche modeling allows to stablish species limits in different taxonomic groups of plants and animals [77,78]. Future morphological, phylogeographic and niche conservatism analyses will reveal whether these differences in the fundamental niche of Zephyranthes species in Mexico are informative at the interspecific level.
The results reported in this research were obtained with environmental variables generated between 2000 [48,49] and 2017, with 1 km2 resolution. This implies that, in the interpretations generated in this work, possible environmental changes that have occurred in Mexico in recent decades are not considered. On the other hand, the resolution of the layers limits the ecological interpretations made, as they do not have the capacity to generate models at the microclimatic level. However, the available environmental layers are the most updated available, so they are an important source of information, which has allowed the generation of reliable models in various investigations in recent years [79,80,81,82]. Potential distribution models are fed by available environmental information. Therefore, it is essential that research centers, organizations and national and international institutions update the available environmental information.
The models reported in this work were performed with the MaxEnt algorithm, obtaining reliable results, given the values of the metrics evaluated. Several authors have tested the performance of ensembles of algorithms in conjunction and comparison with MaxEnt. In a considerable number of investigations, the use of ensembles of algorithms has allowed obtaining consensus models with a high degree of confidence [83,84]. However, there are also studies in which the performance of MaxEnt was compared with other tools, which found that there are no significant differences between the results obtained with the maximum entropy model and other models or ensembles [42,85]. On the other hand, the number of publications and types of investigations in which MaxEnt is implemented is still considerable, making it an accepted and reliable tool.
The models generated will allow us to establish future sampling strategies to identify new populations of Zephyranthes species, which will contribute to increase the number of available records of occurrence. Also, these results can be compared with new investigations about climate change effect on ecological niche of Zephyranthes. These investigations will allow morphological, physiological, genetic and ecological comparisons between populations and species of Zephyranthes, which will integrate basic knowledge about this genus in Mexico in order to promote its conservation.

5. Conclusions

The models generated with MaxEnt obtained an AUC value greater than 0.86, allowing the prediction of the potential distribution of each species in Mexico. The bioclimatic variables with the greatest contribution as predictors to the distribution models were the average annual temperature, average temperature of the rainiest four-month period, average temperature of the warmest four-month period, precipitation of the rainiest period and sodium concentration (cmol L−1), which, according to the principal component analysis (PCA), explained most of the accumulated variance.
Zephyranthes concolor, Z. fosteri, Z. lindleyana, Z. longifolia, Z. morrisclintii and Z. chlorosolen are more widely distributed in the north and center of the country, while Z. brevipes, Z. carinata, Z. citrina, Z. clintiae, and Z. sessilis have a variable distribution (from high to medium-low) in central and southern Mexico. The 1376 records obtained and the analyses previously carried out for this work allowed us to determine the suitability of the habitat in which the 13 species of the genus Zephyranthes are distributed.
The species studied, endemic to Mexico, represent a small part of the great diversity that exists in the country; however, little information is known. This work shows the importance of generating knowledge of the endemic species in order to lay the foundations and provide a guideline for subsequent studies in which the agro-industrial or botanical potential of these and other taxa is made known.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ecologies5040034/s1, Supplementary S1: Occurrence records of 37 species of Zephyranthes. Supplementary S2: PCA results. Table S1: Bioclimatic and edaphic layers used for the MaxEnt modeling of each Zephyranthes species. Table S2: Area Under the Curve (AUC) value of the ROC analysis of the training and test models of 13 resulting Zephyranthes species. Table S3. Cutoff threshold for each species for the binomial test. MTSPS: Maximum Test Sensitivity Plus Specificity. Table S4. Prediction of potential species distribution area using MTSPS as cut-off threshold.

Author Contributions

Conceptualization, Z.E.R.F. and Y.L.F.P.; Data curation, Z.E.R.F. and Y.M.R.; Formal analysis, Z.E.R.F. and J.A.R.V.; Funding acquisition, Z.E.R.F.; Investigation, Z.E.R.F., Y.M.R., J.A.R.V. and Y.L.F.P.; Methodology, Z.E.R.F., Y.M.R. and J.A.R.V.; Project administration, Z.E.R.F.; Software, Z.E.R.F. and J.A.R.V.; Supervision, Y.L.F.P.; Validation, Y.M.R.; Writing—original draft, Z.E.R.F., Y.M.R., J.A.R.V. and Y.L.F.P.; Writing—review and editing, Z.E.R.F., Y.M.R., J.A.R.V. and Y.L.F.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Consejo Mexiquense de Ciencia y Tecnología through a research grant with folio ESYCA2023-1-4244.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding author.

Acknowledgments

The main author is grateful to the Consejo Mexiquense de Ciencia y Tecnologia (COMECyT) for the grant (folio ESYCA2023-1-4244) for a research stay under the program Investigadores e Investigadoras COMECyT EDOMÉX.

Conflicts of Interest

The authors declare no conflicts of interest.

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Ecologies 05 00034 g001
Figure 1. Known and potential geographic distribution of the genus Zephyranthes in Mexico. (a) Occurrence records and biogeographic regions proposed by Morrone [66]. (b) Potential distribution, created with 1376 occurrence records of 13 species of the genus. The range of colors shows habitat suitability.
Figure 1. Known and potential geographic distribution of the genus Zephyranthes in Mexico. (a) Occurrence records and biogeographic regions proposed by Morrone [66]. (b) Potential distribution, created with 1376 occurrence records of 13 species of the genus. The range of colors shows habitat suitability.
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Figure 2. Potential distribution of four species of the genus Zephyranthes. (a) Z. brevipes, (b) Z. carinata, (c) Z. chichimeca, (d) Z. chlorosolen.
Figure 2. Potential distribution of four species of the genus Zephyranthes. (a) Z. brevipes, (b) Z. carinata, (c) Z. chichimeca, (d) Z. chlorosolen.
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Figure 3. Potential distribution of four species of the genus Zephyranthes. (a) Z. citrina, (b) Z. concolor, (c) Z. drummondii, (d) Z. fosteri.
Figure 3. Potential distribution of four species of the genus Zephyranthes. (a) Z. citrina, (b) Z. concolor, (c) Z. drummondii, (d) Z. fosteri.
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Figure 4. Potential distribution of five species of the genus Zephyranthes. (a) Z. lindleyana, (b) Z. longifolia, (c) Z. minuta, (d) Z. morrisclintii, (e) Z. sessilis.
Figure 4. Potential distribution of five species of the genus Zephyranthes. (a) Z. lindleyana, (b) Z. longifolia, (c) Z. minuta, (d) Z. morrisclintii, (e) Z. sessilis.
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Table 1. List of Zephyranthes species endemic to Mexico, and number of occurrences correctly georeferenced.
Table 1. List of Zephyranthes species endemic to Mexico, and number of occurrences correctly georeferenced.
SpecieAcronymNumber of Occurrences
Zephyranthes arenicola BrandegeeZEARE6
Zephyranthes brevipes Standl.ZEBRE56
Zephyranthes carinata Herb.ZECAR77
Zephyranthes chichimeca T.M.Howard & S.OgdenZECHI14
Zephyranthes chlorosolen (Herb.) D.DiettrZECHL144
Zephyranthes citrina BakerZECIT31
Zephyranthes clintiae TraubZECLI8
Zephyranthes concolor (Lindl.) Benth. & Hook.fZECON56
Zephyranthes conzattii Greenm.ZECON1
Zephyranthes crociflora T.M.Howard & S.OgdenZECRC3
Zephyranthes drummondii D.Don in R.SweetZEDRU76
Zephyranthes fosteri TraubZEFOS716
Zephyranthes katheriniae L.B.SpencerZEKAT4
Zephyranthes latissimifolia L.B.SpencerZELAT7
Zephyranthes lindleyana Herb.ZELIN28
Zephyranthes longifolia Hemsl.ZELON54
Zephyranthes minuta (Kunth) D.Dietr.ZEMIN60
Zephyranthes morrisclintii Traub & T.M.HowardZEMOR14
Zephyranthes nelsonii Greenm.ZENEL3
Zephyranthes orellanae Carnevali, Duno & J.L.TapiaZEORE6
Zephyranthes primulina T.M.Howard & S.OgdenZEPRI1
Zephyranthes pulchella J.G.Sm.ZEPUL2
Zephyranthes sessilis Herb.ZESES51
Table 2. Environmental variables used to generate potential distribution models.
Table 2. Environmental variables used to generate potential distribution models.
AcronymDescription
BIO1Annual Mean Temperature (°C)
BIO2Mean Diurnal Range (Mean of monthly (max temp − min temp)) (°C)
BIO3Isothermality (BIO2/BIO7) x 100)
BIO4Temperature Seasonality (standard deviation * 100)
BIO5Max Temperature of Warmest Month (°C)
BIO6Min Temperature of Coldest Month (°C)
BIO7Temperature Annual Range (BIO5-BIO6)
BIO8Mean Temperature of Wettest Quarter (°C)
BIO9Mean Temperature of Driest Quarter (°C)
BIO10Mean Temperature of Warmest Quarter (°C)
BIO11Mean Temperature of Coldest Quarter (°C)
BIO12Annual Precipitation (mm)
BIO13Precipitation of Wettest Month (mm)
BIO14Precipitation of Driest Month (mm)
BIO15Precipitation Seasonality (Coefficient of Variation)
BIO16Precipitation of Wettest Quarter (mm)
BIO17Precipitation of Driest Quarter (mm)
BIO18Precipitation of Warmest Quarter (mm)
BIO19Precipitation of Coldest Quarter (mm)
SMCaCalcium (cmol L−1)
SMKPotassium (cmol L−1)
SMMgMagnesium (cmol L−1)
SMNaSodium (cmol L−1)
SMCOrgOrganic Carbon (kg m−2)
SMOMOrganic Matter (%)
SMECElectric Conductivity (dS m−1)
SMSAR Sodium Absorption Radius (%)
SMpHLogarithmic Scale of Hydrogen Ion Concentration
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Rodríguez Flores, Z.E.; Moredia Rosete, Y.; Ruiz Valencia, J.A.; Fernández Pavía, Y.L. Prediction of Environmentally Suitable Areas for Zephyranthes (Amaryllidaceae) in Mexico. Ecologies 2024, 5, 571-584. https://doi.org/10.3390/ecologies5040034

AMA Style

Rodríguez Flores ZE, Moredia Rosete Y, Ruiz Valencia JA, Fernández Pavía YL. Prediction of Environmentally Suitable Areas for Zephyranthes (Amaryllidaceae) in Mexico. Ecologies. 2024; 5(4):571-584. https://doi.org/10.3390/ecologies5040034

Chicago/Turabian Style

Rodríguez Flores, Zayner Edin, Yanet Moredia Rosete, Jesús Alejandro Ruiz Valencia, and Yolanda Leticia Fernández Pavía. 2024. "Prediction of Environmentally Suitable Areas for Zephyranthes (Amaryllidaceae) in Mexico" Ecologies 5, no. 4: 571-584. https://doi.org/10.3390/ecologies5040034

APA Style

Rodríguez Flores, Z. E., Moredia Rosete, Y., Ruiz Valencia, J. A., & Fernández Pavía, Y. L. (2024). Prediction of Environmentally Suitable Areas for Zephyranthes (Amaryllidaceae) in Mexico. Ecologies, 5(4), 571-584. https://doi.org/10.3390/ecologies5040034

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