Climatic and Evolutionary Trends in Endemic Cacti of the Chihuahuan Desert Biome: Distribution Models and Track Analyses

1. Introduction

The Chihuahuan Desert Biome (CDB) is a major ecosystem assemblage fluctuating between Interglacial (IG) and Glacial (G) phases in a present–day Glaciation Era [1,2,3]. It was established primarily over the last 8 Ma after the gradual closure of the Central American oceanic bridge [1,4,5]. The continent experienced pertinent climate changes through alterations of the warm water oceanic currents, slowing the intake of cold waters from the Antarctic into the Caribbean Sea [1,5]. This happened after regional orogenies and after new seafloors created by expansionary tectonics, where the hydrosphere can be further held [6,7], highly correlated with important geological proxies [8,9,10] and paleomagnetic evidence [6]. Some large orogenies followed up, as we will see with Laramidia, that correlate with uplifted parts of the Central American Archipelago and several mountains [1,3,5]. A significant process was the increase of humidity towards the equator and the transition of arid and semiarid bands toward the north, establishing mid–latitude arid regions [5]. Few studies delve into reconstructions of present and past climates [8,9], while none had covered track analyses for its cacti. Colonization patterns are explored along with them in correlation to best known phylogenies. Most climatologists accept that we live in an Ice Age [2,3,5], accepted by most serious climatologists, fed by atmospheric dilution and Milankovitch cycles. The iteration, which we call IGO (Glacial–Interglacial Oscillation), has seen 87 cycles, and create climate changes that in combination with soil use, and grazing, are among the drivers of cacti diversity, distribution, and evolution in the CDB [1,11,12]. Cactaceae is an amazing family containing over 1470 species, with at least 800 occuring in Mexico and the Southern USA [12]. The CDB holds over 300 species and has high levels of endemicity [13,14,15,16]. We have fossil pollen in Central Mexico dating back 16 – 51.6 Ma [17], with animals the likely agent for their arrival, allegedly from South America [18] & Appendix A.1. Since then, they moved north and west and reached the CDB some 16–20 Ma, after the rise of the Sierra Madre Oriental (SMO), which completed the rain shadow from Atlantic sources. We modeled the Species Distribution Models (SDMs) using MAXENT algorithms for the IGO and studied 75 modelable species that occur strictly inside the biome, and have enough localities, area coverage, or enough separation between groups of sites. Extremely clogged species resembling a single locality, or species with fewer than 4 sites, were not modeled but were used for richness and general perspectives. IG model came from the application of Sánchez–Santillán and García methods [19,20], while Scotese's works [21], and particular proxies from Roy–Priyadarsi [8,9,10], and clues from packrat middens [22,23,24,25], were used for selection of climatic influence zones and G modelling. Megafauna and human activities have had mostly unexplorable effects over cacti in the biome. Track analyses encompass the calculation of Croizat–inspired patterns that represent ancient biotas, involving evolutionary processes in space, time, and form [26]. Those patterns comprise the graphical integration of biodiversity into identifiable lines and points, tracks and nodes, that show estimated patterns of evolution, which were later compared with Halffter´s Cenocrons [27,28]. These explorations include the cladistic content of biology per region and were incorporated into clear methodologies that improved tests by incorporating mathematical models and digital algorithms [29]; as such, we use in this research [30]. We anticipate that the SDMs will highlight areas with the highest idoneities within the phases of the IGO, revealing potential changes in direction, area drift, size, or areal change. We also suggest that they will reveal the general colonization patterns and will moderately fit with the track and node analyses.

1.1. Objectives

Deepen into the study of the evolutionary and biogeographic patterns of endemic cacti to contribute to the general knowledge of their evolution in space, form and time, by distribution models and track analyses.

• Model the SDMs for the glacial and the interglacial phases of the IGO
• Explore the ancient biotas through track analyses: general and individual tracks & nodes
• Search for a profound understanding of the colonization and dispersal–vicariance within the IGO

1.2. Study Area

The Chihuahuan Desert Biome comprises numerous ecosystems, ranging from extreme arid zones to subhumid montane pine and fir forests [22,24,25] in its mountains. Its origin comes from the closure of the Central American sea bridge [1,4,5] and planetary expansive processes [6,7]. It is part of the North American Tectonic Plate, and was covered by deep waters for some thousands of Ma, before the water moved to new oceanic basins [6]. Reef evidence points toward ancient coastal environments [7]. The movement of the Laramidian sea also caused the Laramidian orogeny through isostatic equilibria and the decrease of the curvature angle of the planet's surface. The lower parts broke open, and the upper parts collapsed toward each other, generating gigantic compression forces that gave rise to its younger mountain range (SMO), which effectively isolated the region from the Gulf of Mexico, creating a much stronger rain shadow [10]. The Sierra Madre Occidental (SMOCC) and the Transmexican Volcanic Belt (TMVB) were already stopping humidity from the Pacific Ocean [8,9,10]. Those two mountain chains were not very different from the present, but the SMO rose mainly after the Chicxulub Impact Crater and the antipode Deccan Traps. During some 50 Ma, volcanic and tectonic activity continued, though plummeting in force [6,7]. Upper parts saw eruptive events and lower parts permeated by magmatic dykes. This topographic complex was uplifted over 3000 m from its original conformation while the water was emptied. The last 18 – 8 Ma saw the closure of the bridge, increased aridification and the establishment of the IGO. Several regionalizations had been proposed.The most natural had been obtained after endemic cacti (see Figure 13.1 in [16]), in which a Main, an East, and a Meridional Subprovinces are recognized. Sierra Transversal de Parras (STP) also divides the CDB roughly into a northern and a southern area. The CDB is now the largest desert environment in North America and the largest temperate desert in Mexico, covering an area of over 508,000 Km² from the central Mexican plateau and the Queretaro–Hidalgo central valleys, up to the southern region of Texas, New Mexico, and even the tip of Arizona [13,14,31,32]. It traverses 11 Mexican states and goes from higher elevations in the south, toward lower elevations in most parts of the north. We shall understand that most of the recent evolution of the biome as a desertic complex occurred within the IGO [10,32]. That topography has changed little in the last 30 Ma, making cycles of colder and warmer climatic conditions a major driver of the species' evolution on a stable topography. Some 3500 plant species have been described so far, and a wide variety of microfauna and medium-sized fauna survived the arrival of humans some 23.5 Ka.

It was also affected by a major asteroid hit that impacted the northernmost area some 49 ka, and several reiterative fluctuations like the 12.7 ka Younger Dryas and abundant Heinrich events, making cold return along the IGO [33,34]. Climate oscillations, drifting from the G to the IG phases, saw changes up to 8°C, and a much wetter conditions for northern lands during the G, where a large amount of rain descends from the North America directly into the CDB, turning south while colliding with the massive ice shields and the Rocky Mountains under lower and cooler atmosphere´ conditions [4,10,32,34]. The CDB has few permanent rivers and a dozen of glacial lakes, mostly dried during the IGs. Canyons and river basins seem to be related to cacti dispersal and protection, making for IGO´s Refugia.

2. Materials and Methods

2.1. Climatological Layers & Species Distribution Models

The CDB has been regarded as a xerophytic complex of ecosystems that exists inside a substantial rain shadow created by the massive mountains of SMOCC, SMO, and TMVB [10,35,36]. Nowadays, it is considered a Biogeographical Province, after regionalization studies by Morrone and colleagues [28,37]. There are few climatological studies, and most charts were advanced by the mid–1970s by people in the INEGI (Appendix A.3 & SM). To understand more deeply the correlations of the plants, particularly cacti, within the CDB, we needed a solid base. One that does not have the low resolution of the Bioclimatic variables available online, such as Bioclim and Worldclim, obtained mostly from recent satellite information that include serious biases after the present–day thermal peak, a normal pattern along paleoclimatological studies, which might include a minor contribution from anthropogenic sources. A comprehensive Numerical Database was built after methods of Mexican Climatology pioneers Enriqueta García [19] and Norma Sánchez–Santillán [20], which deeply explored around 50,000 selected entries from 60 usable stations within the region, during 1981–2010 (National Meteorological Service, Appendix A.3 & SM). The complex models and their equations are to the subject of a forthcoming contribution and inspired several works, from which we just use the main layers obtained by Co–Kriging tools using elevation after a merged DEM from 39 INEGI´ DEM sources, as the main predictor for the interpolations. Every digital layer in the project was plotted within an hexaquadratic area that increases by 5 % the area toward the borders at all sides, which assures that the complete CDB area is effectively included. Layers were clipped by this increased extension. Information was worked in MS Excel, R, and QGIS / SIG (3.28.3–Firenze). Paleobotanical reconstructions and geological proxies explored by Van Devender [24,25], Betancourt [22] and Roy–Priyadarsi [8,9,10] allowed a numerical transformation and further precise Co–Kriging. These allow climatic regionalization into influence zones, and P/T (water availability) and thermal gradients were applied to obtain the best approximation to the reality of the G condition. The gradients , representing thermal change every 100 m, cross the climatic influence areas by their major axis and are directly related to the precipitation change through the P/T index, by the following formula (1):

$$P´=\left({\displaystyle \frac{P}{T´}}\right)xT$$

(1)

Where: P´ = Precipitation at the locality, P = Precipitation average for stations,

T = average mean temperature for the stations, and

T´ = mean temperature calculated for the locality

Gradients were directly applied to obtain thermal anomalies at the localities inside each zone and Formula 1 revealed water availability and precipitation best approximations. A total of 2015 localities were modeled following the gradients for each zone, and 11 anomalies were predicted: Mean normal temperatures, maximum mean temperatures, maximum extreme temperatures, mean minimum temperatures, extreme daily minimum temperatures, year normal precipitation, month normal precipitation, and days with: Fog, hail, storm, and rain. Numerical models are shared in summary in SM, (climatic types for each specimen correspond to keys in Appendix A.4). Co–Kriging detailed or fine interpolated layers were created: Seven for the IG part, and five for the G part (Appendix A.3 & SM). This is a powerful and comprehensive exploration of real climatologies as best one could assess, and allowed us to explore correlation trends within the species, and much more importantly, model the IGO SDMs with high precision and correspondence to understand changes within the phases. Extensive revisions of this fine models had allowed research on quantitative Refugia, environmental correlations, rarity and climatological specialization in turn for other works, and hereby, the exploration of the correspondence between idoneities and track analyses for the strictly endemic cacti in the CDB. Co–Kriging searching tools were limited to 1° geographic with square dimensions of 0.01° geographic and 30 aggregations. Several available information layers were used to construct the figures of this work, including INEGI city and road shapefiles, USA/USGS/NOAA shapefiles, and a visualization layer fitting available in QGIS, such as Google Terrain, Google Satellite, and World Countries Borderlines. Geographical maps and the Coordinate Reference System (CRS) of the project were projected after WGS84 ellipsoid (World Geodetic System 1984, EPSG:4326. Ellipsoid: major semiax = 6378137.0 m, flattening = 1/298.257223563). Illustrative maps contain both the geographical degree system and the lines for the Universal Transverse Mercator (UTM). ASCII files used for MAXENT SDMs for the IGO are shared in the SM, additional materials are available by request. MAXENT (Maximum Entropy Modeling Alforithm), developed by the Center for Biodiversity and Conservation at the American Museum of Natural History (AMNH) under the guidance of Steven Phillips and other AMNH´ colleagues [Appendix A.2], consist of a machine–learning algorithm that allows the iteration of a species known points through a distribution area for the selection of environmental features within disposable raster layers (Appendix A.3 & SM), to create suitability or idoneity maps where the species might thrive best (https://biodiversityinformatics.amnh.org/open_source/maxent/). We used routines developed by Joshua Banta and colleagues (University of Texas at Tyler; https://sites.google.com/site/thebantalab/home) in an R script to initially test for the most adequate models to use in each case, the number of replicates, and the regularization multipliers (Appendix B.1 & SM). Cross–validation and particular determined models–regularization multipliers were used with 10,000 background points for modeling 75 species in the IG and G phases. In each case, the relevant climatic layers were used to plot idoneities, and SM. The SDMs were later used to create combined idoneity maps for the IG, the G, and the IGO. They were also tested, containing just the climatic specialists. Raster Calculator of QGIS was used to perform the combinations and particular analyses of the information. 75 SDMs for the IGO were compared in order to determine general trends in size, position and drift over time. MAXENT were used due to their robustness in handling presence-only data and their widespread application in biogeographical research, we prefer such scope over alternative models because it has proved strong value and good results beyond particular or ecological-niche-oriented algorithms that are focused on short term climatological variations. Cacti are long lived plants with decades to hundreds of years life spans, which also provide confidence on using our mean variables for the IG and G phases of the IGO. The R routine procedures allowed the identification of the most appropriate model configurations prior to final implementation (SM table). Although we do not aim to compare alternative modeling algorithms, particular care was taken to ensure that model complexity and performance were adequately controlled to minimize overfitting and maximize interpretability of long-term and wide-scale climatic suitability patterns, that under our high quality data approach probabilities.

2.2. Track Analyses and Evolutionary Correlations

Analyses tools were used to create intersections of localities (2015) and specimen registers (3719), filtering the original 4070 specimens and focusing in the 3719 specimens from the modelable species with corroborated georreferences. The intersections allow the creation of SIG–based occurrence tables and plots that reveal the structure of alpha diversity and suggest a noticeable beta diversity, as determined in several documents to date [11]. Endemism is evaluated on the possibility that the species were endemic to one, two or the three subprovinces sensu Hernández & Gómez–Hinostrosa [16], whereas a larger occurrence makes for a lower Endemism value. Track analyses can be mapped as free-hand made integrations or by using digital algorithms. Tests were performed using Parsimony Analysis of Endemism, but the matrices were low in occurrences for obtaining a clear perspective on the tracks and nodes. Thus, we decided to use a new integrative program called PANBIOTRACKS, designed by Carlos Castillo and already tested for several taxa [30]. The program involves R algorithms that find the nearest correlations among individual tracks of a species in order to create internal generalized tracks, by comparing the lengths and the angles in which each individual track appears over the space. It has also subroutines that are able to correlate the highest densities of tracks approaching each other to deduce main nodes. The tracks and nodes represent the ancient biotas suggested by their present–day remains or manifestations. We studied general tracks and nodes, and make selections of species that possess wide and limited forms of dispersal to have a set of different comparable graphic results that could explain particular biological trends. Cacti, specially Opuntioideae but also Cacteae, show a noticeable level of horizontal translocation of loci, by means of fertile hybridization and molecular vectors. This is probably the case for numerous groups of plants and almost every simple life form in the planet, which might oppose traditional strict views of dichotomic evolutionary trends and suggest nets of life for plants, rather than simple dichotomous trees. Our best try was to integrate the best-resolved phylogenies (Appendix A.1), and the tracks for the known chronologies to compare the species with particular and general tracks and nodes. Matrices were also built after the occurrence of all tracks and nodes over a ¼ geographical degree grid, which might also be informative of the number of overlappings among the individual and generalized patterns. Finally, sizes and positions of the overall idoneities for each of the 75 modelable species were compared by general overlapping of the SDMs in order to detect the trends of evolutionary change, thus being able to suggest lines of vicariance, dispersal and reduction within their potential distributions. We consider that doing so is our best guess, since independent and individual events of vicariance or dispersal are almost untracktable. Species distributions contracting the most are thought to be a signal of potential extinction threat within the IGO.

2.3. Hypotheses Testing

We propose that overlapping the overall idoneities of species with the overall tracks and nodes for them will reveal substantial coincidences between them. We also suppose that widely distributed species will have long reach and wide tracks, and that limited distributed species will have limited tracks and much more complex ramifications and nodes than the widely distributed ones. We advanced overlappings of the idoneities, tracks and nodes to test this ideas graphically, where analyses pinpoint toward colonization of the environments allegedly coming from its South–Eastern tip. Chronologies were included.

3. Results and Discussions

A total of 119 endemic cacti species were surveyed, and 4503 specimens were revised regarding taxonomic status clarity and geopositioning precision, from which 17.4 % were eliminated after gaps. Thus, 3719 specimens corresponding to 2015 confirmed localities were carefully assessed, and focus was given to 75 species, which occur at least over 85 % of the time inside the CDB, and 44 species were represented as points within the GIS, and are not useful for modeling or track analyses. These species happen on 126 ¼° squares within the CDB. We recognized nine chronologically integrated clades from the eight best–resolved phylogenies (Appendix A.1) and superimposed their SDMs for the IGO (Figure 1a), identifying 37 potential dispersal events, 59 potential vicariance events, and up to 22 potential extinction risks. These numbers are not close ones; instead, they are trends or drifts deduced from changes in idoneity in the IGO models. Most common species are Mammillaria formosa, Echinocereus pentalophus, Ferocactus pilosus, Opuntia microdasys, Ferocactus hamatacanthus, Ariocarpus retusus, Mammillaria compressa, Echinocereus enneacanthus, and Thelocactus bicolor. A total of 44 microareal non–modelable species make 119 endemics.

3.1. Species Distribution Models

Endemism is naturally correlated with the greater area of the Main Subprovince, covering most of the CDB. Nevertheless, it is complemented with the Meridional Subprovince (Table 1). Meridional Subprovince attains noticeable occurrences of Lophophora diffusa, Opuntia pachyrrhiza, and Turbinicarpus pseudomacrochele, despite that they could be found in fewer localities otherwise. We present each species idoneities on the SDMs in the SM, where plots and information on them is made accessible. Visual general comparisons allowed the detection of the patterns pinpointed before, which are also summarized in Table 1, where values from 0–1 concerning endemism and climatic specialization are shown. A cumulative species idoneity map for the IGO is presented in Figure 1a, whereas Figure 1b and 1c show the idoneities for species preferring temperate climates (IG) and semi–arid climates (G) for wich we have complete detailed matrices by localities (SM, Appendixes B.3 & B.4). The table summarize main phase for wider distributions for the species, and contains the general trend observed in the plots, followed by the potential change trends for the distributions, and the processes being suggested by those changes. We think that it is impossible to track every evolutionary process and it is likely that such idea will remain impossible forever since we have very small information of just present–day survivors of a long evolutionary history. So we do not intend to reconstruct particular vicariant or dispersal events, but rather to focus on what the change in the distributions could actually tell us for the last part of the IGO. We present the idoneities also in a chronological order looking for clues on their fitness over time and colonization sources. Composite Figure 2 reveals the patterns of colonization and radiation in the CDB, and is in agreement with the track analyses and evolutionary phylogenetic correlations that we present. Idoneities for Age Clades defined after the best-resolved phylogenies (SM) are clipped by the known Areas of Occupancies. A potential extinction gap is easily identified in Figure 1a, perhaps after increasing intensity of the glacial phases aridity or extreme values.

Dispersal methods can vary from the hyperdispersal of some Opuntia to the scarcity and specific correlations of small globose species, like Aztekium, Obregonia, Ariocarpus, and many Coryphantha and Mammillaria. Larger species often rely deeply on fruit succulence for far–distance dispersal by extinct megafauna, present–day mid–fauna, and have even been modeled after human uses and distinct traditions, causing range distribution alteration [18,31,32]. Some cacti had been definitively introduced by humans from one region to another, while most strictly endemics fall far from this trend. It is possible that distributions of Opuntia microdasys and O. rufida, Lophophora williamsii, and even Neobuxbaumia, as well as some Echinocereus and Ferocactus pilosus, might have been altered by human management after their common use in diet or construction. The first three species are outstanding in their responses to human–induced changes and were surely manipulated since the earliest arrival of ancient peoples. A Maximal Idoneity Area (MAXI) fulfills several needs to quantify the abundance of endemic cacti through the IGO and the overlapping of these areal calculations with track and node analyses, with 19 species on a 75% probavbility occurrence (Dotted area, Figures). A general 0.27 idoneity threshold was used for the general IGO cacti idoneity after analyses of the natural breaks in the histogram of the point cloud. This was found to represent the presence of at least 19 species of species found to overlap with 90 % of the generalized tracks, 82 % of overall nodes, and represents 72.43 % of all revised specimens (3719 vouchers) in just 24.7 % of Hernández & Gómez–Hinostrosa Regionalization [16], or just 15.7 % of the hexaquadratic area used for this study. This means that about 84% of the CDB area has low richness compared to the latter, which contains most biodiversity, highlighting the evolutionary connections.

3.2. Track Analyses and Evolutionary Correlations

Track and nodes´ studies focus on searching tracks joining specific localities for species, ordered in a parsimonious way. Those tracks are used to obtain internal generalized tracks for endemic cacti species in general, while we also performed track and node analyses for species with widespread and limited dispersal. We see these tracks and nodes (Figure 3 and Figure 4) as a window into species interconnectivity and a potential explanation of their evolutionary trends, when the orientation is inferred from changes in the predicted idoneities for the IGO. The general orientation of all the tracks is SE–NW, and several tracks and nodes point into the recognized SE-NW direction of the potential colonization, which could be appreciated in Figures and was counted through the 136 ¼° squares with cacti, confirming the following statements (Table 2). We find major tracks going from the Meztitlán and Tolantongo Gorges, in connection with the Mezquital Valley, communicating with central SLP valleys [32]. The general tracks (Figure 3) point toward a dense interaction with major gorges and valleys of the Zimapán–Tolimán–Cadereyta region, and into the plains of SLP. El Huizache and Mier y Noriega, widely known for their incomparable richness and diversity, are quite in the middle of several tracks and nodes, and they correlate directly with several eastern Tamaulipecan valleys and mountains, both in the Main and in the Eastern Subprovinces. Seemingly, tracks go north by the side of the SMO and through the valleys between the middle SLP ranges and Real de Catorce range. The eastern division rises up toward the STP and intermixes thoroughly with SMO, while the western patterns go directly upon the Mazapil–Saltillo region, crossing the STP, creating two parallel tracks toward the southern and northern slopes of the STP. A significant track crosses Coahuila and connects several mountain ranges and dry valleys into interesting routes for dispersal and even for some more vicariance. Sierra La Paila and the Valley of Cuatro Ciénegas join some other valleys, such as El Hundido and Anteojo, in a complicated road for cacti toward the northern areas. El Burro and el Nido ranges, Maderas del Carmen, and the Big Bend National Park region highlight the Northern areas. Some tracks follow northwest near the Rio Grande basin, while a minor one diverges toward the Bolsón de Mapimí through the southern edge of Laguna de Mayrán basin, a large glacial lake that mostly dries up during the IGs. Analyses for species with high reaches (Figure 2 and Figure 4a), those that can travel in the stomach of mid fauna or proxies for the extinct megafauna [18], and that sometimes even disperse through segments – like Opuntia – look straightforward and far reaching, simple and not very dichotomized. In contrast, tracks for scarcely propagated species depending on minor fauna, wind, and water upon local dispersal, are tremendously intricate, not far–reaching, and often intermingled (Figure 4b). These tracks extend into mountains and mountain valleys thoroughly, and nodes for such species rise to 45, while far–reaching species have just six nodes. We propose that a closer look at the individual tracks might reveal something for future studies, and understand that what we are looking at is a complex intermix of dispersal and vicariant events over the IGO, which is roughly explored so far.

Climatologically, we notice four relevant effects within the IGO: SMO Oceanic – corresponds to climates moderated by a reasonable Atlantic influence [8,9,33] through north winds and occasional humid intromissions, Northern Areas – mostly dry during the IGs, they see the most significant changes on humidity and water availability in comparison between the IG and the G phases–conditions, SMO SMOCC – High Pressures over the dry part of the Sierras is usually quite stable even in the G phases, but always preserve somewhat wet and cool environments on the high parts, and South Highlands – elevated mountains and volcanoes toward the Meridional Subprovince are well known for their temperate woods, mesic and even cool environments throughout the IGO. A numerical transformation (0–1) from lower to higher effects is provided in Table 2, where the mean thermal and precipitation changes (x times–folds) from the current IG conditions toward the Mean G conditions can be appreciated. Means refer to species–averaged anomalies, while extreme temperatures are explored in their graphical form in the climatological and SDMs sections. Significant climatic changes override the whole biome, with a 4–7–fold increase in humidity from the north, since massive ice fields and the Rocky Mountains – under a thinner, cooler, and relatively drier general atmosphere – make winds turn southward directly into Mexico during the G phases. However most cacti receive smaller changes on P/T as seen in Table 2. The Northern Areas receive thus the significant climate change in relation with their IG well known aridity, but climatic and vegetation floors change widely, between 6 and 12° C and up to 5 times the P/T indexes we will explore further. Most tracks and nodes occur in low–change areas, as large water availability may involve significant transformations of vegetation communities, potentially affecting climate–vulnerable cacti. As we will see later, several species tolerate lower temperatures and even increased humidity without major problems, and many others even prefer those conditions in mesic–temperate lands during the IG phases. In contrast, some other species prefer aridity and benefit from particular mountain shadows and southern protection from the humid north during the glacial periods. We suggest dispersal is critical for widely propagated species. Still, they are the least among strict endemics of the CDB, whereas evolutionary trends indicating that the species mainly came from the SE tip of the biome are clear. We think that plant rarity and high climatic specialization speak to the dominance of allopatric speciation and align with track analyses.

The eight best phylogenies (Appendix A.1) probably explain the associations among cacti, and were also used to group them by age–clades as best as possible. As seen in the composite Figure 2, SDMs of specific species are congruent with phylogenetic expectations and pinpoint nine cacti minimal–age clades for the CDB, based on the best-resolved phylogenies to date. Tracks and nodes corroborate the patterns shown in the figures and reveal additional correlations within the phylogenetic clades. Cacti arrived mainly or uniquely from the SE tip, and clades I and II rapidly colonized most of the central and northern areas, first passing through the Meridional Subprovince. Astrophytum and Sclerocactus were shortly followed by Opuntioids, perhaps colonizing environments and allopathically creating species some 30 – 16 Ma. Even Coahuila and the central–north diverse regions were early colonized and populated, although it seems that species remained in big valleys and plains, to later evolve into the thin ravines and valleys in the buttresses of SMO and the transversal ranges. Clades III to V evolved even some eight Ma, or somewhat later, coinciding with the effective climatic formation of the CDB´s IGO. They include mostly Mammillaria, a broad genus with the most considerable species richness in Cacteae. Many such species, together with Coryphantha, support elevated humidity and often occur among cold– and wet–preferring species. Later, Clades VI and VII developed further into the ravines and isolated plains, colonizing new environments. Clades VIII and IX were the last to evolve and appear to have existed for less than 5 Ma. They primarily include the recently evolved Echinocereeae and small to large species that do not often support freezing temperatures and remain excluded from very high places and northerly lands. However, even among them, we can find species that support extreme cold and humidity. Opuntioideae are the only fossil pollen confirmed so far from the surroundings of the CDB (Ramírez–Arriaga et al. 2017; TCV, 16 Ma), but other samples are known from southern Oaxaca that exceed 50 Ma [17]. We can be sure that at least Opuntia arrived early, while minimal ages for different branches and specific species are inferred from the molecular clocks, where proxies serve as indicators. There are some interesting manuscripts on the issue, and perhaps Arakaki et al. (2011) and Silva et al. (2018) gave a good look into evolutionary times. However, we adjusted Arakaki´s timelines considering a 34.7 % subestimation derived from the tangible evidence near the CDB and included the adjusted molecular clocks in the species that can be tracked down.

As exposed in the main tracks, and following the SDMs of the clades (Figure 2), there are mostly entrance patterns from the SE tip of the desert and a series of complex dispersal and vicariant events, perhaps counted in the hundreds, that also might have included some extinctions in the relatively recent geological time. SDMs, and their drift and change are extracted by comparing the G and IG best models (SM). We were able to suggest potential states favoring dispersal and vicariance, although the distinct events could not be easily reconstructed or even perceived. We also pinpoint species with a significant risk of extinction within the last IGO cycle, and the present–day species that would receive additional protection after these discoveries. Twenty–two species show a larger ecological niche for the IG conditions, while 17 species have equivalent species distributions in the overall IGO (Table 1). Thirty–six species have a greater distributions during the G phase, highlighting the importance of both phases in the evolution of cacti. Some 37 cases of potential dispersal and 59 of potential vicariance were highlighted for the last transition from G to IG conditions (Table 1). In contrast, they might imply more specific processes on the move. The extinction threats refer to potential risks after substantial reductions in identity areas, not to direct measures as reported by Goettsch et al. (2015) in their assessment of the conservation status of the family [11]. This does not necessarily imply that the species are currently on the brink of extinction, but it may help improve IUCN Red List evaluations and propose future biome conservation schemes. There are twelve species potentially drifting their distributions toward the center, five toward the center–east, two toward the center–north, three toward the center–south, six toward the center–west, seventeen equally distributed, 10 toward the northwest, five toward the west, and several other intermingled cases. Twenty–two species contracted their suitability areas, 34 species diverged in their distributions, and 16 species remained the same during the last fluctuation. Coryphantha werdermannii, Homalocephala parryi, and Mammillaria moelleriana noticeably expanded their suitability area, probably increasing through this phenomenon into new dispersal events [27]. We suggest that species that contract their SDMs and have limited ways of dispersal could be at most risk. However, that could depend on varied threats and the current state of land use, therefore conservation improvements require much more studies.

3.3. Hypothesis Evaluations

We see that there is actual overlap between general, wide–dispersed, and limited–dispersed species' tracks, with higher idoneities calculated for the IGO. There is also a strong pattern showing that the western side of SMO is the most important idoneity–track superposition, and that is explained after the combined protection effects and the rain shadow provided by this longitudinal range. Its western derivation through the STP divides the CDB into two parts: A northern arid area during the IG and a wet area during the G that limits cacti survival, and a southern area that extends even towards the Eastern and Meridional Subprovinces, where larger idoneities are found, and Refugia are likely for the IGO. Widely distributed species indeed met wide and long tracks, and limited species also had limited, very complex anastomosed and intricate tracks, thus corroborating our hypotheses. The southeastern tip also correlates with what we perceive as the colonization channel for the CDB, through the valleys of Meztitlán, Tolantongo, and Mezquital, which connect the biome with Central Mexican Valleys, TCV, and even the Balsas Basin towards the S–SW.

4. Conclusions

Endemic cacti provide a window for present and past exploration of the CDB and have revealed interesting patterns regarding their distribution (SDMs) and their evolutionary trends. Cacti undoubtedly entered the CDB area through the southeastern tip, probably crossing several central Mexican temperate valleys more than once, and then colonizing the Meztitlán and Tolantongo Gorges, passing to the Mezquital Valley and dispersing all over the SLP valleys towards Tamaulipas to the east, and towards Zacatecas and Coahuila to the north and northwest. Astrophytum, Sclerocactus, and Opuntia dispersed first, while Coryphantha, Mammillaria, and Lophophora probably dispersed and radiated later. It´s even possible that Escobaria, Lophophora, Obregonia, Pelecyphora, and Neolloydia radiated within the very CDB during well–established IGO variable conditions. The same could be said, for younger ages, for Ariocarpus, Epithelantha, Thelocactus, and Turbinicarpus, to a certain extent. The last genera present new taxonomic challenges because they appear polyphyletic. However, horizontal transfers within Cacteae are significant and potentially affect Mammillaria and Coryphantha. Opuntia is the largest genus in Mexico and undoubtedly contains high amounts of horizontal gene transfer via hybridization, virus vectors, and even gardening practices.

However, the strictly endemic species considered here are not widely commercially used, serving mostly as livestock forage, and perhaps are less affected than other utilitarian species. Hundreds of dispersal and vicariant events might had been involved in the evolution of present–day cacti of the CDB, which might likely reveal unexplorable in detail. Still, we can deduce the number of species decreasing their distributions from the last G to the present IG [32]. Around 23 % of the species did not substantially change their suitability during the last episode of IGO, while many others either reduced or increased their potential distributions, perhaps in relation to IGO´s Refugia. Diversity and idoneity is higher in the SMO's central squares of Huizache, Mier y Noriega, and the Tamaulipecan valleys. We also have some rich areas in the Meridional Subprovince, and even around Mazapil´s square, towards Cuatro Ciénegas and the Maderas del Carmen–El Nido–Cañón de Santa Elena–Big Bend areas. Evolutionary patterns concerning the relevance of central SLP valleys, the Tamaulipecan valleys, and the Queretaro–Hidalgo valleys are undebatable. We think that this study pinpointed the general patterns of colonization, vicariance and distribution fluctuation on the correct scenario of IGO effects, and correspond well with a IGO development following the decreasing power of Central America´s oceanic currents and the drift of deserts to higher latitudes. Cacti also experienced gradual change in mobility forms through extinction of mid–fauna and megafauna. They arrived quite early from the south in the stomachs or on the hair and feathers of animals, and later traveled on herbivorous large mammals that eventually became extinct as a combination of human pressures and intense environmental change. Cacti exhibit incredible resilience and persist in fluctuating distributions, serving as a significant element of the CDB´s floristic composition. LGM is suspected to be a good estimation of G conditions, and the present–day climate a nice view of a mean IG. Tracks and nodes widely coincides with the suitability obtained for the endemic cacti through the IGO, because many patterns occur in the MAXI, including generalized tracks and several types of internal correlation nodes, sensu Escalante. About 90 % of total tracks and over 80 % of overall nodes are contained inside this relatively small area, covering around 24 % of CDB´s sensu Hernández (122,000 km²) [16]. It also contains many species that are high climatic specialists. We recognize that water availability is not the only causation factor behind the development of significant drifts in vegetation, thus not neccesarily implying giant grasslands or forest–covered transitions in all parts of the CDB [32,38]. Results show that several G–temperate loving species refuge in mountain tops and protected valleys, with lower temperatures and somewhat moister conditions. Considering cacti distributions and evolution is very important for improving our comprehension of the CDB, and most likely needed for the creation of sound conservation proposals [11,13,14,31]. Tracks clearly follow the mountain´s rain shadow and the highest idoneities and richness in both phases of the IGO. They also show interesting trends toward overlapping species idoneities, that could almost be taken by probabilities after data quality. Their patterns correlate with those found in the SMO [39]. Highly dispersed species show long and more simple tracks, while propagation–limited species are indeed intricate and complex, and much more constricted to ranges and valleys in the Main and Meridional Subprovinces of the Grand Biome. Nodes are informative, but could vary much more than the tracks. We found correlative nodes among main tracks and strongly suggest that the inter–province or inter–region nodes, sensu Morrone, are to be found within the SE tip toward the TMVB and the central valleys of Mexico and the Balsas Depression, and toward the NW tip concerning the Madrean Region relating the CDB to the Sonoran Desert. Although distinct vicariance and dispersal events are almost impossible to explore and understand, being the evidence limited and mostly erased from the face of the Earth other than heritage possibilities, we demonstrate that SDMs can be compared to suggest change patterns along the IGO. We can also measure the overall occurrence of tracks and nodes over space in order to pin–point relevant areas. On an expanding planet, atmospheric dilution is the main driver of aridity and desert growth, favoring arid-adapted species. Cacti surely will have a promising and long-term future in that major trend.

Appendix A.1. Most Complete Phylogenetic Reconstructions

[a] Arakaki, M., Christin, P. A., Nyffeler, R., Lendel, A., Eggli, U., Ogburn, R. M., Spriggs, E., Moore, M. J., Edwards, E. J. (2011). Contemporaneous and recent radiations of the world's major succulent plant lineages. Proceedings of the National Academy of Sciences, 108(20): 8379 - 8384. https://doi.org/10.1073/pnas.1100628108

[b] Bárcenas, Rolando T.. (2016). A molecular phylogenetic approach to the systematics of Cylindropuntieae (Opuntioideae, Cactaceae) Cladistics. 32, 4: 351-359. https://doi.org/10.1111/cla.12135

[c] Bárcenas, Rolando T.; Yesson, Chris; Hawkins, Julie A.. (2011). Molecular systematics of the Cactaceae. Cladistics. 27, 5: 470-489. https://doi.org/10.1111/j.1096-0031.2011.00350.x

[d] Guerrero, Pablo C; Majure, Lucas C; Cornejo-Romero, Amelia; Hernández-Hernández, Tania. (2019). Phylogenetic Relationships and Evolutionary Trends in the Cactus Family. Journal of Heredity. 110, 1: 44287. https://doi.org/10.1093/jhered/esy064

[e] Hernandez-Hernandez, T.; Hernandez, H. M.; De-Nova, J. A.; Puente, R.; Eguiarte, L. E.; Magallon, S.. (2011). Phylogenetic relationships and evolution of growth form in Cactaceae (Caryophyllales, Eudicotyledoneae) American Journal of Botany. 98, 1: 44-61. https://doi.org/10.3732/ajb.1000129

[f] Sánchez, Daniel; Vázquez-Benítez, Balbina; Vázquez-Sánchez, Monserrat; Aquino, David; Arias, Salvador. (2022). Phylogenetic relationships in Coryphantha and implications on Pelecyphora and Escobaria (Cacteae, Cactoideae, Cactaceae) PhytoKeys. 188, : 115-165. https://doi.org/10.3897/phytokeys.188.75739

[g] Vázquez-Lobo, Alejandra; Morales, Gisela Aguilar; Arias, Salvador; Golubov, Jordan; Hernández-Hernández, Tania; Mandujano, María C.. (2016). Phylogeny and Biogeographic History of <I>Astrophytum</I> (Cactaceae) Systematic Botany. 40, 4: 1022-1030. https://doi.org/10.1600/036364415X690094

[h] Vázquez-sánchez, Monserrat; Sánchez, Daniel; Terrazas, Teresa; De La Rosa-Tilapa, Alejandro; Arias, Salvador. (2019). Polyphyly of the iconic cactus genus Turbinicarpus (Cactaceae) and its generic circumscription. Botanical Journal of the Linnean Society. 190, 4: 405-420. https://doi.org/10.1093/botlinnean/boz027

[i] Vázquez-Sánchez, Monserrat; Terrazas, Teresa; Arias, Salvador; Ochoterena, Helga. (2013). Molecular phylogeny, origin and taxonomic implications of the tribe Cacteae (Cactaceae) Systematics and Biodiversity. 11, 1: 103-116. https://doi.org/10.1080/14772000.2013.775191

[j] Wilson, J. S., Pitts, J. P. (2012). Identifying Pleistocene refugia in North American cold deserts using phylogeographic analyses and ecological niche modeling of Polistes biglumis (Hymenoptera: Vespidae). Biological Journal of the Linnean Society, 105(3): 515 - 529. https://doi.org/10.1111/j.1095-8312.2011.01812.x

Appendix A.2. MAXENT & SDMs Background-Methodological Bibliography

[a] Phillips, S. J., Anderson, R. P., & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 2006. 190, 3–4: 231–259 https://doi.org/10.1016/j.ecolmodel.2005.03.026

[b] Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., & Yates, C. J. A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 2011. 17, 1: 43–57 https://doi.org/10.1111/j.1472-4642.2010.00725.x

[c] Merow C., Smith M.J., & Silander J.A. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography, 2013. 36, 1058–1069 https://doi.org/10.1111/j.1600-0587.2013.07872.x

[d] A. Townsend Peterson, Jorge Soberón, Richard G. Pearson, Roger P. Anderson, Enrique Martínez-Meyer, Miguel Nakamura, & Miguel Bastos Araújo. Ecological niches and geographic distributions. Princeton University Press. 2011. 328 https://www.researchgate.net/profile/Andrew-Peterson-11/publication/345684146_Ecological_Niches_and_Geographic_Distributions_MPB-49/links/5fc0170a458515b79776cb45/Ecological-Niches-and-Geographic-Distributions-MPB-49.pdf?utm_source=chatgpt.com

[e] Kass, J. M., et al. ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions. Methods in Ecology and Evolution, 2021. 12, 1602–1608 https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13628

Appendix A.3. Selected List of QGIS Layers Consulted or Created Along the Project, Available by Request.* See Also S.M.

[i] Brailovsky-Signoret, D. (2024-2026). Capa compuesta IG_Climate: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\IG_Climate.tif.

[ii] Brailovsky-Signoret, D. (2024-2026).Capa compuesta IGPrec: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\IG_Prec.tif.

[iii] Brailovsky-Signoret, D. (2024-2026).Capa compuesta IGPT: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\IG_GPT.tif.

[iv] Brailovsky-Signoret, D. (2024-2026).Capa compuesta IGdailymin: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\IG_ dailymin.tif.

[v] Brailovsky-Signoret, D. (2024-2026).Capa compuesta IGMeanT: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\IG_MeanT.tif.

[vi] Brailovsky-Signoret, D. (2024-2026).Capa compuesta G_Climate: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_Climate.tif.

[vii] Brailovsky-Signoret, D. (2024-2026).Capa compuesta GPrec: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_Prec.tif.

[viii] Brailovsky-Signoret, D. (2024-2026).Capa compuesta GPT: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_GPT.tif.

[ix] Brailovsky-Signoret, D. (2024-2026).Capa compuesta Gdailymin: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_ dailymin.tif.

[x] Brailovsky-Signoret, D. (2024-2026).Capa compuesta GMeanT: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_MeanT.tif.

[xi] Brailovsky-Signoret, D. (2024-2026).Capa compuesta GMminT: raster climático modelado para el Desierto Chihuahuense [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\MODELLED LAYERS\G_MminT.tif.

[xii] Brailovsky-Signoret, D. (2025-2026).IDW_finedetal_G_REFUGIA_i: raster interpolado de refugia climáticos potenciales [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\IDW_finedetal_IG_REFUGIA_i.tif.

[xiii] Brailovsky-Signoret, D. (2025-2026).IDW_finedetal_IG_REFUGIA_i: raster interpolado de refugia climáticos potenciales [Archivo GeoTIFF, resolución 0.01°].D:\DATACACTI\IDW_finedetal_IG_REFUGIA_i.tif.

[xiv] Brailovsky-Signoret, D. & Hernández (2026).IG_REFUGIA_TEMPERATE_CONTOURS: curvas de nivel de refugia climáticos en zonas templadas. D:\DATACACTI\G_REFUGIA_SEMIARIDAS_CONTOURS.shp.

[xv] Brailovsky-Signoret, D. & Hernández (2026). G_REFUGIA_SEMIARID_CONTOURS: curvas de nivel de refugia climáticos en zonas semiáridas.D:\DATACACTI\G_REFUGIA_SEMIARIDAS_CONTOURS.shp.

[xvi] Brailovsky-Signoret, D. & Hernández (2026). Climatic & Cacti Database for SMN Climatology 1981-2010. IG Reconstruction.

[xvii] Brailovsky-Signoret, D. & Hernández (2026). Climatic & Cacti Database for Last Glacial Maximum. G. Reconstruction.

[xviii] Brailovsky-Signoret, D. & Hernández (2026). D:\DATACACTI\IDW_finedetal_IG idoneities_i.tif.

[xix] Brailovsky-Signoret, D. & Hernández (2026). D:\DATACACTI\IDW_finedetal_IG_idoneities_i.tif.

[xxi] Brailovsky-Signoret, D. & Hernández (2026). D:\DATACACTI\IDW_finedetal_IGO_MAXI.tif.

[xxi] Brailovsky-Signoret, D. & Hernández (2026). D:\DATACACTI\IDW_finedetal_IGO_Mean_idoneities_i.tif.

[xxii] CONABIO (Comisión Nacional para el Conocimiento y uso de la Biodiversidad). (1997a). Carta de Climas. Escala 1:1,000,000.

[xxiii] CONABIO (Comisión Nacional para el Conocimiento y uso de la Biodiversidad). (1997b). Carta de Isotermas anuales. Escala 1:1,000,000.

[xxiv] CONABIO (Comisión Nacional para el Conocimiento y uso de la Biodiversidad). (1997c). Carta de Precipitación total anual. Escala 1:1,000,000.

[xxv] CONABIO (Comisión Nacional para el Conocimiento y uso de la Biodiversidad). (2006). Información y cartografía digital. www.conabio.gob.mx

[xxvi] CONABIO (Comisión Nacional para el Conocimiento y uso de la Biodiversidad). (s. f.). Climas de la República Mexicana [Carta climática digital]. Geoportal CONABIO. Recuperado en Febrero de 2024-2026, de CONABIO Geoportal

[xxvii] Fick, S. E., Hijmans, R. J. (2017).WorldClim 2: new 1 km spatial resolution climate surfaces for global land areas.*International Journal of Climatology*, *37*(12), 4302 - 4315. https://doi.org/10.1002/joc.5086

[xxviii] Hernández, H. M., Gómez Hinostrosa, C. (2005, 2006). Subprovincias del Desierto Chihuahuense [Datos geoespaciales: capa vectorial]. En: Propuesta de delimitación del Desierto Chihuahuense. Instituto de Biología, Universidad Nacional Autónoma de México (UNAM). Shapefile consultado en D:\DATACACTI\CDBMAINSP.gpkg.

[xxix] Hernández, H. M., Gómez-Hinostrosa, C., et al. (n.d.). Database of Cactaceae of Central and North America [Unpublished dataset]. Instituto de Biología, Universidad Nacional Autónoma de México (UNAM). Retrieved September 2023. 4040 vouchers consulted, 2015 Localities consulted, 75 species consulted. Retrieved in september-october, 2023.

[xxx] Hernández, H. M., Gómez-Hinostrosa, C., et al. (n.d.). Database of Cactaceae of Central and North America [Unpublished dataset]. Instituto de Biología, Universidad Nacional Autónoma de México (UNAM). Retrieved September 2023. 317 vouchers consulted, 44 species consulted. Retrieved in April, 2025.

[xxxi] Instituto de Geografía, Universidad Nacional Autónoma de México. (1989). Carta de Viento dominante. Clima IV.4.2, *Atlas Nacional de México*, Escala 1:4,000,000.

[xxxii] Instituto de Geografía, Universidad Nacional Autónoma de México. (1989). Carta de Energía del Viento Dominante. Clima IV.4.3, *Atlas Nacional de México*, Escala 1:4,000,000.

[xxxiii] Instituto de Geología, Universidad Nacional Autónoma de México. (2007). Actualización de la Carta Geológica de México, escala 1:4 000 000 [Mapa geológico digital]. UNAM.

[xxxiv] Instituto Nacional de Estadística y Geografía. (2025). Modelos Digitales de Elevación, escala 1:50 000. 39 mosaicos correspondientes al Desierto Chihuahuense. Edición digital. INEGI.

[xxxv] Instituto Nacional de Estadística y Geografía (INEGI). (s. f.). Cartas topográficas escala 1:50 000 [Mapas topográficos digitales]. Recuperado en Febrero de 2024, de https://www.inegi.org.mx/temas/mapa/

[xxxvi] Instituto Nacional de Estadística y Geografía (INEGI). (s. f.). Carta Topográfica Nacional, escala 1:100 000 [Mapas topográficos digitales]. Recuperado en Febrero de 2025, de https://www.inegi.org.mx/app/mapa/espacial/

[xxxvii] International Association of Oil & Gas Producers (IOGP).(2023). EPSG:4326 – WGS 84. EPSG Geodetic Parameter Dataset. Recuperado el 10 de julio de 2025, de https://epsg.io/4326

[xxxviii] Met Office; Hollis, D., McCarthy, M., Kendon, M., Legg, T., Simpson, I. (2018). HadUK-Grid: gridded and regional average climate observations for the UK.Centre for Environmental Data Analysis. Recuperado de https://catalogue.ceda.ac.uk/uuid/4dc8450d889a491ebb20e724debe2dfb

[xxxix] National Imagery and Mapping Agency (NIMA). (2000). Department of Defense World Geodetic System 1984: Its definition and relationships with local geodetic systems (NIMA TR8350.2, Third Edition).Bethesda, MD: U.S. Department of Defense.

[xl] SARH (Secretaría de Recursos Hidráulicos). (1977). Documentación de la Comisión del Plan Nacional Hidráulico. 12 – Uso Potencial del Suelo. Anexo A – Área Central del Estado de Zacatecas. México. 21 pp.

[xli] Servicio Meteorológico Nacional – CONAGUA. (2008, 2018). Datos digitales en tiempo real de las sondas meteorológicas del Observatorio Meteorológico de la Bufa, Zacatecas. Servicio Meteorológico Nacional, México.

[xlii] Servicio Meteorológico Nacional – CONAGUA. (2006). Base de datos climáticos de la República Mexicana. CLIMCON.

[xliii] Servicio Meteorológico Nacional – CONAGUA. (2024). Normales climatológicas (1981 - 2010): 60 estaciones completas para el Desierto Chihuahuense. Recuperado en Febrero de 2024, de https://smn.conagua.gob.mx/es/climatologia/informacion-climatologica/normales-climatologicas-por-estado?estado=chih

[xliv] SRH (Secretaría de Recursos Hidráulicos). (1953, 1969). Boletín Hidrológico No. 11 de la Dirección General de Hidrología. Región Hidrológica No. 36, Ríos Nazas y Aguanaval.

[xlv] WorldClim 2.1 Bioclimatic variables (BIO1 - BIO19) [Dataset].(s. f.). University of California, Berkeley & CIAT. Google Earth Engine.Recuperado el 10 de julio de 2025, de https://developers.google.com/earth-engine/datasets/catalog/WORLDCLIM_V1_BIO

Appendix A.4. Climate Keys After Köppen Modified by García, by Keywords, English and Spanish

Climatic type	Climate in words / Clima en palabras	Rainfall regime / Régimen de lluvias
Köppen (García)
(A)Cbm(f)(i´)g	Temperate oceanic climate with abundant rainfall, mild summers, and cool winters with occasional frost.	Rainfall all year, mildly dry winter, oceanic influence
AW	Tropical climate with summer rains and a dry winter season (savanna).	Summer rains, dry winter
C(m)(f)b(e)	Temperate climate with constant rainfall, moderate summers, and cool winters.	Rainfall all year, erratic pattern
Cb(m)(f)(e)	Temperate highland climate with regular rainfall and mild temperatures.	Rainfall all year, erratic pattern
Cx´(w1)b	Highland climate with marked summer precipitation and cool summers.	Summer rains, short dry season, cool summers
BS0hw(e)	Warm steppe climate with sparse winter precipitation.	Sparse winter rains, erratic rainfall
BS0hw(e)g	Warm steppe climate with weak winter rains and slight oceanic influence.	Sparse winter rains, erratic pattern, and oceanic influence
BS0kw(e)	Cold semi-arid climate with slight winter precipitation.	Winter rainfall, erratic pattern
BS0kw(x´)(e)	Cold semi-arid climate with slight winter precipitation.	Extremely scarce summer rains, erratic rainfall
BS0kx´(w)(e)	Cold semi-arid climate with extreme summer heat and slight winter precipitation.	Summer rains, extremely scarce, erratic pattern
BS1(h´)hw(e´)g	Hot semi-arid climate, very dry, with strong oceanic influence and some winter precipitation.	Very scarce winter rains, highly erratic, oceanic influence
BS1hw(e)	Hot semi-arid climate with slight winter precipitation.	Light winter rains, erratic pattern
BS1hx´(w)(e)	Hot semi-arid climate with extreme heat, dry winters, and slight precipitation.	Summer rains, extremely scarce, erratic pattern
BS1kw(e)	Cold semi-arid climate with slight winter precipitation.	Winter rains, erratic pattern
BS1kw(e)g	Cold semi-arid climate with slight winter precipitation and oceanic influence.	Winter rains, erratic pattern, and oceanic influence
BS1kw(i´)g	Cold semi-arid climate with cold winters and oceanic influence.	Mildly dry winter, erratic rainfall, oceanic influence
BS1kx´(w)(e)	Cold semi-arid climate with extreme summer heat, dry winters, and slight precipitation.	Summer rains, extremely scarce, erratic pattern
BWhw(e´)	Hot desert climate with winter precipitation.	Sparse winter rains, very erratic pattern
(A)Cbm(f)(i´)g	Clima templado subhúmedo con lluvias todo el año, veranos cálidos, inviernos frescos y con influencia oceánica.	Lluvias todo el año, invierno ligeramente seco, influencia oceánica
AW	Clima tropical de sabana con estación seca en invierno.	Lluvias en verano, estación seca en invierno
C(m)(f)b(e)	Clima templado con lluvias constantes, veranos templados e inviernos frescos.	Lluvias todo el año, régimen errático
Cb(m)(f)(e)	Clima templado de montaña con lluvias todo el año y temperaturas moderadas.	Lluvias todo el año, régimen errático
Cx´(w1)b	Clima de montaña con lluvias en verano y veranos frescos.	Lluvias en verano, estación seca corta, veranos frescos
BS0hw(e)	Clima estepario cálido con estación seca y ligeras precipitaciones invernales.	Pocas lluvias en invierno, régimen errático
BS0hw(e)g	Clima estepario frío con lluvias invernales escasas.	Pocas lluvias en invierno, régimen errático, con influencia oceánica
BS0kw(e)	Clima estepario cálido con estación seca, ligeras lluvias en invierno y cierta influencia oceánica.	Lluvias en invierno, régimen errático
BS0kw(x´)(e)	Clima estepario frío con verano extremadamente caluroso y lluvias invernales ligeras.	Lluvias extremadamente escasas en verano, régimen errático
BS0kx´(w)(e)	Clima estepario frío con verano muy caluroso, invierno seco y lluvias ligeras.	Lluvias en verano, extremadamente escasas, régimen errático
BS1(h´)hw(e´)g	Clima semiárido cálido muy seco, con ligeras lluvias invernales e influencia oceánica.	Lluvias invernales muy escasas, régimen muy errático, con influencia oceánica
BS1hw(e)	Clima semiárido cálido con estación seca y lluvias ligeras en invierno.	Lluvias ligeras en invierno, régimen errático
BS1hx´(w)(e)	Clima semiárido cálido con calor extremo en verano, invierno seco y lluvias ligeras.	Lluvias en verano, extremadamente escasas, régimen errático
BS1kw(e)	Clima semiárido frío con lluvias ligeras en invierno.	Lluvias en invierno, régimen errático
BS1kw(e)g	Clima semiárido frío con lluvias invernales y cierta influencia oceánica.	Lluvias en invierno, régimen errático, con influencia oceánica
BS1kw(i´)g	Clima semiárido frío con inviernos fríos e influencia oceánica.	Invierno ligeramente seco, régimen errático, con influencia oceánica
BS1kx´(w)(e)	Clima semiárido frío con verano muy caluroso, invierno seco y lluvias ligeras.	Lluvias en verano, extremadamente escasas, régimen errático
BWhw(e´)	Clima desértico cálido con precipitaciones invernales.	Lluvias escasas en invierno, régimen muy errático

Appendix B.1. Conservation Status, Endemism & Area Evaluations, Inclusivity Percentage, MAXENT SDMS R Values

Table A1. b – Endemic Cacti comprehensive list, IUCN status, count by species, inclusivity, areality, endemism & R-run MAXENT Settings. Sinonimia is given, and inclusivity in the CDB is presented in counts and percentages. Endemism evaluations for the supbprovinces (right) are given in calues from 0 to 1, where 1 is maximum.

No.	Species	SINONIMIA (Korotkova, IUCN & IPNI)	COUNT	IUCN status	Outsiders count	Insiders count	Outsiders %	Insiders %	AO sq km	AO Index 0-1	Stdz Fragmentation 0-1	MainEnd 0-1	EastSPEnd 0-1	MerSPEnd 0-1
1	Ariocarpus agavoides	Anhalonium agavoides, Roseocactus agavoides	14	EN	0	14	0.00	100.00	5142	0.01	0.10	0.93	0.00	0.07
2	Ariocarpus fissuratus	Anhalonium fissuratum, Roseocactus fissuratus	40	LC	1	85	1.16	98.84	119838	0.22	0.16	0.93	0.00	0.08
3	Ariocarpus kotschoubeyanus	Anhalonium kotschoubeyanum, Roseocactus kotschoubeyanus	49	NT	0	49	0.00	100.00	59636	0.11	0.18	0.82	0.06	0.12
4	Ariocarpus retusus	Anhalonium retusum, Roseocactus retusus	156	LC	0	156	0.00	100.00	31186	0.06	0.07	0.87	0.05	0.08
5	Astrophytum capricorne	Echinocactus capricornis, Astrophytum capricorne var. senile	41	LC	1	40	2.44	97.56	7386	0.01	0.04	0.83	0.02	0.15
6	Astrophytum myriostigma	Echinocactus myriostigma, Astrophytum prismaticum	126	LC	0	125	0.00	100.00	26325	0.05	0.14	0.90	0.02	0.08
7	Astrophytum ornatum	Echinocactus ornatus, Astrophytum mirbelii	47	VU	2	44	4.35	95.65	1708	0.00	0.02	0.89	0.02	0.09
8	Coryphantha difficilis	Mammillaria difficilis, Escobaria difficilis	12	LC	0	12	0.00	100.00	1475	0.00	0.03	0.83	0.00	0.17
9	Coryphantha durangensis	Mammillaria durangensis, Escobaria durangensis	6	LC	0	6	0.00	100.00	101269	0.19	0.36	1.00	0.00	0.00
10	Coryphantha macromeris	Mammillaria macromeris, Escobaria macromeris	35	LC	0	45	0.00	100.00	112695	0.21	0.19	0.91	0.03	0.06
11	Coryphantha octacantha	Mammillaria octacantha, Escobaria octacantha	35	LC	1	32	3.03	96.97	110569	0.21	0.19	0.76	0.03	0.21
12	Coryphantha poselgeriana	Mammillaria poselgeriana, Escobaria poselgeriana	51	LC	0	51	0.00	100.00	53095	0.10	0.13	0.90	0.02	0.06
13	Coryphantha pulleineana	Mammillaria pulleineana, Escobaria pulleineana	8	LC	0	8	0.00	100.00	10407	0.02	0.14	0.88	0.00	0.13
14	Coryphantha werdermannii	Mammillaria werdermannii, Escobaria werdermannii	5	LC	0	5	0.00	100.00	4757	0.01	0.09	0.80	0.00	0.20
15	Cumarinia odorata	Mammillaria odorata, Escobaria odorata	16	LC	0	16	0.00	100.00	3849	0.01	0.06	0.81	0.00	0.19
16	Echinocereus enneacanthus	Cereus enneacanthus, Wilcoxia enneacantha	140	LC	10	142	6.58	93.42	93073	0.17	0.11	0.85	0.04	0.06
17	Echinocereus knippelianus	Cereus knippelianus, Wilcoxia knippeliana	13	LC	0	12	0.00	100.00	48664	0.09	0.28	0.85	0.08	0.08
18	Echinocereus pentalophus	Cereus pentalophus, Wilcoxia pentalopha	284	LC	34	243	12.27	87.73	32750	0.06	0.07	0.88	0.02	0.10
19	Echinocereus stramineus	Cereus stramineus, Wilcoxia straminea	57	LC	4	417	0.95	99.05	58312	0.11	0.10	0.77	0.00	0.12
20	Echinocereus viereckii	Cereus viereckii, Wilcoxia viereckii	3	LC	0	3	0.00	100.00	123878	0.23	0.62	1.00	0.00	0.00
21	Epithelantha greggii	Mammillaria greggii, Coryphantha greggii	30	-	0	105	0.00	100.00	15947	0.03	0.08	0.83	0.03	0.13
22	Epithelantha micromeris	Mammillaria micromeris, Coryphantha micromeris	29	LC	10	121	7.63	92.37	156197	0.29	0.21	0.77	0.00	0.23
23	Epithelantha spinosior	Mammillaria spinosior, Coryphantha spinosior	3	-	0	3	0.00	100.00	2222	0.00	0.08	1.00	0.00	0.00
24	Escobaria chihuahuensis	Coryphantha chihuahuensis, Mammillaria chihuahuensis	5	LC	0	5	0.00	100.00	288375	0.54	0.82	0.60	0.00	0.40
25	Escobaria dasyacantha	Coryphantha dasyacantha, Mammillaria dasyacantha	22	LC	0	25	0.00	100.00	537441	1.00	1.00	0.77	0.00	0.23
26	Ferocactus echidne	Echinocactus echidne, Ferocactus pringlei	91	LC	8	77	9.41	90.59	8329	0.02	0.03	0.81	0.02	0.15
27	Ferocactus hamatacanthus	Echinocactus hamatacanthus, Ferocactus sinuatus	189	LC	23	187	10.95	89.05	137952	0.26	0.17	0.83	0.04	0.07
28	Ferocactus pilosus	Echinocactus pilosus, Ferocactus stainesii	209	LC	1	206	0.48	99.52	58042	0.11	0.17	0.93	0.01	0.03
29	Homalocephala parryi	Echinocactus parryi, Ferocactus parryi	14	NT	0	14	0.00	100.00	10530	0.02	0.14	0.79	0.00	0.21
30	Leuchtenbergia principis	Echinocactus principis, Agave principis	47	LC	0	46	0.00	100.00	25641	0.05	0.10	0.72	0.13	0.13
31	Lophophora diffusa	Anhalonium diffusum, Lophophora williamsii var. diffusa	28	VU	0	28	0.00	100.00	1412	0.00	0.04	0.54	0.04	0.43
32	Lophophora williamsii	Anhalonium williamsii, Lophophora lewinii	108	VU	9	102	8.11	91.89	118528	0.22	0.19	0.86	0.02	0.08
33	Mammillaria albicoma	Escobaria albicoma, Coryphantha albicoma	11	EN	0	9	0.00	100.00	5277	0.01	0.07	0.91	0.00	0.00
34	Mammillaria baumii	Escobaria baumii, Coryphantha baumii	12	LC	0	12	0.00	100.00	496	0.00	0.02	0.83	0.08	0.08
35	Mammillaria bocasana	Neomammillaria bocasana, Cactus boscanus	9	LC	0	9	0.00	100.00	20383	0.04	0.23	0.89	0.00	0.11
36	Mammillaria compressa	Neomammillaria compressa, Cactus compressus	146	LC	16	120	11.76	88.24	35464	0.07	0.13	0.88	0.01	0.08
37	Mammillaria formosa	Neomammillaria formosa, Cactus formosus	294	LC	3	284	1.05	98.95	59332	0.11	0.10	0.91	0.02	0.07
38	Mammillaria gigantea	Neomammillaria gigantea, Cactus giganteus	12	DD	0	12	0.00	100.00	13676	0.03	0.11	0.92	0.00	0.08
39	Mammillaria glassii	Neomammillaria glassii, Cactus glassii	20	LC	0	19	0.00	100.00	3919	0.01	0.04	0.80	0.20	0.00
40	Mammillaria klissingiana	Neomammillaria klissingiana, Cactus klissingianus	7	LC	0	7	0.00	100.00	43639	0.08	0.29	0.86	0.14	0.00
41	Mammillaria lenta	Neomammillaria lenta, Cactus lentus	12	LC	0	12	0.00	100.00	19968	0.04	0.15	0.92	0.00	0.08
42	Mammillaria moelleriana	Neomammillaria moelleriana, Cactus moellerianus	4	LC	0	7	0.00	100.00	12902	0.02	0.21	1.00	0.00	0.00
43	Mammillaria parkinsonii	Neomammillaria parkinsonii, Cactus parkinsonii	22	EN	3	19	13.64	86.36	557	0.00	0.02	0.77	0.05	0.18
44	Mammillaria perbella	Neomammillaria perbella, Cactus perbellus	19	VU	2	17	10.53	89.47	2735	0.01	0.05	0.84	0.00	0.16
45	Mammillaria picta	Neomammillaria picta, Cactus pictus	66	LC	1	65	1.52	98.48	9053	0.02	0.06	0.85	0.05	0.11
46	Mammillaria plumosa	Neomammillaria plumosa, Cactus plumosus	8	LC	1	7	12.50	87.50	3350	0.01	0.08	0.75	0.13	0.13
47	Mammillaria pottsii	Neomammillaria pottsii, Cactus pottsii	85	LC	0	109	0.00	100.00	73827	0.14	0.12	0.80	0.00	0.12
48	Mammillaria schiedeana	Neomammillaria schiedeana, Cactus schiedeanus	30	VU	1	29	3.33	96.67	1522	0.00	0.02	0.87	0.00	0.13
49	Mammillaria sphaerica	Neomammillaria sphaerica, Cactus sphaericus	3	LC	0	3	0.00	100.00	59162	0.11	0.42	1.00	0.00	0.00
50	Mammillaria surculosa	Neomammillaria surculosa, Cactus surculosus	10	EN	0	10	0.00	100.00	1896	0.00	0.05	1.00	0.00	0.00
51	Neobuxbaumia euphorbioides	Cereus euphorbioides, Carnegiea euphorbioides	4	VU	0	7	0.00	100.00	4706	0.01	0.12	1.00	0.00	0.00
52	Neobuxbaumia polylopha	Cereus polylophus, Carnegiea polylopha	8	VU	0	8	0.00	100.00	12047	0.02	0.11	1.00	0.00	0.00
53	Neolloydia matehualensis	Echinocactus matehualensis, Coryphantha matehualensis	14	DD	0	8	0.00	100.00	187937	0.35	0.66	0.86	0.00	0.00
54	Obregonia denegrii	Ariocarpus denegrii, Strombocactus denegrii	16	EN	0	16	0.00	100.00	353	0.00	0.02	0.94	0.06	0.00
55	Opuntia megarrhiza	Platyopuntia megarrhiza, Nopalea megarrhiza	11	EN	0	11	0.00	100.00	20022	0.04	0.18	1.00	0.00	0.00
56	Opuntia microdasys	Cactus microdasys, Opuntia rufida	208	LC	20	183	9.85	90.15	141042	0.26	0.35	0.88	0.01	0.09
57	Opuntia pachyrrhiza	Platyopuntia pachyrrhiza, Nopalea pachyrrhiza	21	EN	2	19	9.52	90.48	59407	0.11	0.30	0.57	0.00	0.43
58	Opuntia rufida	Cactus rufidus, Opuntia microdasys var. rufida	100	LC	3	122	2.40	97.60	117388	0.22	0.17	0.80	0.00	0.13
59	Pelecyphora aselliformis	Mammillaria aselliformis, Encephalocarpus aselliformis	21	LC	0	21	0.00	100.00	1185	0.00	0.03	0.81	0.05	0.14
60	Pelecyphora strobiliformis	Mammillaria strobiliformis, Encephalocarpus strobiliformis	14	LC	1	13	7.14	92.86	14989	0.03	0.15	0.93	0.07	0.00
61	Sclerocactus mariposensis	Ancistrocactus mariposensis, Echinocactus mariposensis	16	LC	1	35	2.78	97.22	50098	0.09	0.16	0.63	0.06	0.31
62	Sclerocactus unguispinus	Ancistrocactus unguispinus, Echinocactus unguispinus	32	LC	3	28	9.68	90.32	122733	0.23	0.26	0.88	0.03	0.09
63	Stenocactus coptonogonus	Echinofossulocactus coptogonus, Echinocactus coptogonus	31	LC	6	20	23.08	76.92	62758	0.12	0.24	0.84	0.03	0.10
64	Strombocactus disciformis	Echinocactus disciformis, Mammillaria disciformis	29	VU	2	27	6.90	93.10	2481	0.00	0.06	0.86	0.00	0.14
65	Thelocactus bicolor	Thelocactus hexaedrophorus	132	LC	11	149	6.88	93.13	150368	0.28	0.21	0.88	0.00	0.10
66	Thelocactus conothelos	Echinocactus conothelos, Ferocactus conothelos	91	LC	0	81	0.00	100.00	4874	0.01	0.03	0.86	0.03	0.07
67	Thelocactus hexaedrophorus	Echinocactus hexaedrophorus, Ferocactus hexaedrophorus	118	LC	0	116	0.00	100.00	33940	0.06	0.10	0.92	0.01	0.08
68	Thelocactus rinconensis	Echinocactus rinconensis, Ferocactus rinconensis	22	LC	1	21	4.55	95.45	14696	0.03	0.11	0.86	0.00	0.14
69	Turbinicarpus knuthianus	Gymnocactus knuthianus, Echinocactus knuthianus	16	-	0	16	0.00	100.00	1025	0.00	0.04	0.94	0.00	0.06
70	Turbinicarpus pseudomacrochele	Gymnocactus pseudomacrochele, Echinocactus pseudomacrochele	11	EN	0	11	0.00	100.00	223	0.00	0.01	0.64	0.09	0.27
71	Turbinicarpus pseudopectinatus	Gymnocactus pseudopectinatus, Echinocactus pseudopectinatus	24	LC	0	24	0.00	100.00	24467	0.05	0.15	0.88	0.00	0.13
72	Turbinicarpus schmiedickeanus	Gymnocactus schmiedickeanus, Echinocactus schmiedickeanus	59	NT	0	59	0.00	100.00	6417	0.01	0.05	0.92	0.02	0.07
73	Turbinicarpus subterraneus	Gymnocactus subterraneus, Echinocactus subterraneus	6	EN	0	6	0.00	100.00	11925	0.02	0.14	1.00	0.00	0.00
74	Turbinicarpus valdezianus	Gymnocactus valdezianus, Echinocactus valdezianus	8	VU	0	8	0.00	100.00	27485	0.05	0.18	1.00	0.00	0.00
75	Turbinicarpus viereckii	Gymnocactus viereckii, Echinocactus viereckii	15	LC	0	15	0.00	100.00	2015	0.00	0.04	1.00	0.00	0.00
ADDENDUM Microareal & Non-Modelable Endemics						MAXENT Settings from R routines				MAXENT (Mod. Settings R routines	fc - model IG	rm - correction IG	fc - models G	rm - correction G
76	Acharagma aguirreana		6	CR		1	Ariocarpus agavoides			JK	H	4	LQH	2
77	Acharagma roseanum	Escobaria roseanum	5	VU		2	Ariocarpus fissuratus			JK	L	1	LQHPT	4
78	Ariocarpus bravoanus		19	EN		3	Ariocarpus kotschoubeyanus			JK	LQHPT	3	LQ	1
79	Ariocarpus scaphirostris		7	EN		4	Ariocarpus retusus			RKF	LQ	1	LQHPT	3
80	Ariocarpus trigonus		24	LC		5	Astrophytum capricorne			JK	LQHP	2	LQ	1
81	Aztekium hintonii		4	NT		6	Astrophytum myriostigma			RKF	LQHPT	2	LQ	1
82	Aztekium ritteri		7	LC		7	Astrophytum ornatum			JK	LQ	1	LQ	2
83	Coryphantha clavata		46	LC		8	Coryphantha difficilis			JK	L	2	LQ	1
84	Coryphantha wohlschlageri		5	LC		9	Coryphantha durangensis			JK	LQHP	5	LQHPT	2
85	Echinocereus poselgeri	Wilcoxia tuberosa	46	LC		10	Coryphantha macromeris			JK	L	1	L	2
86	Echinocereus waldeisii		5	-		11	Coryphantha octacantha			JK	LQ	2	LQ	1
87	Epithelantha bokei		14	LC		12	Coryphantha poselgeriana			RKF	L	1	LQ	2
89	Geohintonia mexicana		3	NT		13	Coryphantha pulleineana			JK	LQ	3	LQHPT	4
90	Mammillaria duwei		5	CR		14	Coryphantha werdermannii			JK	L	2	L	4
91	Mammillaria elongata		52	LC		15	Cumarinia odorata			JK	LQ	1	LQ	1
92	Mammillaria erythrosperma		9	LC		16	Echinocereus enneacanthus			RKF	LQHPT	2	LQ	1
93	Mammillaria glochidiata		2	CR		17	Echinocereus knippelianus			JK	LQ	1	LQ	1
94	Mammillaria marcosi		2	CR		18	Echinocereus pentalophus			RKF	LQHPT	1	LQHPT	2
95	Mammillaria microhelia		2	EN		19	Echinocereus stramineus			RKF	LQ	1	LQHPT	1
96	Mammillaria perezdelarosae		19	-		20	Echinocereus viereckii			JK	LQHPT	4	LQHPT	3
97	Mammillaria pilispina		49	LC		21	Epithelantha greggii			JK	LQHPT	2	LQH	3
98	Mammillaria pottsii		109	LC		22	Epithelantha micromeris			JK	L	4	LQ	1
99	Mammillaria prolifera		72	LC		23	Epithelantha spinosior			JK	LQH	4	LQHP	4
100	Mammillaria scheinvariana		1	-		24	Escobaria chihuahuensis			JK	L	4	L	1
101	Mammillaria tezontle		1	-		25	Escobaria dasyacantha			JK	LQ	2	LQ	1
102	Mammillaria weingartiana		7	LC		26	Ferocactus echidne			RKF	LQHPT	3	L	3
103	Mammillaria wrightii		30	LC		27	Ferocactus hamatacanthus			RKF	LQHPT	2	LQ	1
104	Mammillaria zahniana		2	-		28	Ferocactus pilosus			RKF	LQ	1	LQHPT	2
105	Opuntia anteojoensis		12	VU		29	Homalocephala parryi			JK	H	3	LQ	1
106	Opuntia xandersonii		27	-		30	Leuchtenbergia principis			JK	LQ	1	LQ	1
107	Sclerocactus warnockii		32	LC		31	Lophophora diffusa			JK	LQH	1	LQ	1
108	Strombocactus corregidorae		4	-		32	Lophophora williamsii			RKF	LQ	1	LQ	1
109	Thelocactus alonsoi		1	-		33	Mammillaria albicoma			JK	LQ	2	LQ	2
110	Thelocactus horripilus		8	-		34	Mammillaria baumii			JK	LQ	1	LQ	1
111	Thelocactus lausseri		1	DD		35	Mammillaria bocasana			JK	L	1	LQ	2
112	Rapicactus beguinii		57	LC		36	Mammillaria compressa			RKF	LQHPT	2	LQ	1
113	Turbinicarpus gielsdorfianus		3	CR		37	Mammillaria formosa			RKF	LQHPT	2	LQHPT	1
114	Turbinicarpus hoferi		5	CR		38	Mammillaria gigantea			JK	LQ	1	LQ	1
115	Turbinicarpus iysabelae		5	-		39	Mammillaria glassii			JK	LQ	1	LQ	2
116	Turbinicarpus lophophoroides		4	NT		40	Mammillaria klissingiana			JK	H	5	LQ	1
117	Turbinicarpus mandragora		1	CR		41	Mammillaria lenta			JK	L	2	LQ	1
118	Turbinicarpus swobodae		1	CR		42	Mammillaria moelleriana			JK	L	5	H	3
119	Turbinicarpus xmombergeri		1	-		43	Mammillaria parkinsonii			JK	LQ	1	LQ	1
120	Turbinicarpus zaragozae		1	-		44	Mammillaria perbella			JK	LQ	2	LQ	1
						45	Mammillaria picta			RKF	LQ	1	LQ	1
						46	Mammillaria plumosa			JK	LQH	2	LQH	3
						47	Mammillaria pottsii			RKF	L	1	L	1
						48	Mammillaria schiedeana			RKF	LQ	1	LQ	1
						49	Mammillaria sphaerica			JK	L	2	L	2
						50	Mammillaria surculosa			JK	LQ	1	LQ	2
						51	Neobuxbaumia euphorbioides			JK	LQHP	1	H	3
						52	Neobuxbaumia polylopha			JK	LQH	2	L	1
						53	Neolloydia matehualensis			JK	LQ	1	H	3
						54	Obregonia denegrii			JK	LQ	1	LQ	1
						55	Opuntia megarrhiza			JK	LQ	3	LQ	1
						56	Opuntia microdasys			RKF	LQHPT	2	LQHPT	3
						57	Opuntia pachyrrhiza			JK	LQ	1	LQ	1
						58	Opuntia rufida			RKF	LQHPT	2	LQ	1
						59	Pelecyphora aselliformis			JK	LQ	1	LQHP	1
						60	Pelecyphora strobiliformis			JK	LQHPT	4	LQ	1
						61	Sclerocactus mariposensis			JK	LQ	1	L	1
						62	Sclerocactus unguispinus			JK	LQH	4	L	3
						63	Stenocactus coptonogonus			JK	LQH	2	LQ	1
						64	Strombocactus disciformis			JK	LQ	1	LQ	1
						65	Thelocactus bicolor			RKF	LQHPT	2	LQ	2
						66	Thelocactus conothelos			RKF	LQ	1	LQHPT	3
						67	Thelocactus hexaedrophorus			RKF	LQ	1	LQ	1
						68	Thelocactus rinconensis			JK	LQ	1	LQ	1
						69	Turbinicarpus knuthianus			JK	LQ	1	LQH	1
						70	Turbinicarpus pseudomacrochele			JK	L	1	LQ	2
						71	Turbinicarpus pseudopectinatus			JK	LQ	1	LQ	1
						72	Turbinicarpus schmiedickeanus			RKF	LQ	1	LQ	1
						73	Turbinicarpus subterraneus			JK	LQHPT	4	LQ	2
						74	Turbinicarpus valdezianus			JK	H	2	LQ	2
						75	Turbinicarpus viereckii			JK	LQ	2	LQ	1

* R routines were revised with the adivce of J. Banta, University of Texas. Non-modelable species usually have one or two sites. Detail on analyses are available by request, and the complete set of MAXENT SDMs, and fine layers, could be consulted in the digital SM.

Table A1. b – Endemic Cacti comprehensive list, IUCN status, count by species, inclusivity, areality, endemism & R-run MAXENT Settings. Sinonimia is given, and inclusivity in the CDB is presented in counts and percentages. Endemism evaluations for the supbprovinces (right) are given in calues from 0 to 1, where 1 is maximum.

No.	Species	SINONIMIA (Korotkova, IUCN & IPNI)	COUNT	IUCN status	Outsiders count	Insiders count	Outsiders %	Insiders %	AO sq km	AO Index 0-1	Stdz Fragmentation 0-1	MainEnd 0-1	EastSPEnd 0-1	MerSPEnd 0-1
1	Ariocarpus agavoides	Anhalonium agavoides, Roseocactus agavoides	14	EN	0	14	0.00	100.00	5142	0.01	0.10	0.93	0.00	0.07
2	Ariocarpus fissuratus	Anhalonium fissuratum, Roseocactus fissuratus	40	LC	1	85	1.16	98.84	119838	0.22	0.16	0.93	0.00	0.08
3	Ariocarpus kotschoubeyanus	Anhalonium kotschoubeyanum, Roseocactus kotschoubeyanus	49	NT	0	49	0.00	100.00	59636	0.11	0.18	0.82	0.06	0.12
4	Ariocarpus retusus	Anhalonium retusum, Roseocactus retusus	156	LC	0	156	0.00	100.00	31186	0.06	0.07	0.87	0.05	0.08
5	Astrophytum capricorne	Echinocactus capricornis, Astrophytum capricorne var. senile	41	LC	1	40	2.44	97.56	7386	0.01	0.04	0.83	0.02	0.15
6	Astrophytum myriostigma	Echinocactus myriostigma, Astrophytum prismaticum	126	LC	0	125	0.00	100.00	26325	0.05	0.14	0.90	0.02	0.08
7	Astrophytum ornatum	Echinocactus ornatus, Astrophytum mirbelii	47	VU	2	44	4.35	95.65	1708	0.00	0.02	0.89	0.02	0.09
8	Coryphantha difficilis	Mammillaria difficilis, Escobaria difficilis	12	LC	0	12	0.00	100.00	1475	0.00	0.03	0.83	0.00	0.17
9	Coryphantha durangensis	Mammillaria durangensis, Escobaria durangensis	6	LC	0	6	0.00	100.00	101269	0.19	0.36	1.00	0.00	0.00
10	Coryphantha macromeris	Mammillaria macromeris, Escobaria macromeris	35	LC	0	45	0.00	100.00	112695	0.21	0.19	0.91	0.03	0.06
11	Coryphantha octacantha	Mammillaria octacantha, Escobaria octacantha	35	LC	1	32	3.03	96.97	110569	0.21	0.19	0.76	0.03	0.21
12	Coryphantha poselgeriana	Mammillaria poselgeriana, Escobaria poselgeriana	51	LC	0	51	0.00	100.00	53095	0.10	0.13	0.90	0.02	0.06
13	Coryphantha pulleineana	Mammillaria pulleineana, Escobaria pulleineana	8	LC	0	8	0.00	100.00	10407	0.02	0.14	0.88	0.00	0.13
14	Coryphantha werdermannii	Mammillaria werdermannii, Escobaria werdermannii	5	LC	0	5	0.00	100.00	4757	0.01	0.09	0.80	0.00	0.20
15	Cumarinia odorata	Mammillaria odorata, Escobaria odorata	16	LC	0	16	0.00	100.00	3849	0.01	0.06	0.81	0.00	0.19
16	Echinocereus enneacanthus	Cereus enneacanthus, Wilcoxia enneacantha	140	LC	10	142	6.58	93.42	93073	0.17	0.11	0.85	0.04	0.06
17	Echinocereus knippelianus	Cereus knippelianus, Wilcoxia knippeliana	13	LC	0	12	0.00	100.00	48664	0.09	0.28	0.85	0.08	0.08
18	Echinocereus pentalophus	Cereus pentalophus, Wilcoxia pentalopha	284	LC	34	243	12.27	87.73	32750	0.06	0.07	0.88	0.02	0.10
19	Echinocereus stramineus	Cereus stramineus, Wilcoxia straminea	57	LC	4	417	0.95	99.05	58312	0.11	0.10	0.77	0.00	0.12
20	Echinocereus viereckii	Cereus viereckii, Wilcoxia viereckii	3	LC	0	3	0.00	100.00	123878	0.23	0.62	1.00	0.00	0.00
21	Epithelantha greggii	Mammillaria greggii, Coryphantha greggii	30	-	0	105	0.00	100.00	15947	0.03	0.08	0.83	0.03	0.13
22	Epithelantha micromeris	Mammillaria micromeris, Coryphantha micromeris	29	LC	10	121	7.63	92.37	156197	0.29	0.21	0.77	0.00	0.23
23	Epithelantha spinosior	Mammillaria spinosior, Coryphantha spinosior	3	-	0	3	0.00	100.00	2222	0.00	0.08	1.00	0.00	0.00
24	Escobaria chihuahuensis	Coryphantha chihuahuensis, Mammillaria chihuahuensis	5	LC	0	5	0.00	100.00	288375	0.54	0.82	0.60	0.00	0.40
25	Escobaria dasyacantha	Coryphantha dasyacantha, Mammillaria dasyacantha	22	LC	0	25	0.00	100.00	537441	1.00	1.00	0.77	0.00	0.23
26	Ferocactus echidne	Echinocactus echidne, Ferocactus pringlei	91	LC	8	77	9.41	90.59	8329	0.02	0.03	0.81	0.02	0.15
27	Ferocactus hamatacanthus	Echinocactus hamatacanthus, Ferocactus sinuatus	189	LC	23	187	10.95	89.05	137952	0.26	0.17	0.83	0.04	0.07
28	Ferocactus pilosus	Echinocactus pilosus, Ferocactus stainesii	209	LC	1	206	0.48	99.52	58042	0.11	0.17	0.93	0.01	0.03
29	Homalocephala parryi	Echinocactus parryi, Ferocactus parryi	14	NT	0	14	0.00	100.00	10530	0.02	0.14	0.79	0.00	0.21
30	Leuchtenbergia principis	Echinocactus principis, Agave principis	47	LC	0	46	0.00	100.00	25641	0.05	0.10	0.72	0.13	0.13
31	Lophophora diffusa	Anhalonium diffusum, Lophophora williamsii var. diffusa	28	VU	0	28	0.00	100.00	1412	0.00	0.04	0.54	0.04	0.43
32	Lophophora williamsii	Anhalonium williamsii, Lophophora lewinii	108	VU	9	102	8.11	91.89	118528	0.22	0.19	0.86	0.02	0.08
33	Mammillaria albicoma	Escobaria albicoma, Coryphantha albicoma	11	EN	0	9	0.00	100.00	5277	0.01	0.07	0.91	0.00	0.00
34	Mammillaria baumii	Escobaria baumii, Coryphantha baumii	12	LC	0	12	0.00	100.00	496	0.00	0.02	0.83	0.08	0.08
35	Mammillaria bocasana	Neomammillaria bocasana, Cactus boscanus	9	LC	0	9	0.00	100.00	20383	0.04	0.23	0.89	0.00	0.11
36	Mammillaria compressa	Neomammillaria compressa, Cactus compressus	146	LC	16	120	11.76	88.24	35464	0.07	0.13	0.88	0.01	0.08
37	Mammillaria formosa	Neomammillaria formosa, Cactus formosus	294	LC	3	284	1.05	98.95	59332	0.11	0.10	0.91	0.02	0.07
38	Mammillaria gigantea	Neomammillaria gigantea, Cactus giganteus	12	DD	0	12	0.00	100.00	13676	0.03	0.11	0.92	0.00	0.08
39	Mammillaria glassii	Neomammillaria glassii, Cactus glassii	20	LC	0	19	0.00	100.00	3919	0.01	0.04	0.80	0.20	0.00
40	Mammillaria klissingiana	Neomammillaria klissingiana, Cactus klissingianus	7	LC	0	7	0.00	100.00	43639	0.08	0.29	0.86	0.14	0.00
41	Mammillaria lenta	Neomammillaria lenta, Cactus lentus	12	LC	0	12	0.00	100.00	19968	0.04	0.15	0.92	0.00	0.08
42	Mammillaria moelleriana	Neomammillaria moelleriana, Cactus moellerianus	4	LC	0	7	0.00	100.00	12902	0.02	0.21	1.00	0.00	0.00
43	Mammillaria parkinsonii	Neomammillaria parkinsonii, Cactus parkinsonii	22	EN	3	19	13.64	86.36	557	0.00	0.02	0.77	0.05	0.18
44	Mammillaria perbella	Neomammillaria perbella, Cactus perbellus	19	VU	2	17	10.53	89.47	2735	0.01	0.05	0.84	0.00	0.16
45	Mammillaria picta	Neomammillaria picta, Cactus pictus	66	LC	1	65	1.52	98.48	9053	0.02	0.06	0.85	0.05	0.11
46	Mammillaria plumosa	Neomammillaria plumosa, Cactus plumosus	8	LC	1	7	12.50	87.50	3350	0.01	0.08	0.75	0.13	0.13
47	Mammillaria pottsii	Neomammillaria pottsii, Cactus pottsii	85	LC	0	109	0.00	100.00	73827	0.14	0.12	0.80	0.00	0.12
48	Mammillaria schiedeana	Neomammillaria schiedeana, Cactus schiedeanus	30	VU	1	29	3.33	96.67	1522	0.00	0.02	0.87	0.00	0.13
49	Mammillaria sphaerica	Neomammillaria sphaerica, Cactus sphaericus	3	LC	0	3	0.00	100.00	59162	0.11	0.42	1.00	0.00	0.00
50	Mammillaria surculosa	Neomammillaria surculosa, Cactus surculosus	10	EN	0	10	0.00	100.00	1896	0.00	0.05	1.00	0.00	0.00
51	Neobuxbaumia euphorbioides	Cereus euphorbioides, Carnegiea euphorbioides	4	VU	0	7	0.00	100.00	4706	0.01	0.12	1.00	0.00	0.00
52	Neobuxbaumia polylopha	Cereus polylophus, Carnegiea polylopha	8	VU	0	8	0.00	100.00	12047	0.02	0.11	1.00	0.00	0.00
53	Neolloydia matehualensis	Echinocactus matehualensis, Coryphantha matehualensis	14	DD	0	8	0.00	100.00	187937	0.35	0.66	0.86	0.00	0.00
54	Obregonia denegrii	Ariocarpus denegrii, Strombocactus denegrii	16	EN	0	16	0.00	100.00	353	0.00	0.02	0.94	0.06	0.00
55	Opuntia megarrhiza	Platyopuntia megarrhiza, Nopalea megarrhiza	11	EN	0	11	0.00	100.00	20022	0.04	0.18	1.00	0.00	0.00
56	Opuntia microdasys	Cactus microdasys, Opuntia rufida	208	LC	20	183	9.85	90.15	141042	0.26	0.35	0.88	0.01	0.09
57	Opuntia pachyrrhiza	Platyopuntia pachyrrhiza, Nopalea pachyrrhiza	21	EN	2	19	9.52	90.48	59407	0.11	0.30	0.57	0.00	0.43
58	Opuntia rufida	Cactus rufidus, Opuntia microdasys var. rufida	100	LC	3	122	2.40	97.60	117388	0.22	0.17	0.80	0.00	0.13
59	Pelecyphora aselliformis	Mammillaria aselliformis, Encephalocarpus aselliformis	21	LC	0	21	0.00	100.00	1185	0.00	0.03	0.81	0.05	0.14
60	Pelecyphora strobiliformis	Mammillaria strobiliformis, Encephalocarpus strobiliformis	14	LC	1	13	7.14	92.86	14989	0.03	0.15	0.93	0.07	0.00
61	Sclerocactus mariposensis	Ancistrocactus mariposensis, Echinocactus mariposensis	16	LC	1	35	2.78	97.22	50098	0.09	0.16	0.63	0.06	0.31
62	Sclerocactus unguispinus	Ancistrocactus unguispinus, Echinocactus unguispinus	32	LC	3	28	9.68	90.32	122733	0.23	0.26	0.88	0.03	0.09
63	Stenocactus coptonogonus	Echinofossulocactus coptogonus, Echinocactus coptogonus	31	LC	6	20	23.08	76.92	62758	0.12	0.24	0.84	0.03	0.10
64	Strombocactus disciformis	Echinocactus disciformis, Mammillaria disciformis	29	VU	2	27	6.90	93.10	2481	0.00	0.06	0.86	0.00	0.14
65	Thelocactus bicolor	Thelocactus hexaedrophorus	132	LC	11	149	6.88	93.13	150368	0.28	0.21	0.88	0.00	0.10
66	Thelocactus conothelos	Echinocactus conothelos, Ferocactus conothelos	91	LC	0	81	0.00	100.00	4874	0.01	0.03	0.86	0.03	0.07
67	Thelocactus hexaedrophorus	Echinocactus hexaedrophorus, Ferocactus hexaedrophorus	118	LC	0	116	0.00	100.00	33940	0.06	0.10	0.92	0.01	0.08
68	Thelocactus rinconensis	Echinocactus rinconensis, Ferocactus rinconensis	22	LC	1	21	4.55	95.45	14696	0.03	0.11	0.86	0.00	0.14
69	Turbinicarpus knuthianus	Gymnocactus knuthianus, Echinocactus knuthianus	16	-	0	16	0.00	100.00	1025	0.00	0.04	0.94	0.00	0.06
70	Turbinicarpus pseudomacrochele	Gymnocactus pseudomacrochele, Echinocactus pseudomacrochele	11	EN	0	11	0.00	100.00	223	0.00	0.01	0.64	0.09	0.27
71	Turbinicarpus pseudopectinatus	Gymnocactus pseudopectinatus, Echinocactus pseudopectinatus	24	LC	0	24	0.00	100.00	24467	0.05	0.15	0.88	0.00	0.13
72	Turbinicarpus schmiedickeanus	Gymnocactus schmiedickeanus, Echinocactus schmiedickeanus	59	NT	0	59	0.00	100.00	6417	0.01	0.05	0.92	0.02	0.07
73	Turbinicarpus subterraneus	Gymnocactus subterraneus, Echinocactus subterraneus	6	EN	0	6	0.00	100.00	11925	0.02	0.14	1.00	0.00	0.00
74	Turbinicarpus valdezianus	Gymnocactus valdezianus, Echinocactus valdezianus	8	VU	0	8	0.00	100.00	27485	0.05	0.18	1.00	0.00	0.00
75	Turbinicarpus viereckii	Gymnocactus viereckii, Echinocactus viereckii	15	LC	0	15	0.00	100.00	2015	0.00	0.04	1.00	0.00	0.00
ADDENDUM Microareal & Non-Modelable Endemics						MAXENT Settings from R routines				MAXENT (Mod. Settings R routines	fc - model IG	rm - correction IG	fc - models G	rm - correction G
76	Acharagma aguirreana		6	CR		1	Ariocarpus agavoides			JK	H	4	LQH	2
77	Acharagma roseanum	Escobaria roseanum	5	VU		2	Ariocarpus fissuratus			JK	L	1	LQHPT	4
78	Ariocarpus bravoanus		19	EN		3	Ariocarpus kotschoubeyanus			JK	LQHPT	3	LQ	1
79	Ariocarpus scaphirostris		7	EN		4	Ariocarpus retusus			RKF	LQ	1	LQHPT	3
80	Ariocarpus trigonus		24	LC		5	Astrophytum capricorne			JK	LQHP	2	LQ	1
81	Aztekium hintonii		4	NT		6	Astrophytum myriostigma			RKF	LQHPT	2	LQ	1
82	Aztekium ritteri		7	LC		7	Astrophytum ornatum			JK	LQ	1	LQ	2
83	Coryphantha clavata		46	LC		8	Coryphantha difficilis			JK	L	2	LQ	1
84	Coryphantha wohlschlageri		5	LC		9	Coryphantha durangensis			JK	LQHP	5	LQHPT	2
85	Echinocereus poselgeri	Wilcoxia tuberosa	46	LC		10	Coryphantha macromeris			JK	L	1	L	2
86	Echinocereus waldeisii		5	-		11	Coryphantha octacantha			JK	LQ	2	LQ	1
87	Epithelantha bokei		14	LC		12	Coryphantha poselgeriana			RKF	L	1	LQ	2
89	Geohintonia mexicana		3	NT		13	Coryphantha pulleineana			JK	LQ	3	LQHPT	4
90	Mammillaria duwei		5	CR		14	Coryphantha werdermannii			JK	L	2	L	4
91	Mammillaria elongata		52	LC		15	Cumarinia odorata			JK	LQ	1	LQ	1
92	Mammillaria erythrosperma		9	LC		16	Echinocereus enneacanthus			RKF	LQHPT	2	LQ	1
93	Mammillaria glochidiata		2	CR		17	Echinocereus knippelianus			JK	LQ	1	LQ	1
94	Mammillaria marcosi		2	CR		18	Echinocereus pentalophus			RKF	LQHPT	1	LQHPT	2
95	Mammillaria microhelia		2	EN		19	Echinocereus stramineus			RKF	LQ	1	LQHPT	1
96	Mammillaria perezdelarosae		19	-		20	Echinocereus viereckii			JK	LQHPT	4	LQHPT	3
97	Mammillaria pilispina		49	LC		21	Epithelantha greggii			JK	LQHPT	2	LQH	3
98	Mammillaria pottsii		109	LC		22	Epithelantha micromeris			JK	L	4	LQ	1
99	Mammillaria prolifera		72	LC		23	Epithelantha spinosior			JK	LQH	4	LQHP	4
100	Mammillaria scheinvariana		1	-		24	Escobaria chihuahuensis			JK	L	4	L	1
101	Mammillaria tezontle		1	-		25	Escobaria dasyacantha			JK	LQ	2	LQ	1
102	Mammillaria weingartiana		7	LC		26	Ferocactus echidne			RKF	LQHPT	3	L	3
103	Mammillaria wrightii		30	LC		27	Ferocactus hamatacanthus			RKF	LQHPT	2	LQ	1
104	Mammillaria zahniana		2	-		28	Ferocactus pilosus			RKF	LQ	1	LQHPT	2
105	Opuntia anteojoensis		12	VU		29	Homalocephala parryi			JK	H	3	LQ	1
106	Opuntia xandersonii		27	-		30	Leuchtenbergia principis			JK	LQ	1	LQ	1
107	Sclerocactus warnockii		32	LC		31	Lophophora diffusa			JK	LQH	1	LQ	1
108	Strombocactus corregidorae		4	-		32	Lophophora williamsii			RKF	LQ	1	LQ	1
109	Thelocactus alonsoi		1	-		33	Mammillaria albicoma			JK	LQ	2	LQ	2
110	Thelocactus horripilus		8	-		34	Mammillaria baumii			JK	LQ	1	LQ	1
111	Thelocactus lausseri		1	DD		35	Mammillaria bocasana			JK	L	1	LQ	2
112	Rapicactus beguinii		57	LC		36	Mammillaria compressa			RKF	LQHPT	2	LQ	1
113	Turbinicarpus gielsdorfianus		3	CR		37	Mammillaria formosa			RKF	LQHPT	2	LQHPT	1
114	Turbinicarpus hoferi		5	CR		38	Mammillaria gigantea			JK	LQ	1	LQ	1
115	Turbinicarpus iysabelae		5	-		39	Mammillaria glassii			JK	LQ	1	LQ	2
116	Turbinicarpus lophophoroides		4	NT		40	Mammillaria klissingiana			JK	H	5	LQ	1
117	Turbinicarpus mandragora		1	CR		41	Mammillaria lenta			JK	L	2	LQ	1
118	Turbinicarpus swobodae		1	CR		42	Mammillaria moelleriana			JK	L	5	H	3
119	Turbinicarpus xmombergeri		1	-		43	Mammillaria parkinsonii			JK	LQ	1	LQ	1
120	Turbinicarpus zaragozae		1	-		44	Mammillaria perbella			JK	LQ	2	LQ	1
						45	Mammillaria picta			RKF	LQ	1	LQ	1
						46	Mammillaria plumosa			JK	LQH	2	LQH	3
						47	Mammillaria pottsii			RKF	L	1	L	1
						48	Mammillaria schiedeana			RKF	LQ	1	LQ	1
						49	Mammillaria sphaerica			JK	L	2	L	2
						50	Mammillaria surculosa			JK	LQ	1	LQ	2
						51	Neobuxbaumia euphorbioides			JK	LQHP	1	H	3
						52	Neobuxbaumia polylopha			JK	LQH	2	L	1
						53	Neolloydia matehualensis			JK	LQ	1	H	3
						54	Obregonia denegrii			JK	LQ	1	LQ	1
						55	Opuntia megarrhiza			JK	LQ	3	LQ	1
						56	Opuntia microdasys			RKF	LQHPT	2	LQHPT	3
						57	Opuntia pachyrrhiza			JK	LQ	1	LQ	1
						58	Opuntia rufida			RKF	LQHPT	2	LQ	1
						59	Pelecyphora aselliformis			JK	LQ	1	LQHP	1
						60	Pelecyphora strobiliformis			JK	LQHPT	4	LQ	1
						61	Sclerocactus mariposensis			JK	LQ	1	L	1
						62	Sclerocactus unguispinus			JK	LQH	4	L	3
						63	Stenocactus coptonogonus			JK	LQH	2	LQ	1
						64	Strombocactus disciformis			JK	LQ	1	LQ	1
						65	Thelocactus bicolor			RKF	LQHPT	2	LQ	2
						66	Thelocactus conothelos			RKF	LQ	1	LQHPT	3
						67	Thelocactus hexaedrophorus			RKF	LQ	1	LQ	1
						68	Thelocactus rinconensis			JK	LQ	1	LQ	1
						69	Turbinicarpus knuthianus			JK	LQ	1	LQH	1
						70	Turbinicarpus pseudomacrochele			JK	L	1	LQ	2
						71	Turbinicarpus pseudopectinatus			JK	LQ	1	LQ	1
						72	Turbinicarpus schmiedickeanus			RKF	LQ	1	LQ	1
						73	Turbinicarpus subterraneus			JK	LQHPT	4	LQ	2
						74	Turbinicarpus valdezianus			JK	H	2	LQ	2
						75	Turbinicarpus viereckii			JK	LQ	2	LQ	1

* R routines were revised with the adivce of J. Banta, University of Texas. Non-modelable species usually have one or two sites. Detail on analyses are available by request, and the complete set of MAXENT SDMs, and fine layers, could be consulted in the digital SM.