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12 pages, 4507 KiB  
Article
Femoroacetabular Impingement Morphological Changes in Sample of Patients Living in Southern Mexico Using Tomographic Angle Measures
by Ricardo Cardenas-Dajdaj, Arianne Flores-Rivera, Marcos Rivero-Peraza and Nina Mendez-Dominguez
Tomography 2024, 10(12), 1947-1958; https://doi.org/10.3390/tomography10120141 - 3 Dec 2024
Viewed by 324
Abstract
Background: Femoroacetabular impingement (FAI) is a condition caused by abnormal contact between the femur head and the acetabulum, which damages the labrum and articular cartilage. While the prevalence and the type of impingement may vary across human groups, the variability among populations with [...] Read more.
Background: Femoroacetabular impingement (FAI) is a condition caused by abnormal contact between the femur head and the acetabulum, which damages the labrum and articular cartilage. While the prevalence and the type of impingement may vary across human groups, the variability among populations with short height or with a high prevalence of overweight has not yet been explored. Latin American studies have rarely been conducted in reference to this condition, including the Mayan and mestizo populations from the Yucatan Peninsula. Objective: We aimed to describe the prevalence of morphological changes in femoroacetabular impingement by measuring radiological angles in abdominopelvic tomography studies in a sample of patients from a population with short height. Methods: In this prospective study, patients with programmed abdominopelvic tomography unrelated to femoroacetabular impingement but with consistent symptoms were included. Among the 98 patients, the overall prevalence of unrelated femoroacetabular impingement was 47%, and the pincer-type was the most frequent. The cam-type occurred more frequently among individuals with taller stature compared to their peers. Alpha and Wiberg angles predicted cam- and pincer-type, respectively, with over 0.95 area under the curve values in ROC analyses. The inter-rater agreement in the study was >91%. Conclusions: In a patient population from Yucatan, Mexico, attending ambulatory consultations unrelated to femoroacetabular impingement, an overall morphological changes prevalence of 47% was observed. Angle measurements using tomographic techniques can be used to predict cam- and pincer-type femoroacetabular impingement. Average stature was observed to be shorter in patients with cam-type femoroacetabular impingement, but body mass index did not vary between groups. Full article
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<p>Computed tomography image with 3D volumetric reconstruction showing anterosuperior bony prominence in the cervical–cephalic transition of the bilateral femur, as well as bone excrescence in the right acetabular roof. Findings in relation to right mixed-type and left cam-type femoroacetabular impingement are marked with white arrowheads.</p>
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<p>Computed tomography image showing bilateral pincer-type femoroacetabular impingement with coronal reconstruction and window for bone tissues, where acetabular over-coverage was identified with a center-right edge angle of 57.7° and a left angle of 47°. In addition, a stone was observed in the left ureter and a right double J catheter.</p>
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<p>Measurement of the center-edge angle (Wiberg) in an asymptomatic patient. An angle is obtained starting from the center of the femoral head, with a stroke following the vertical axis of the same (90°) and the lateral edge of the acetabulum. The normal value is less than 40°.</p>
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<p>Measurement of the Alpha angle in a patient with femoroacetabular cam impingement. The angle is obtained from the start of the middle femoral head by means of a linear stroke that runs through the center of the femoral neck and another to the point where the sphericity is lost at the junction between the head and the neck. The normal value is equal to or less than 50°.</p>
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<p>ROC analyses reporting area under the curve values for three predictors of FAI. (<b>A</b>) Left Pincer, (<b>B</b>) Right Pincer, (<b>C</b>) Left Cam, (<b>D</b>) Right Cam.</p>
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14 pages, 1776 KiB  
Review
Mangrove Area Trends in Mexico Due to Anthropogenic Activities: A Synthesis of Five Decades (1970–2020)
by Pablo Antúnez
Coasts 2024, 4(4), 726-739; https://doi.org/10.3390/coasts4040038 - 28 Nov 2024
Viewed by 511
Abstract
This paper presents a meta-analysis of mangrove area in Mexico, using linear mixed models to assess trends from 1970 to 2020. The objective is to highlight the changes in the extent of these vital ecosystems over the past five decades. The analysis reveals [...] Read more.
This paper presents a meta-analysis of mangrove area in Mexico, using linear mixed models to assess trends from 1970 to 2020. The objective is to highlight the changes in the extent of these vital ecosystems over the past five decades. The analysis reveals a concerning decline of approximately 163.33 hectares per year from 1970 to 2005. Although a rebound was observed starting in 2016—likely due to effective conservation efforts—these ecosystems continue to decline overall. The states that have shown a consistent decline in mangrove area include Campeche, Sinaloa, Nayarit, Chiapas, Veracruz, Oaxaca, Guerrero, Colima, and Jalisco. Threats to mangroves vary significantly by region. In the North Pacific, the expansion of aquaculture farms has contributed to over 60% of mangrove loss. In contrast, the Yucatán Peninsula faces challenges from urban development, oil exploitation, and road expansion. Additionally, tourism activities have severely impacted the states of Colima, Jalisco, Guerrero, and Quintana Roo. In the Gulf of Mexico, the primary threats include aquaculture, transportation routes, and hydraulic infrastructure. Based on these findings, seven action strategies for the ecological restoration of mangroves are proposed. These strategies, drawn from successful case studies and existing literature, include: comprehensive restoration initiatives, expansion of research and data sources, updates to current regulations, regulation of anthropogenic activities, inter-institutional coordination, education and awareness-raising efforts, and continuous monitoring and evaluation. Full article
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<p>Map of the five regions in Mexico with mangrove forests, adapted from CONABIO’s 2020 map.</p>
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<p>(<b>A</b>) Net change in mangrove area in Mexico from 1996 to 2020, based on Global Mangrove Watch data, and (<b>B</b>) Trend of marginal mean mangrove area from 1970 to 2020, derived from a generalized linear mixed model based on historical records compiled by CONABIO [<a href="#B10-coasts-04-00038" class="html-bibr">10</a>].</p>
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<p>Marginal means calculated from a linear mixed-effects model of disturbed mangrove surface area from 1970 to 2020, using years as a fixed effect and states as a random effect.</p>
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<p>Boxplots showing anthropogenic activities driving mangrove area loss in Mexico (2005–2015). (<b>A</b>) Activities contributing to mangrove loss from 2005 to 2015. (<b>B</b>) Comparison of the most impactful activities in 2005, 2010 and 2015. Act. 1 is airports and runways; Act. 2 is aquaculture farms and artificial ponds; Act. 3 is hydraulic infrastructure; Act. 4 is Settlements; Act. 5 is transport; Act. 6 is Building zones; Act. 7 is industrial zones; Act. 8 is port zones; Act. 9 is touristic zones; and Act. 10 is Reclassification zones.</p>
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<p>Comparison of mangrove area between the initial year and the years 2005, 2010, 2012, 2015 and 2020.</p>
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24 pages, 8757 KiB  
Article
Characterization of Traditional Pottery Artifacts from Yucatán Peninsula, México: Implications for Manufacturing Process Based on Elemental Analyses
by Miguel Pérez, Oscar G. de Lucio, Hugo M. Sobral, Ciro Márquez-Herrera, Avto Goguitchaichvili and Soledad Ortiz
Minerals 2024, 14(10), 993; https://doi.org/10.3390/min14100993 - 30 Sep 2024
Viewed by 1241
Abstract
The present work is focused on developing and implementing a minimally invasive methodology for material characterization of traditional pottery from Yucatan, México. The developed methodology, which combines elemental (X-ray fluorescence spectroscopy (XRF), inductively coupled plasma-optical emission spectroscopy (ICP-OES), and Laser-Induced Breakdown Spectroscopy (LIBS)) [...] Read more.
The present work is focused on developing and implementing a minimally invasive methodology for material characterization of traditional pottery from Yucatan, México. The developed methodology, which combines elemental (X-ray fluorescence spectroscopy (XRF), inductively coupled plasma-optical emission spectroscopy (ICP-OES), and Laser-Induced Breakdown Spectroscopy (LIBS)) and molecular (fiber optic reflectance spectroscopy (FORS)) spectroscopic analytical techniques, allowed for the characterization of contemporary pottery objects manufactured following traditional recipes in the town of Uayma, Yucatán, México and raw materials associated with the pottery manufacturing process. The results allowed us to detect and estimate the number of selected elements and helped to infer the presence of complex materials such as iron oxides, aluminosilicates, and calcium carbonate. Additionally, the analysis indicated two pottery groups separated by their elemental and molecular composition, corresponding to the sources of raw materials employed by the potters. It confirmed the absence of toxic compounds in ceramic objects, a significant concern for potters, as some objects are intended for domestic use. The research findings provide reassurance about the safety of these products. Full article
(This article belongs to the Special Issue Geomaterials and Cultural Heritage)
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<p>Map of the Yucatán peninsula with the location of raw material samples collection areas. Raw material samples Y1, G2, B3, <span class="html-italic">Kut</span>, and <span class="html-italic">Sascab</span> were collected from Uayma. M1 from Yókát, M2 from Uayma, and M3 from Tepakán.</p>
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<p>Pottery from the workshop of the Espadas Xooc family.</p>
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<p>Microscopy image of five spots over the object’s surface, with an average size of 130 µm.</p>
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<p>Elements identified via XRF and their concentrations in the raw materials samples: Y1, G2, B3, M1, M2, M3, <span class="html-italic">Kut</span>, and <span class="html-italic">Sascab</span>. Error bars correspond to experimental uncertainties.</p>
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<p>Average concentration of XRF-identified elements in pottery objects. Error bars correspond to the standard deviation of the measurements in the set of samples.</p>
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<p>XRF element concentration for every pottery object and principal elements. (<b>a</b>) Al and Si, (<b>b</b>) Ca, (<b>c</b>) K, and (<b>d</b>) Fe.</p>
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<p>Biplot of principal component results from XRF measurements in pottery objects. Eigenvectors are associated with elements and score plots of objects. Two groups related principally to Ca and K and Si, Al, Fe, Ti, Zn, Sr, V, and Zr are formed.</p>
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<p>Mean concentration for elements identified in the set of pottery objects with ICP-OES, ordered from highest to lowest concentration. Error bars indicate the standard deviation from the set of objects for each element.</p>
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<p>The elemental concentration of pottery objects measured with ICP-OES. (<b>a</b>) Al with Si, (<b>b</b>) Ca, (<b>c</b>) Fe with Mg, and (<b>d</b>) K.</p>
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<p>The elemental concentration of pottery objects measured with ICP-OES. (<b>a</b>) Al with Si, (<b>b</b>) Ca, (<b>c</b>) Fe with Mg, and (<b>d</b>) K.</p>
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<p>Biplot of principal component results from ICP-OES measurements in pottery objects. PC2 vs. PC1 score plot with two clusters formed via <span class="html-italic">k-means</span> classification.</p>
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<p>Intensities of signals related to elements detected with LIBS analysis in pottery objects. The correlated elements were (<b>a</b>) Al with Si, (<b>b</b>) C with Ca, and (<b>c</b>) Mg with Fe.</p>
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<p>Biplot of principal component results from LIBS measurements in pottery objects. Score plots were classified into two groups via k-means clustering, and ellipses indicate 95% confidence. Vectors indicate the elements included in the analysis projected in the PC1 vs. PC2 plot.</p>
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<p>Comparison between each technique for the set of objects of the concentration of principal elements (<b>a</b>) Ca, (<b>b</b>) Fe, (<b>c</b>) Al, (<b>d</b>) Si, (<b>e</b>) Sr, (<b>f</b>) Ti, (<b>g</b>) K, (<b>h</b>) Mg. Graphs have common XRF and ICP concentration scales.</p>
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<p>Visible region spectra of (<b>a</b>) pottery object 2 and (<b>b</b>) pottery object 6 present the lowest and highest proportion of Fe, respectively. Derivatives were calculated to find the features associated with iron oxides easily.</p>
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<p>SWIR spectra FORS from representative pottery objects 4, 6, 15, and 19. Principal absorption bands are indicated. The reflectance spectrum of Montmorillonite clay is included for comparison.</p>
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<p>PCA score plot of analyzed reflectance data (FORS) from pottery objects. Inset indicates the region used for analysis.</p>
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<p>PCA biplot of PC1 vs. PC2 of XRF measurements of raw materials and pottery objects. Vectors indicate the elements identified (bold letters).</p>
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19 pages, 2275 KiB  
Article
Evaluating Thermal Infrared Drone Flight Parameters on Spider Monkey Detection in Tropical Forests
by Eduardo José Pinel-Ramos, Filippo Aureli, Serge Wich, Steven Longmore and Denise Spaan
Sensors 2024, 24(17), 5659; https://doi.org/10.3390/s24175659 - 30 Aug 2024
Cited by 1 | Viewed by 1019
Abstract
Geoffroy’s spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and a high degree of fission–fusion dynamics, are challenging to survey in their natural habitats. Our objective was to evaluate how different flight parameters affect the detectability of spider [...] Read more.
Geoffroy’s spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and a high degree of fission–fusion dynamics, are challenging to survey in their natural habitats. Our objective was to evaluate how different flight parameters affect the detectability of spider monkeys in videos recorded by a drone equipped with a thermal infrared camera and examine the level of agreement between coders. We used generalized linear mixed models to evaluate the impact of flight speed (2, 4, 6 m/s), flight height (40, 50 m above ground level), and camera angle (−45°, −90°) on spider monkey counts in a closed-canopy forest in the Yucatan Peninsula, Mexico. Our results indicate that none of the three flight parameters affected the number of detected spider monkeys. Agreement between coders was “substantial” (Fleiss’ kappa coefficient = 0.61–0.80) in most cases for high thermal-contrast zones. Our study contributes to the development of standardized flight protocols, which are essential to obtain accurate data on the presence and abundance of wild populations. Based on our results, we recommend performing drone surveys for spider monkeys and other medium-sized arboreal mammals with a small commercial drone at a 4 m/s speed, 15 m above canopy height, and with a −90° camera angle. However, these recommendations may vary depending on the size and noise level produced by the drone model. Full article
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<p>Map of Los Arboles Tulum, Tulum, Mexico, with 2 ha lots (white lines) showing the drone take-off and landing points (white dots with a black center) and flight routes (yellow lines) over five spider monkey sleeping sites (red squares) where we tested the effect of three flight parameters on spider monkey detectability.</p>
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<p>(<b>a</b>) Drone at height H with camera pointing directly down (−90°). The value <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mn>90</mn> </mrow> </msub> </mrow> </semantics></math> is the distance on the ground subtended by a camera with an angular field of view <span class="html-italic">θ</span>. (<b>b</b>) Side-on view of drone at height H facing toward the right, with the center of the camera field of view pointing an angle of <span class="html-italic">ϕ</span>. <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math> is the distance on the ground from directly below the drone to the nearest point of the drone’s field of view. <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>D</mi> </mrow> <mrow> <mi>N</mi> </mrow> <mrow> <mi>G</mi> </mrow> </msubsup> </mrow> </semantics></math> is the distance from the drone to this point, with G being ground. <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>M</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math> are the distances on the ground from directly below the drone to the middle (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>M</mi> </mrow> </msub> </mrow> </semantics></math>) and farthest (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math>) point on the drone’s field of view. The angle <span class="html-italic">χ</span> is an arbitrary angle between zero and <span class="html-italic">θ</span> to generalize the mathematical expressions. (<b>c</b>) Reprojected view of (<b>b</b>), rotated to show the width (W) of the field of view on the ground at the point nearest to the drone, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>D</mi> </mrow> <mrow> <mi>N</mi> </mrow> <mrow> <mi>W</mi> </mrow> </msubsup> </mrow> </semantics></math>.</p>
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<p>Examples of (<b>a</b>) high thermal contrast zones and (<b>b</b>) low thermal contrast zones, and how the spider monkeys appear in the videos (inside the white circle).</p>
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<p>Spider monkeys (within white circles) in TIR drone footage under different combinations of flight height and camera angle: (<b>a</b>) 50 m and −90°, (<b>b</b>) 40 m and −90°, (<b>c</b>) 50 m and −45°, and (<b>d</b>) 40 m and −45°.</p>
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<p>Level of agreement between coders for different flight parameter combinations for high (blue points) and low (orange point) thermal contrast zones. Gray points indicate that both contrast zones had the same level of agreement. The categories of level of agreement between coders on the <span class="html-italic">y</span>-axis are as follows: SL (slight), F (fair), M (moderate), SU (substantial), AP (almost perfect). The values of the flight parameter combinations on the <span class="html-italic">x</span>-axis are presented in the following order: flight speed (m/s), flight height (m a.g.l.), and camera angle (°).</p>
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25 pages, 11888 KiB  
Article
Hydrogeophysical Evaluation of the Karst Aquifer near the Western Edge of the Ring of Cenotes, Yucatán Peninsula
by Jorge Adrián Perera-Burgos, Luis Gerardo Alvarado-Izarraras, Juan Carlos Mixteco-Sánchez, César Canul-Macario, Gilberto Acosta-González, Alfredo González-Calderón, Jesús Horacio Hernández-Anguiano and Yanmei Li
Water 2024, 16(14), 2021; https://doi.org/10.3390/w16142021 - 17 Jul 2024
Viewed by 1587
Abstract
In this work, electrical resistivity tomography was carried out together with physical hydrogeology techniques to evaluate the karst aquifer in the northwest region of the Yucatán Peninsula in a study area near the western edge of the Ring of Cenotes of the Chicxulub [...] Read more.
In this work, electrical resistivity tomography was carried out together with physical hydrogeology techniques to evaluate the karst aquifer in the northwest region of the Yucatán Peninsula in a study area near the western edge of the Ring of Cenotes of the Chicxulub Crater. In addition, based on a systematic compilation of open-access data of water levels reported for the peninsular aquifer, maps of groundwater isolines and groundwater flows were generated using IDW interpolation, Empirical Bayesian Kriging, and the Flow Net method. From these results, a shallow aquifer is observed, with the presence of heterogeneities such as possible dissolution conduits and/or flooded caverns, approximately 20 m below ground level, formed by the dissolution processes of limestone rocks. On a regional scale, the geomorphological influence of the Ring of Cenotes on groundwater flows was observed. In general, the flow directions observed from these maps coincide with those conceptualized for this region of the peninsular aquifer. Nevertheless, some differences were observed depending on the interpolation method used. Our results contribute to hydrogeological studies carried out in the periphery of this ring, where the vulnerability of the aquifer to anthropogenic contamination has been highlighted due to the intrinsic features of the karst environment. Full article
(This article belongs to the Section Hydrogeology)
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<p>(<b>a</b>) Location of the hydrogeophysical study site in the northwestern region of the YP, (<b>b</b>) close-up of the study site, and (<b>c</b>) real orientations of ERT transects.</p>
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<p>(<b>a</b>) Classification of the geological formations of the Yucatán Peninsula. (<b>b</b>) Map of surface geology and conceptual regional groundwater flows of the YP. Image modified from [<a href="#B5-water-16-02021" class="html-bibr">5</a>]. The colors between both figures indicate the respective geological formations. The geological information was obtained from the SGM (01 of 12 of 2007); State Geological-Mining Chart, Campeche, Quintana Roo, Yucatán, SC. 1:500,000.</p>
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<p>(<b>a</b>) Interpretation of the real 2D resistivity profiles for transect T1 with a north–south orientation (ERT 1). (<b>b</b>) Interpretation of the real 2D resistivity profiles for transect T2 with an east–west orientation (ERT 2).</p>
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<p>Effective porosity sections obtained from profiles (<b>a</b>) ERT-1 and (<b>b</b>) ERT-2.</p>
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<p>Groundwater levels for the northwest aquifer of the Yucatán Peninsula considering a steady-state approximation. (<b>a</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> and (<b>b</b>) Empirical Bayesian Kriging.</p>
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<p>Groundwater flows on a regional scale for the northwest aquifer of the Yucatán Peninsula considering a steady-state approximation and an isotropic porous medium. (<b>a</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> and (<b>b</b>) Empirical Bayesian Kriging.</p>
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<p>(<b>a</b>,<b>b</b>) Interpretation of the real 2D resistivity profiles for transect T1 with a north–south orientation (ERT 1) using ZondRes2D and Res2DInv software, respectively. (<b>c</b>,<b>d</b>) Interpretation of the real 2D resistivity profiles for transect T2 with an east–west orientation (ERT 2) using ZondRes2D and Res2DInv, respectively.</p>
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<p>Groundwater levels for the northwest aquifer of the Yucatán Peninsula considering a steady-state approximation. (<b>a</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>b</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>1.5</mn> </mrow> </semantics></math>.</p>
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<p>Groundwater flows on a regional scale for the northwest aquifer of the Yucatán Peninsula considering a steady-state approximation and an isotropic porous medium. (<b>a</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and (<b>b</b>) IDW interpolation with <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>1.5</mn> </mrow> </semantics></math>.</p>
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<p>(<b>a</b>) Cross-validation between observed and predicted water levels and (<b>b</b>) QQ plot of the data.</p>
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<p>Location of some sites with CONAGUA monitoring wells. (<b>a</b>) Map of the zone, indicating the study site, and the well sites; (<b>b</b>–<b>d</b>) salinity profiles for wells P1, P4, and P6, respectively.</p>
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25 pages, 9871 KiB  
Article
Investigating the Morphometry and Hydrometeorological Variability of a Fragile Tropical Karstic Lake of the Yucatán Peninsula: Bacalar Lagoon
by Laura Carrillo, Mario Yescas, Mario Oscar Nieto-Oropeza, Manuel Elías-Gutiérrez, Juan C. Alcérreca-Huerta, Emilio Palacios-Hernández and Oscar F. Reyes-Mendoza
Hydrology 2024, 11(5), 68; https://doi.org/10.3390/hydrology11050068 - 11 May 2024
Cited by 1 | Viewed by 1888
Abstract
Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more [...] Read more.
Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more than 52.7 km in length, with widths varying from 0.18 km to 2.28 km. It has a volume of 554.4 million cubic meters, with an average depth of 8.85 m, reaching depths of up to 26 m in the north and featuring sub-lacustrine dolines in the south, with depths of 38 m, 48.5 m, and 63.6 m. The study reveals seasonal variations in surface water temperature, closely linked to air temperature (r = 0.89), and immediate responses of water levels to hydrometeorological events. Water level fluctuations also exhibit seasonal patterns that are correlated with regional aquifer conditions, with a lag of 2 months after seasonal rainfall. Interannual variability in rainfall and water levels was observed. From 2010 to 2012, rainfall consistently remained below its mean climatic value, due to a prolonged La Niña event, while the exceptionally wet conditions in 2020 were also associated with La Niña. Extreme and anomalous hydrometeorological events, such as those following tropical storm Cristobal in 2020, revealed the fragility of Bacalar Lagoon, causing a notable transformation in lake color and transparency, shifting it from its typical oligotrophic state to eutrophic conditions that lasted longer than a year. These color changes raise questions about the factors impacting ecological health in tropical karstic regions. Additional factors affecting water quality in the BL in 2020, such as deforestation, coastline changes, and urban growth, warrant further investigation. Our study can serve as a starting landmark. Full article
(This article belongs to the Topic Karst Environment and Global Change)
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<p>Study area. Locations mentioned in the text are shown. The red line corresponds to the Hondo River fault. The Yucatán Peninsula in the upper-left corner shows gray background shading, indicating relative topographic elevation, with white as the highest. The red circles show the submerged dolines, called Cenotes.</p>
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<p>Time series of monthly (<b>a</b>) air temperature (°C) and (<b>b</b>) rainfall (mm) from the in situ ECOSUR meteorological station (red lines) and MERRA-2 data (blue lines) for the period from 15 February 2009 to 15 December 2013.</p>
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<p>Hypsographic curve (red line) and percentage of cumulative volume (black line) of Bacalar Lagoon.</p>
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<p>Bathymetric map of Bacalar Lagoon’s main basin. The values of the level curves are given by the color scale. Depth in meters. (<b>a</b>) Northern section of BL, (<b>b</b>) southern section of BL.</p>
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<p>Transverse profiles of typical cross sections along Bacalar Lagoon’s main basin. Profile P4 includes coastal elevation (m). Coordinates centered at the center of the cross section: P1, 18.86719° N, 88.18827° W; P2, 18.8422° N, 88.25366° W; P3, 18.80577° N, 88.27345° W; P4, 18.72816° N, 88.34278° W; P5, 18.67161° N, 88.38439° W; P6, 18.61289° N, 88.42318° W.</p>
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<p>Bathymetric details of the three submerged dolines in Bacalar Lagoon from left to right: Cenote Negro (18.6672° N, 88.3945° W), Cenote Esmeralda (18.6549° N, 88.4050° W), and Cenote Cocalitos (18.6500° N, 88.4096° W). The top panels show the three-dimensional structure of the Cenote, the central panels show the detailed bathymetry (m) and the contours are every 5 m for Cenote Negro and Cenote Esmeralda, but every 2 m for Cenote Cocalitos. The bottom panels show the cross-sections of the minor axis (A, dashed line in the bathymetric map) and major axis (B, dashed line in the bathymetric map) for each Cenote. The depth and northing/easting coordinates (UTM16N) are given in meters.</p>
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<p>Climatology estimated from 41 years of MERRA2 data (January 1981–31 December 2022) of (<b>a</b>) air temperature (°C), monthly mean (solid red line), with minimum and maximum values (dashed lines); (<b>b</b>) relative humidity (%) (dotted line indicates the mean relative humidity value of 77.77); and (<b>c</b>) rainfall (mm/month).</p>
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<p>Time series for the period from 25 May 2010 to 31 May 2012 of (<b>a</b>) daily air temperature (°C) and (<b>b</b>) daily water temperature (°C) (gray line), fitted Fourier annual curve (blue dashed line), and fitted Fourier annual and semi-annual curve (red line). (<b>c</b>) Daily water level (m) (gray line), fitted Fourier annual curve (blue dashed line), and fitted Fourier annual and semi-annual curve (red line). Positive water level values are shaded in blue, while negative water level values are shaded in red. (<b>d</b>) Daily rainfall. Events with precipitation above 50 mm are identified and labeled: (1) Hurricane Alex (26 June 2010—51.49 mm); (2) Tropical Wave 18 (26 July 2010—138.32 mm); (3) Hurricane Karl (15 September 2010—118.80 mm); (4) Tropical Wave 3 (18 June 2011—58.22 mm); (5) Tropical wave 4 and influence of tropical storm Arlene (5 July 2011—55.53 mm); (6) Cold front 6/remains of tropical depression 12-E (13 October 2011—56.20 mm); and (7) Cold front 45 (17 April 2012—81.11 mm).</p>
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<p>(<b>a</b>) Monthly Water Storage Anomaly (m) for the Yucatán Basin time series (blue line) and in situ water level (m) for Bacalar Lagoon (red line). The red dashed line represents the reconstructed water level (m) at Bacalar Lagoon. (<b>b</b>) Monthly rainfall (mm); the dashed line indicates 300 mm. (<b>c</b>) Monthly Rainfall Anomaly Index (RAI), blue bars represent positive anomalies, while red bars represent negative anomalies. (<b>d</b>) Multivariate El Niño–Southern Oscillation (ENSO) Index (MEI). Positive MEI values in red represent El Niño events. Negative MEI values in blue represent La Niña events.</p>
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<p>(<b>a</b>) Historical Secchi disk measurements (1997–2021), depth in meters. (<b>b</b>) Aerial photographs taken with a Mavic 2 drone from the southern site at 18.6776° N, 88.3885° W (Bacalar Town) on 4 March 2019 (A) and 20 July 2020 (B). Sentinel-2 Optimized L1C True Color images covering Bacalar Lagoon and the northern lagoons of Chile Verde, Salada, Guerrero, and the northern area of Chetumal Bay. The dates correspond to 14 February 2019 (C) and 13 July 2020 (D). Images with less than 30% cloud cover were included.</p>
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<p>The left panel shows a sequence of aerial georeferenced photographs taken with a Mavic 2 drone from the northern site located at 18.8646° N, 88.2466° W (near Buenavista). (<b>a</b>) 4 March 2019; (<b>b</b>) 20 July 2020; (<b>c</b>) 20 October 2020; and (<b>d</b>) 20 June 2021. The selected area for RGB analysis is represented as a dashed red rectangle. The right panel (<b>e</b>–<b>h</b>) shows the histogram of RGB, related to the area extracted from each aerial photo. Red channel (red line), green channel (green line), and blue channel (blue line).</p>
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19 pages, 4455 KiB  
Article
Connecting Water Quality and Ecosystem Services for Valuation and Assessment of a Groundwater Reserve Area in South-East Mexico
by Myrna L. López-Monzalvo, Eduardo Batllori-Sampedro, Jairo A. Ayala-Godoy, Eugenio Guerrero-Ruiz and Laura M. Hernández-Terrones
Water 2024, 16(10), 1358; https://doi.org/10.3390/w16101358 - 10 May 2024
Cited by 1 | Viewed by 1583
Abstract
Even though the role of ecosystem services is known, the identification and assessment of water-related services is usually absent or often less represented as an ecosystem service. Progress in water quality indicator definition and compliance with regulations has been made; however, the relationship [...] Read more.
Even though the role of ecosystem services is known, the identification and assessment of water-related services is usually absent or often less represented as an ecosystem service. Progress in water quality indicator definition and compliance with regulations has been made; however, the relationship between water quality degradation and benefits to individuals and ecosystems remains little recognized. Here, we present an assessment of water quality and identification of ecosystem services in south-east Mexico. This study was performed within the geohydrological reserve zone of the Ring of Sinkholes, Yucatán Peninsula. Thirteen ecosystem services provided by the aquifer were identified. Water quality was evaluated in sinkholes based on national and international norms, considering different sinkhole uses. Results show a dynamic system, without saltwater intrusion and good to excellent water quality. The research demonstrates the relationship between ecosystem services and water quality, showing pressure in services related to uses for aquatic life protection and to a lesser extent those related to consumption. Current productive activities showed no pressure at this time. Principal Component Analysis (PCA) and Analysis of Variance (ANOVA) exhibited a significant difference in parameters and campaigns, but not between sinkholes. A long-lasting monitoring program for water quality is necessary to accurately evaluate the status of ecosystem services provided by the aquifer. Moreover, it is necessary to assess aquifers as ecosystems with economic, ecologic and socio-cultural importance. Effective water governance requires a balance of interests between all parties, within a legal and institutional framework. Full article
(This article belongs to the Section Water Quality and Contamination)
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<p>The geohydrological reserve area, the study sites and meteorological station locations.</p>
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<p>Ecosystem services identified by the participants interviewed.</p>
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<p>Plot of the eigenvector projections on the first two principal components and classifications by <span class="html-italic">k</span>-means.</p>
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<p>Biplot of the eigenvectors projections on the first two principal components and clustering by campaign.</p>
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<p>Total annual precipitation at each meteorological station for the years 2010 to 2017.</p>
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15 pages, 1916 KiB  
Article
Potential Anti-Infectious Activity of Essential Oil Chemotypes of Lippia origanoides Kunth on Antibiotic-Resistant Staphylococcus aureus Strains
by Andrés Humberto Uc-Cachón, Luz María Calvo-Irabien, Angel de Jesús Dzul-Beh, Haziel Eleazar Dzib-Baak, Rosa Grijalva-Arango and Gloria María Molina-Salinas
Plants 2024, 13(9), 1172; https://doi.org/10.3390/plants13091172 - 23 Apr 2024
Cited by 1 | Viewed by 1693
Abstract
Staphylococcus aureus infections are prevalent in healthcare and community environments. Methicillin-resistant S. aureus is catalogued as a superbug of high priority among the pathogens. This Gram-positive coccus can form biofilms and produce toxins, leading to persistent infection and antibiotic resistance. Limited effective antibiotics [...] Read more.
Staphylococcus aureus infections are prevalent in healthcare and community environments. Methicillin-resistant S. aureus is catalogued as a superbug of high priority among the pathogens. This Gram-positive coccus can form biofilms and produce toxins, leading to persistent infection and antibiotic resistance. Limited effective antibiotics have encouraged the development of innovative strategies, with a particular emphasis on resistance mechanisms and/or virulence factors. Medicinal aromatic plants have emerged as promising alternative sources. This study investigated the antimicrobial, antibiofilm, and antihemolysis properties of three different chemotypes of Lippia origanoides essential oil (EO) against susceptible and drug-resistant S. aureus strains. The chemical composition of the EO was analyzed using GC-MS, revealing high monoterpene concentrations, with carvacrol and thymol as the major components in two of the chemotypes. The third chemotype consisted mainly of the sesquiterpene β-caryophyllene. The MIC values for the two monoterpene chemotypes ranged from 62.5 to 500 µg/mL for all strains, whereas the sesquiterpene chemotype showed activity against seven strains at concentrations of 125–500 µg/mL, which is the first report of its anti-S. aureus activity. The phenolic chemotypes inhibited biofilm formation in seven S. aureus strains, whereas the sesquiterpene chemotype only inhibited biofilm formation in four strains. In addition, phenolic chemotypes displayed antihemolysis activity, with IC50 values ranging from 58.9 ± 3.8 to 128.3 ± 9.2 µg/mL. Our study highlights the importance of L. origanoides EO from the Yucatan Peninsula, which has the potential for the development of anti-S. aureus agents. Full article
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<p>Antihemolysis activity of the <span class="html-italic">L. origanoides</span> EO on <span class="html-italic">S. aureus.</span> Car: carvacrol; Thy: thymol; average IC<sub>50</sub> values (±SD) with the same letter showed non-significant differences in the post hoc Tukey test (<span class="html-italic">p</span> &lt; 0.05). The sesquiterpene chemotype IC<sub>50</sub> is &gt;250 µg/mL for both strains.</p>
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<p>Flowchart of the methodology.</p>
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24 pages, 9857 KiB  
Article
Seasonality of Marine Litter Hotspots in the Wider Caribbean Region
by Xiaobiao Xu, Eric P. Chassignet, Philippe Miron and Olmo Zavala-Romero
J. Mar. Sci. Eng. 2024, 12(2), 319; https://doi.org/10.3390/jmse12020319 - 13 Feb 2024
Cited by 2 | Viewed by 1517
Abstract
The persistent increase in marine plastic litter has become a major global concern, with one of the highest plastic concentrations in the world’s oceans found in the Wider Caribbean Region (WCR). In this study, we use marine plastic litter tracking simulations to investigate [...] Read more.
The persistent increase in marine plastic litter has become a major global concern, with one of the highest plastic concentrations in the world’s oceans found in the Wider Caribbean Region (WCR). In this study, we use marine plastic litter tracking simulations to investigate where marine plastic accumulates, i.e., hotspots, in the WCR and how the accumulation varies on seasonal timescales. We show that most of the marine plastic waste converges on the coastlines shortly after being released into the WCR because of the strong surface current and the predominant easterly winds. Major plastic accumulations take place along (i) the western coastline of the WCR, especially the north–south-oriented coasts of Costa Rica/Nicaragua, Guatemala/Belize/Mexico, and Texas, and (ii) the coastlines of Haiti–Dominican Republic and Venezuela. Relatively low plastic accumulation is found along western Florida, the western Yucatán peninsula, and the leeward and windward Caribbean islands. Accumulation along the western WCR coastlines is modulated primarily by ocean currents and exhibits significant seasonal variabilities due to changes in wind patterns. The accumulation observed on the Haiti–Dominican Republic and Venezuela coastlines is primarily due to the proximity of large, mismanaged plastic waste sources. Finally, we discuss the uncertainty associated with the choices made in defining the different criteria for plastic beaching in the models. Full article
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<p>Wider Caribbean Region and transboundary lines delineating exclusive economic zones (EEZ), from Ambrose [<a href="#B20-jmse-12-00319" class="html-bibr">20</a>].</p>
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<p>Time averaged (<b>a</b>) ocean surface circulation and (<b>b</b>) near-surface wind in the Wider Caribbean Region (WCR) over 2010–2021. The ocean circulation is from the global ocean forecasting system (GOFS3.1) reanalysis, and the wind is from the US Navy Global Environmental Model (NAVGEM).</p>
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<p>Spatial distribution of (<b>a</b>) land-based and (<b>b</b>) river-based mismanaged plastic waste (MPW, in tons) sources into the WCR domain. The results are from Lebreton and Andrady [<a href="#B48-jmse-12-00319" class="html-bibr">48</a>] and Lebreton et al. [<a href="#B49-jmse-12-00319" class="html-bibr">49</a>], respectively.</p>
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<p>Examples of the MPW particle trajectories on 2013-02-20 from (<b>a</b>) GLB, (<b>b</b>) REALISTIC, and (<b>c</b>) UNIFORM. All the particles were released on 2013-01-01, and for (<b>a</b>) GLB and (<b>b</b>) REALISTIC, only the particles released from the WCR countries are included. The particle trails for the last 10 days are shown in blue, with the end positions marked with black circles and the beached particles with red dots.</p>
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<p>(<b>a</b>) Percentage of the beached MPW particles as a function of time after being released into the WCR in the GLB, REALISTIC, and UNIFORM experiments, averaged for the releases from 2010 to 2020. (<b>b</b>) Percentage of the beached MPW particles 6 months after being released (x axis) into the WCR for each release in the GLB, REALISTIC, and UNIFORM experiments.</p>
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<p>Number of beached MPW particles in 2010–2021 in the UNIFORM experiment, in which MPW particles were released uniformly along the coastline of the WCR domain.</p>
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<p>Distribution of beached MPW (in tons) in 2010–2021 from the particles that were released from the WCR countries in the (<b>a</b>) REALISTIC and (<b>b</b>) UNIFORM experiments; panel (<b>c</b>) shows their difference (red indicates more beached MPW in REALISTIC and vice versa).</p>
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<p>The distribution of beached MPW (in tons) in 2010–2021 in the REALISTIC experiment, as in <a href="#jmse-12-00319-f007" class="html-fig">Figure 7</a>a, but from the particles that were transferred into the WCR domain through northern and eastern boundaries. Note that the scale of the MPW is 10 times smaller than that in <a href="#jmse-12-00319-f007" class="html-fig">Figure 7</a>.</p>
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<p>Seasonal near-face wind anomalies (in m/s, relatively to annual means) averaged over 2010–2021 for (<b>a</b>) DJF (December to February), (<b>b</b>) MAM (March to May), (<b>c</b>) JJA (June to August), and (<b>d</b>) SON (September to November), corresponding to the seasonal MPW hotspots as shown in <a href="#jmse-12-00319-f010" class="html-fig">Figure 10</a>.</p>
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<p>Spatial distribution of beached MPW (in tons) that are beached along the WCR coastline in different seasons: (<b>a</b>) DJF (December to February), (<b>b</b>) MAM (March to May), (<b>c</b>) JJA (June to August), and (<b>d</b>) SON (September to November), based on the REALISTIC experiment over 2010–2021 (note that the scale is scaled by a factor of 4 to be comparable to the MPW accumulated for the full year).</p>
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<p>Thirty-day trajectories from one release (2010/01/01) in the REALISTIC experiment to illustrate the “beaching” criterion using a distance threshold of (<b>a</b>) 25 km and (<b>b</b>) 100 km, respectively. The particles that traveled less (more) than the corresponding threshold values are marked in red (blue) and are defined as beached (moving).</p>
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<p>Number of beached particles (in %) for each release in the REALISTIC experiment using distance threshold (red) and probability (blue) methods, respectively. The thick and thin lines are for the WCR particles and the boundary particles.</p>
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<p>Distribution of beached MPW (in tons) along using the probability method for (<b>a</b>) the WCR particles and (<b>c</b>) the boundary particles, and (<b>b</b>,<b>d</b>) the corresponding differences from using the 25 km distance threshold method (red indicates more beaching with the probability method than the distance method and vice versa for blue).</p>
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14 pages, 1806 KiB  
Article
Unraveling the Relative Contributions of Deterministic and Stochastic Processes in Shaping Species Community Assembly in a Floodplain and Shallow Hillslope System
by Gustavo Enrique Mendoza-Arroyo, René Efraín Canché-Solís, Alejandro Morón-Ríos, Mario González-Espinosa and Moisés Méndez-Toribio
Forests 2024, 15(2), 250; https://doi.org/10.3390/f15020250 - 28 Jan 2024
Cited by 1 | Viewed by 1332
Abstract
Understanding the process underlying species coexistence is crucial in ecology. This challenge is relevant in tree communities inhabiting contrasting abiotic conditions, such as lowland floodplain and shallow hillslope karstic systems. We examined the influence of topographic variables and spatial factors on the structure [...] Read more.
Understanding the process underlying species coexistence is crucial in ecology. This challenge is relevant in tree communities inhabiting contrasting abiotic conditions, such as lowland floodplain and shallow hillslope karstic systems. We examined the influence of topographic variables and spatial factors on the structure of tree communities in the karstic system in Calakmul, Mexico. We measured 7050 trees (diameter at breast height ≥ 3 cm) in 152 circular plots and generated seven topographic variables from a digital elevation model. We employed redundancy analysis and variance partitioning to test the effects of environmental and spatial factors on tree communities. In addition, we used the null Raup–Crick model to uncover the relative importance of the deterministic and stochastic processes driving community assembly. Our study revealed significant floristic distinction between seasonally flooded and upland forests. The topographic wetness index (TWI) contribution to explaining the floristic differentiation in the studied tree assemblages was greater than that of the other topography-related variables. The explanatory power of the environmental and spatial factors varied slightly between datasets. The null model indicated a predominant influence of deterministic over stochastic processes. Our findings reaffirm the role of seasonal flooding as an abiotic filter. Additionally, the TWI can serve to identify flood-prone conditions within shallow depressions. The preservation of adjacent seasonally flooded and upland forests is relevant for the maintenance of tree diversity in the karst of the Yucatan Peninsula, since flooding drives the distribution of species. Full article
(This article belongs to the Special Issue Global Change and Forest Plant Community Dynamics)
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<p>Study area and location of sampling vegetation plots (black dots) in the municipality of Calakmul, state of Campeche, Mexico. (<b>a</b>) State of Campeche; (<b>b</b>) Balam-kin protected area; (<b>c</b>) Balam-kú protected area.</p>
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<p>Non-metric multidimensional scaling (NMDS) using the Bray–Curtis dissimilarity metric to distinguish floristic composition differences between seasonally flooded forest (blue circles) and upland forest (red circles) trees within the municipality of Calakmul in the state of Campeche, Mexico. Ellipses encompassed 95% confidence interval. (<b>a</b>) All-individuals dataset (7050 tree stems), (<b>b</b>) DBH ≥10cm (4847 tree stems) and (<b>c</b>) DBH ≤10cm (2203 tree stems). Scientific name abbreviations: <span class="html-italic">Guaiacum sanctum</span> (Gs); <span class="html-italic">Lonchocarpus yucatanensis</span> (Ly); <span class="html-italic">Manilkara zapota</span> (Mz); <span class="html-italic">Coccoloba cozumelensis</span> (Cc); <span class="html-italic">Haematoxylum campechianum</span> (Hc); <span class="html-italic">Thouinia paucidentata</span> (Tp); <span class="html-italic">Psidium sartorianum</span> (Ps); Fabaceae 1 (F1); Fabaceae 2 (F2).</p>
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<p>Mean dissimilarity (±S.E.) according to Raup–Crick metric among sampling plots (beta Raup–Crick, BRC) in three different assemblies within the municipality of Calakmul in the state of Campeche, Mexico.</p>
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18 pages, 9654 KiB  
Article
Assessment of Physicochemical Parameters by Remote Sensing of Bacalar Lagoon, Yucatán Peninsula, Mexico
by José Luis Hernández-Martínez, Jorge Adrián Perera-Burgos, Gilberto Acosta-González, Jesús Alvarado-Flores, Yanmei Li and Rosa María Leal-Bautista
Water 2024, 16(1), 159; https://doi.org/10.3390/w16010159 - 31 Dec 2023
Cited by 2 | Viewed by 1989
Abstract
Remote sensing is an invaluable research tool for the analysis of marine and terrestrial water bodies. However, it has some technical limitations in waters with oligotrophic conditions or close to them due to the low spectral response of some water parameters to the [...] Read more.
Remote sensing is an invaluable research tool for the analysis of marine and terrestrial water bodies. However, it has some technical limitations in waters with oligotrophic conditions or close to them due to the low spectral response of some water parameters to the signal from the sensors to be used. In this work, we use remote sensing to evaluate a set of water quality parameters (dissolved oxygen, total dissolved solids, oxidation–reduction potential, electrical conductivity, salinity, and turbidity) in the Bacalar Lagoon, located in the Mexican Caribbean, which has experienced in recent years a dramatic change from its natural oligotrophic condition to mesotrophic and eutrophic due to anthropogenic contamination. This was accomplished through the correlation and linear regression analysis between reflectance images processed from Landsat 8 and Sentinel 2, with in situ measurements for each physicochemical parameter considered, and the development of statistical models to predict their values in places where only the reflectance values were available. The results of this work indicate the feasibility of using remote sensing to monitor electrical conductivity, salinity, turbidity, and total dissolved solids since their predicted values agree with those reported at various sites within this lagoon. Full article
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<p>(<b>a</b>) Stromatolite, (<b>b</b>) stromatolite structure mush affected by recreational activities at Bacalar Lagoon (Pictures courtesy of Dr. Eugene Perry).</p>
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<p>Bacalar lagoon system. The inner boxes indicate the study areas. Dots indicate water sampling sites.</p>
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<p>Flowchart of the research methodology to generate the spatial distribution images of physicochemical parameters by remote sensing.</p>
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<p>Average spectral response for the Bacalar and Xul-Ha lagoons.</p>
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<p>Coefficients of determination <math display="inline"><semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics></math> on a percentage scale for the analysis with SLR, MLR, and SLR with ratios for the physicochemical parameters considered in this study: dissolved oxygen (DO), oxidation–reduction potential (ORP), electrical conductivity (EC), total dissolved solids (TDS), turbidity (Turb), and salinity (S). (<b>a</b>,<b>c</b>,<b>e</b>) shows the results obtained using the Landsat 8 image and (<b>b</b>,<b>d</b>,<b>f</b>) shows those obtained with the Sentinel 2 image.</p>
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<p>Spatial distribution of (<b>a</b>) electrical conductivity (EC), and (<b>b</b>) salinity (S). The extreme coordinates of the image are (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>45</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>28</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) to (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>45</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>19</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) and (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>32</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>19</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) to (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>32</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>28</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W).</p>
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<p>Spatial distribution of (<b>a</b>) turbidity (Turb), and (<b>b</b>) total dissolved solids (TDS). The extreme coordinates of the image are (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>45</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>28</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) to (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>45</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>19</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) and (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>32</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>19</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W) to (<math display="inline"><semantics> <mrow> <msup> <mn>18</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>32</mn> <mo>′</mo> </msup> </mrow> </semantics></math> N, <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>88</mn> <mo>∘</mo> </msup> <mspace width="0.166667em"/> <msup> <mn>28</mn> <mo>′</mo> </msup> </mrow> </semantics></math> W).</p>
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<p>Spatial distributions of the physicochemical parameters measured in situ.</p>
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13 pages, 10929 KiB  
Article
Identification of Floral Resources Used by the Stingless Bee Melipona beecheii for Honey Production in Different Regions of the State of Campeche, Mexico
by Román Alberto León-Canul, Juan Bautista Chalé-Dzul, Arely Anayansi Vargas-Díaz, Juan Javier Ortiz-Díaz, Kelly Cristina Durán-Escalante, Eugenio Carrillo-Ávila and Alberto Santillán-Fernández
Diversity 2023, 15(12), 1218; https://doi.org/10.3390/d15121218 - 14 Dec 2023
Cited by 2 | Viewed by 2028
Abstract
The stingless bee Melipona beecheii is experiencing colony decline due to floral resource scarcity caused by deforestation. A study was conducted to identify the floral resources used by M. beecheii using honey samples collected in four regions of the state of Campeche, [...] Read more.
The stingless bee Melipona beecheii is experiencing colony decline due to floral resource scarcity caused by deforestation. A study was conducted to identify the floral resources used by M. beecheii using honey samples collected in four regions of the state of Campeche, Mexico. A melissopalynological analysis of sixteen collected honey samples identified 69 plant species from 24 families, and established that Fabaceae was the main plant family visited. Based on botanical origin, seven samples were classified as monofloral and nine as multifloral. The predominant species were Bursera simaruba, Lonchocarpus longistylus, Piscidia piscipula, Senna pallida and Senna racemosa. Shannon diversity index values (2.06–2.55) indicated moderate diversity in floral resources and Simpson diversity index values (0.82–0.89) indicated a moderate dominance of plant species in the studied regions. The results suggest M. beecheii is polylectic with some degree of specialization. The plant species identified as predominant in the studied honey samples are candidates for use in strategies intended to conserve the food resources used by M. beecheii on the Yucatan Peninsula. Full article
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<p>State of Campeche, <span class="html-italic">Melipona beecheii</span> honey sample collection sites. MC1–MC3: 20 Noviembre, Calakmul; MC4; La Lucha 1, Calakmul; MC5: Xcalot Akal, Hopelchén; MC6: Ich ek, Hopelchén; MC7: San Antonio, Hopelchén; MC8 and MC9: Sihochac, Champotón; MC10: Pucnachén, Calkiní; MC11: Tankunché, Calkiní; MC12: Santa María, Calkiní; MC13: Sahcabchén, Calkiní; MC14: Tankunché, Calkiní; MC15: Pucnachén, Calkiní; MC16: Santa María, Calkiní.</p>
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<p>Pollen types identified in <span class="html-italic">Melipona beecheii</span> honey samples from Campeche, Mexico. (<b>a</b>) <span class="html-italic">Senna racemosa</span>; (<b>b</b>) <span class="html-italic">Lonchocarpus longistylus</span>; (<b>c</b>) <span class="html-italic">Piscidia piscipula</span>; (<b>d</b>) <span class="html-italic">Senna villosa</span>; (<b>e</b>) <span class="html-italic">Bursera simaruba</span>; (<b>f</b>) <span class="html-italic">Pimienta dioica</span>; (<b>g</b>) <span class="html-italic">Mimosa bahamensis</span>; (<b>h</b>) <span class="html-italic">Waltheria communis</span>; (<b>i</b>) <span class="html-italic">Croton</span> sp. Scale: 10 μm.</p>
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<p>Characterization of the honey samples collected in different regions of Campeche, Mexico, as monofloral or multifloral. Numbers in the bars correspond to the percentages of pollen frequency per sample. Pollen taxa were included only as predominant (&gt;45%) and secondary (15–45%).</p>
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<p>Principal components analysis (PCA) of the floral origin of <span class="html-italic">Melipona beecheii</span> honey from the state of Campeche. (Ar) <span class="html-italic">Alternanthera ramosissima</span>; (B) <span class="html-italic">Boraginaceae</span> sp.; (Bs) <span class="html-italic">Bursera simaruba</span>; (C) <span class="html-italic">Croton</span> sp.; (Ea) <span class="html-italic">Eugenia axillaris</span>; (Lel) <span class="html-italic">Leucaena leucocephala</span>; (Ll) <span class="html-italic">Lonchocarpus longistylus</span>; (Mb) <span class="html-italic">Mimosa bahamensis</span>; (Mp) <span class="html-italic">Mimosa pudica</span>; (Ne) <span class="html-italic">Neomillspaughia emarginata</span>; (P) <span class="html-italic">Poligonaceae</span> sp.; (Pc) <span class="html-italic">Protium copal</span>; (Pd) <span class="html-italic">Pimienta dioica</span>; (Pp) <span class="html-italic">Piscidia piscipula</span>; (S) <span class="html-italic">Sapindaceae</span> sp.; (Sep) <span class="html-italic">Senna pallida</span>; (Sn) <span class="html-italic">Solanum nudum</span>; (Sr) <span class="html-italic">Senna racemosa</span>; (Sv) <span class="html-italic">Senna villosa</span>; (Vd) <span class="html-italic">Viguiera dentata</span>; (Wc) <span class="html-italic">Waltheria communis</span>.</p>
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<p>Dendrogram representation of Euclidean distance, based on frequent pollen types in each geographical region.</p>
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25 pages, 5805 KiB  
Article
Public Policies Shaping Mexican Small Farmer Practices and Environmental Conservation: The Impacts of 28 Years of PROCAMPO (1994–2022) in the Yucatán Peninsula
by Lesly-Paola Ramírez, Birgit Schmook, Mateo Mier y Terán Giménez Cacho, Sophie Calmé and Crisol Mendez-Medina
Land 2023, 12(12), 2124; https://doi.org/10.3390/land12122124 - 30 Nov 2023
Cited by 1 | Viewed by 2845
Abstract
Conditional cash transfer (CCT) programs, generally viewed as policies to modernize and increase agricultural production and commercialization, also have social and environmental impacts. Among the first Mexican CCT programs, PROCAMPO is directed toward traditional agriculture and pays farmers for permanent cultivation, ignoring traditional [...] Read more.
Conditional cash transfer (CCT) programs, generally viewed as policies to modernize and increase agricultural production and commercialization, also have social and environmental impacts. Among the first Mexican CCT programs, PROCAMPO is directed toward traditional agriculture and pays farmers for permanent cultivation, ignoring traditional fallow systems. It was implemented nationally in 1994 to counteract the effects of trade liberalization. Its objectives encompassed modernizing and improving agricultural competitiveness and environmental conservation. Here, we analyze PROCAMPO from the perspective of environmental conservation to understand its effects on agricultural practices and forest cover, specifically in the Yucatán Peninsula, where agriculture sustainability was previously achieved via an alternating cycle of multi-crop system (milpa) and forest. We performed an in-depth program analysis, reviewing 51 documents, including scientific literature, technical evaluations, and official records. Research consistently showed direct effects of PROCAMPO on agricultural practices resulting in extensive land use change, including a reduction in crop diversity and the elimination of traditional milpas and fallow. PROCAMPO has impacted conservation by causing high rates of deforestation. Our findings show the need to reorient the design and implementation of agricultural policy to increase agroecosystem resilience and ecological service provision to face climate change. Full article
(This article belongs to the Special Issue Feature Papers for 'Land Socio-Economic and Political Issues' Section)
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<p>The study area, encompassing the Yucatán Peninsula, Mexico.</p>
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<p>The Direct Rural Support Program and its transformations over time in different government processes. Data from [<a href="#B8-land-12-02124" class="html-bibr">8</a>,<a href="#B75-land-12-02124" class="html-bibr">75</a>,<a href="#B76-land-12-02124" class="html-bibr">76</a>,<a href="#B77-land-12-02124" class="html-bibr">77</a>,<a href="#B78-land-12-02124" class="html-bibr">78</a>,<a href="#B79-land-12-02124" class="html-bibr">79</a>,<a href="#B80-land-12-02124" class="html-bibr">80</a>,<a href="#B81-land-12-02124" class="html-bibr">81</a>,<a href="#B82-land-12-02124" class="html-bibr">82</a>,<a href="#B83-land-12-02124" class="html-bibr">83</a>,<a href="#B84-land-12-02124" class="html-bibr">84</a>,<a href="#B85-land-12-02124" class="html-bibr">85</a>,<a href="#B86-land-12-02124" class="html-bibr">86</a>,<a href="#B87-land-12-02124" class="html-bibr">87</a>,<a href="#B88-land-12-02124" class="html-bibr">88</a>,<a href="#B89-land-12-02124" class="html-bibr">89</a>,<a href="#B90-land-12-02124" class="html-bibr">90</a>].</p>
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18 pages, 2210 KiB  
Article
Ecogeography of Dioscorea remotiflora Kunth: An Endemic Species from Mexico
by Jocelyn Maira Velázquez-Hernández, José Ariel Ruíz-Corral, Noé Durán-Puga, Miguel Ángel Macías, Diego Raymundo González-Eguiarte, Fernando Santacruz-Ruvalcaba, Giovanni Emmanuel García-Romero and Agustín Gallegos-Rodríguez
Plants 2023, 12(20), 3654; https://doi.org/10.3390/plants12203654 - 23 Oct 2023
Cited by 1 | Viewed by 1732
Abstract
Dioscorea remotiflora, a perennial climbing herbaceous plant native to Mexico, produces tubers with great nutritional and ethnobotanical value. However, most ecological aspects of this plant remain unknown, which limits its cultivation and use. This is why the objective of this research was [...] Read more.
Dioscorea remotiflora, a perennial climbing herbaceous plant native to Mexico, produces tubers with great nutritional and ethnobotanical value. However, most ecological aspects of this plant remain unknown, which limits its cultivation and use. This is why the objective of this research was to characterize the ecogeography of D. remotiflora as a source to determine its edaphoclimatic adaptability and current and potential distribution. A comprehensive database encompassing 480 geo-referenced accessions was assembled from different data sources. Using the Agroclimatic Information System for México and Central America (SIAMEXCA), 42 environmental variables were formulated. The MaxEnt model within the Kuenm R package was employed to predict the species distribution. The findings reveal a greater presence of D. remotiflora in harsh environments, characterized by arid to semiarid conditions, poor soils, and hot climates with long dry periods. Niche modeling revealed that seven key variables determine the geographical distribution of D. remotiflora: precipitation of the warmest quarter, precipitation of the driest month, minimum temperature of the coldest month, November–April solar radiation, annual mean relative humidity, annual moisture availability index, and May–October mean temperature. The current potential distribution of D. remotiflora is 428,747.68 km2. Favorable regions for D. remotiflora coincide with its current presence sites, while other suitable areas, such as the Yucatán Peninsula, northeast region, and Gulf of Mexico, offer potential expansion opportunities for the species distribution. The comprehensive characterization of Dioscorea remotiflora, encompassing aspects such as its soil habitats and climate adaptation, becomes essential not only for understanding its ecology but also for maximizing its economic potential. This will enable not only its sustainable use but also the exploration of commercial applications in sectors such as the pharmaceutical and food industries, thus providing a broader approach for its conservation and optimal utilization in the near future. Full article
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<p>The current distribution of <span class="html-italic">D. remotiflora</span> across the agroclimatic regions of Mexico.</p>
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<p>Current distribution of <span class="html-italic">D. remotiflora</span> across soil units of Mexico.</p>
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<p>Results of Jackknife test of the relative importance of predictor environmental variables in MaxEnt model for <span class="html-italic">D. remotiflora</span> in Mexico.</p>
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<p>Models obtained and evaluated by Kuenm R package for <span class="html-italic">D. remotiflora</span>.</p>
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<p>Areas with environmental suitability for <span class="html-italic">D. remotiflora</span> in Mexico.</p>
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22 pages, 1149 KiB  
Review
Antioxidant Potential and Known Secondary Metabolites of Rare or Underutilized Plants of Yucatan Region
by Jonatan Jafet Uuh-Narvaez, Maira Rubi Segura-Campos and Oksana Sytar
Future Pharmacol. 2023, 3(4), 664-685; https://doi.org/10.3390/futurepharmacol3040042 - 7 Oct 2023
Cited by 3 | Viewed by 2313
Abstract
The screening of rare plants from the Yucatan region and the known native plants in Mexico, that have been successfully introduced worldwide, has been conducted. Based on a literature analysis and a search of English and Spanish scientific information regarding botanical, plant biochemical, [...] Read more.
The screening of rare plants from the Yucatan region and the known native plants in Mexico, that have been successfully introduced worldwide, has been conducted. Based on a literature analysis and a search of English and Spanish scientific information regarding botanical, plant biochemical, and antioxidant potential in databases such as Google Scholar, Scopus, Web of Knowledge, as well as the national databases of Mexico (Flora: Yucatan Peninsula (cicy.mx) and Especies endémicas|Biodiversidad Mexicana), rare or underutilized plants from the Yucatan region with antioxidant potential have been selected. The formulas of the most studied secondary metabolites of these selected rare plants are shown. Among the selected rare plants with antioxidant potential, the families Sapidaceae and Anacardiaceae had the highest number of representatives. Additionally, representatives from the families Annonaceae, Moraceae, Malpighiaceae, Solanaceae, Ebenaceae, Asteraceae, Ranunculaceae, and Leguminosae were also presented. The current scientific data analysis of selected rare plants from the Yucatan region, Mexico, provides significant background for their further use and introduction in not only the Yucatan region of Mexico, but also worldwide. Full article
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<p>Selected rare or underutilized plants of Yucatan region. Reproduced with permission from [<a href="#B11-futurepharmacol-03-00042" class="html-bibr">11</a>].</p>
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<p>Some specific secondary metabolites of the selected plant species of Yucatan region.</p>
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