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Se analizaron la composición elemental de los sedimentos y la distribución y abundancia de microfósiles en dos zonas de marisma de la laguna costera Estero de Urías (Golfo de California, México) con el fin de determinar las características ambientales de este medio marino restringido. En los sedimentos se detectó un enriquecimiento por metales (en particular Cu, Ni, Pb y Zn) probablemente debido a la combustión de carburantes relacionada con las actividades del puerto y la estación termoeléctrica aledaña a la laguna. Los foraminíferos bentónicos y los ostrácodos mostraron una relación con la elevación topográfica sobre el nivel marino medio, con muy pocas especies constituyendo las asociaciones. No se observó una relación entre la contaminación de los sedimentos y la presencia o abundancia de individuos y caparazones en las muestras. Este enfoque combinado entre geoquímica y micropaleontología se considera adecuado para la identificación de posibles impactos humanos y variaciones en el nivel del mar a partir de secuencias sedimentarias históricas y holocenas en esta región costera.

espanolLos manglares, junto con los pastizales marinos y las marismas, se encuentran entre los ecosistemas costeros conocidos como ecosistemas de carbono azul. Estos ecosistemasson sumideros naturales de carbono, relevantes para la mitigacion del calentamiento global debido a que son capaces de secuestrar importantes cantidades de CO2 para produccion de biomasa, asi como de almacenar materia organica en sus sedimentos durante muy largo plazo. Se presentan los resultados de la evaluacion temporal de los flujos (g m-2ano-1) e inventarios (Mgha-1) de carbono organico (Corg) en nucleos sedimentarios recolectados en areas de manglar asociados a la laguna costera Estero de Urias (Mazatlan, Sinaloa). La estrategia de trabajo incluyo la caracterizacion geoquimica de los sedimentos mediante el analisis de composicion elemental por espectrometria de fluorescencia de rayos-X para evaluar cambios en el origen de los sedimentos (terrigeno o marino); la determinacion de la distribucion de tamano de grano para evaluar cambios en la hidrodinamica de los sitios de estudio; y la cuantificacion de las concentraciones de Corg mediante un analizador elemental. Por ultimo, se presenta una estimacion del costo economico de los impactos de las emisiones potenciales de CO2como consecuencia de la oxidacion del Corg,debido a las potenciales perturbaciones de los sitios de estudio. La informacion generada representa una componente mas de los beneficios economicos de la preservacion de los ecosistemas de manglar, relevante en los planes de manejo de humedales costeros,cuya conservacion contribuye a la reduccion de emisiones de gases de efecto invernadero, y podria ser aprovechada como parte de una estrategia de adaptacion al cambio climatico basada en ecosistemas, en zonas tropicales y subtropicales alrededor del mundo EnglishMangroves, along with seagrasses and saltmarshes, are among the coastal ecosystems known as blue carbon ecosystems. These ecosystems are natural carbon sinks, relevant to mitigate global warming because they are able to sequester significant amounts of CO2for biomass production, andto store organic matter in sediments for a very long time. We present the temporal evaluation of fluxes (g m-2year-1) and inventories (Mg ha-1) of organic carbon (Corg) from sediment cores collected in mangroves areas associated with the coastal lagoon Estero de Urias, in Mazatlan, Sinaloa. The work strategy included the geochemical characterization of sediments by elemental composition analysis through X-ray fluorescence spectrometry to evaluate changes in sediment origin (terrestrial or marine); the determination of the grain size distribution to evaluate changes in the hydrodynamics of the study sites; and the quantification of Corgconcentrations with an elemental analyzer. Finally, we estimated theeconomic cost of the impacts of CO2 emissions caused by the oxidation of Corgdue to potential perturbations of the study sites. This information isan additional component of the economic benefits of the preservation of mangrove ecosystems, relevant in coastal wetland management plans, since mangrove conservation contributes to the reduction of greenhouse gas emissions and could be used as part of an ecosystem-based adaptation to climate change strategy in tropical andsubtropical zones around the world.

Due to their location in tropical latitudes, mangrove forests are susceptible to the impact of hurricanes and can be vastly damaged by their high-speed winds. Given the logistic difficulties regarding field surveys in mangroves, remote sensing approaches have been considered a reliable alternative. We quantified trends in damage and early signs of canopy recovery in a fringe Rhizophora mangle area of Marismas Nacionales, Mexico, following the landfall of Hurricane Willa in October 2018. We monitored (2016-2021) broad canopy defoliation using 21 vegetation indices (VI) from the Google Earth Engine tool (GEE). We also mapped a detailed canopy fragmentation and developed digital surface models (DSM) during five study periods (2018-2021) with a consumer-grade unmanned aerial vehicle (UAV) over an area of 100 ha. Based on optical data from the GEE time series, results indicated an abrupt decline in the overall mangrove canopy. The VARI index was the most reliable VI for the mangrove canopy classification from a standard RGB sensor. The impact of the hurricane caused an overall canopy defoliation of 79%. The series of UAV orthomosaics indicate a gradual recovery in the mangrove canopy, while the linear model predicts at least 8.5 years to reach pre-impact mangrove cover conditions. However, the sequence of DSM estimates that the vertical canopy configuration will require a longer time to achieve its original structure.

The mangrove-estuarine system of Marismas Nacionales, Mexico is considered the most extensive wetland complex of the eastern Pacific coast. Originally, this large wetland was connected to the ocean solely through a natural inlet (Teacapan). However, in the early 1970s, it was decided that an artificial inlet (Cuautla Canal) will provide a second direct connection to the ocean that could help enhance local economic development. Unfortunately, it is believed that hydrological modification resulting from this inlet changed the hydrodynamics and thus massive loss of mangroves. Hence, the purpose of this investigation was to assess the tidal hydrodynamics before and after the canal’s construction and thus understand the potential negative impacts of such unsupervised coastal projects. Specifically, sea level elevation and tidal circulation velocities were simulated during flood and ebb currents using nonlinear numerical models for both inlets. Results indicated that sea level elevation and salinity increased from 2 to 35 cm and 0.5 to 35 PSU in the Agua Brava lagoon, respectively. Additionally, there was an overall increase of 0.6 m/s regarding the tidal current velocities, and thus it is probable that the Cuautla Canal contributed to the deterioration of the once Laguncularia racemosa dominated forests, which is slowly being replaced by Avicennia germinans, Rhizophora mangle, and extensive hypersaline floodplains. Consequently, such modeling could help in mitigating the impacts of future coastal developments in Mexico or elsewhere by helping in the prediction of the possible influence of tidal hydrodynamic changes on the subtropical coastal vegetation.

Estuarine systems in subtropical and tropical areas of the Mexican Pacific are characterized by specific hydrological, biological, and anthropogenic conditions. Using multivariate analyses of geomorphic, biological, and anthropogenic variables, five of the largest estuarine systems of the southeastern Gulf of California were classified into estuary type using a similar classification method to that employed in New South Wales, Australia. Three estuary types were identified: tide-dominated, wave-dominated, and intermittently-closed. The characteristics of each estuary type were related to the fish assemblages from every system, using catch per unit effort to make results comparable among all estuaries. Our results demonstrated that intrinsic estuarine characteristics, such as geomorphologic, biological, physicochemical, anthropogenic, and biogeographical attributes, are likely to have a strong influence on the diversity and structure of fish assemblages, but more information is needed on the ecology and biology of the fish fauna to understand how these variables affect the different fish species.

Continuum monitoring of mangrove ecosystems is required to maintain and improve upon national mangrove conservation strategies. In particular, mangrove canopy assessments using remote sensing methods can be undertaken rapidly and, if freely available, optimize costs. Although such spaceborne data have been used for such purposes, their application to map mangroves at the species level has been limited by the capacity to provide continuous data. The objective of this study was to assess mangrove seasonal patterns using seven multispectral vegetation indices based on a Sentinel-2 (S2) time series (July 2018 to October 2019) to assess phenological trajectories of various semiarid mangrove classes in the Google Earth Engine platform using Fourier analysis for an area located in Western Mexico. The results indicate that the months from November through December and from May through July were critical in mangrove species discrimination using the EVI2, NDVI, and VARI series. The Random Forest classification accuracy for the S2 image was calculated at 79% during the optimal acquisition period (June 25, 2019), whereas only 55% accuracy was calculated for the non-optimal image acquired date (March 2, 2019). Although mangroves are considered evergreen forests, the phenological pattern of various mangrove canopies, based on these indices, were shown to be very similar to the surrounding land-based semiarid deciduous forest. Consequently, it is believed that the rainfall pattern is likely to be the key environmental factor driving mangrove phenology in this semiarid coastal system and thus the degree of success in mangrove remote sensing classification endeavors. Identifying the optimal dates when canopy spectral conditions are ideal in achieving mangrove species discrimination could be of utmost importance when purchasing more expensive very-high spatial resolution satellite images or collecting spatial data from UAVs.

There has been a constant increase in technology regarding unmanned aerial vehicle (UAV) systems in the last decade; yet the possibility of surveying large areas with such aerial platforms has been hampered by their low endurance. This situation has been exacerbated in low institutional capacity countries with high biodiversity coastal environments where constant monitoring is required for conservation purposes. The objective of this study was hence to determine an optimal flight mission over an initial area of 40 ha of coastal wetlands using a low-cost UAV system. The UAV missions were planned at altitudes of 60, 80, 100, and 120 m. Several orthoimages were generated with different along/across track overlaps (in intervals of 10% from 40 to 90%) in order to determine the minimum flight duration and computational efficiency. Results indicated that flight altitude and across track overlap were the most relevant variables in terms of flight distance, flight duration, number of generated images, and computer processing time. The optimal flight mission was found to be at 120-m altitude with an along/across track overlap of 60/50%. Based on the aforementioned parameters, we were able to survey a larger area of 200 ha with minimum flight duration and computer processing time. Our study highlights the feasibility and limitations of using a consumer-grade UAV in order to assess coastal wetland areas rapidly when field-based surveys approaches are not possible.

The strength and frequency of local tides in coastal lagoons plays a crucial role in providing suitable locations for the establishment of mangrove seedlings. Hence, the purpose of this investigation was to assess the hydrodynamics of a meandering tidal channel in order to select optimal locations for the construction of platforms, and thus improve the recruitment of white mangrove ( Laguncularia racemosa ) and red mangrove ( Rhizophora mangle ) propagules. The study was conducted within a coastal lagoon located along the semiarid coast of the Gulf of California. Current velocities and vorticity were simulated during flood and ebb tides using nonlinear numerical models. We tested three platforms of 3 × 3 × 0.5 m and measured the velocity and vorticity again. Once the model predicted locations where the ratio between friction and advective terms were greater, we proceeded with the construction of platforms in such suitable locations. The platforms presented a wooden perimeter filled with sediment at a similar height of the nearby mangroves (i.e., + 0.5 m Mean Sea Level). One platform was afforested with 50 red mangrove propagules, while the remaining two platforms were left without plants. Results indicated that the platforms without plants were quickly invaded by white mangrove propagules. Contrary to the aforementioned, the platform with red mangrove propagules was not invaded or replaced by other mangrove species. After nine years, the two platforms with white mangroves present 60 and 40 trees with a height of 3.5 ± 0.5 m, while the red mangrove platform presents 25 trees with a height of 3 ± 0.5 m. Our study showed the feasibility of combining numerical models and constructed platforms in order to create mangrove islands in semiarid coastlines.

Within the last few decades, tropical coastal systems such as beaches, dunes, and mangrove forests have experienced high annual rates of loss worldwide due to natural and anthropogenic impacts. Historical remote sensing data have been used to map and monitor these fragile systems, as well as to track specific events through time. The purpose of this study was to examine coastal trends along Marismas Nacionales in Mexico, which is the largest wetland complex of the western coast of the Pacific Ocean. The opening of the Cuautla Canal in 1976 and the construction of several hydroelectric power dams have severely impacted this wetland system. Shoreline variability was estimated based on representative remote sensing images over half a century (1970 to 2019). Results indicate that, after 49 years, 805 ha of beach deposits have been lost in the Cuautla Canal and at the beach ridge region that should otherwise be an accretional coastal zone. Conversely, the southern section of the study site shows 406 ha of constant accretion during the same period due to the presence of the unobstructed San Pedro River. Our study highlights the adverse effects of engineering projects, such as inlets and hydroelectric dams throughout tropical coastal systems that have strongly depended on freshwater input from upstream rivers.

The Gulf of California (GC) is a unique large marine ecosystem characterized by its rich biodiversity, high biological productivity and endemism of marine life, which are the basis of Mexico's most important fisheries. However, as many other large ecosystems worldwide, it is subject to diverse anthropogenic pressures (overfishing, losses of biodiversity and habitats, pollution, climate variability and climate change (CC)). We reviewed over 180 studies dealing with the impacts of CC and climate variability in the GC region. Main issues on the impact of ENSO events, acidification, sea level rise, and water availability are discussed for the GC in a global context. Impacts of ENSO events on the GC are geographically heterogeneous, upwelling tends to be suppressed, and this in turn influences the distribution and abundance of marine mammals, fishes, shrimps, benthic species, seaweeds and phytoplankton. ENSO events strongly impact small pelagic fishes, key components of the GC ecosystem, thus affecting fisheries in general as well as non-harvested species such as marine mammals and sea birds. Probably the most well-known phenomenon associated to ENSO impact in the GC is coral bleaching, a process by which corals expel most of their microalgal endosymbionts to become pale or white (bleached). Beside shifts in the distributional limits of benthic organisms, invasions of alien species are also occuring. Harmful algal blooms (HABs) are common and recurrent in the GC. Fourteen HAB-forming species have been recorded, with Gymnodinium catenatum being the most frequent. HABs are inhibited by El Nino and promoted by La Nina. During El Nino events the size and biomass of macroalgal blooms tend to decrease. Finally, several aspects that require further research are proposed.

El propósito del presente estudio fue generar información en torno a la posibilidad de estabilizar isletas de dragado mediante la plantación de halófitas, particularmente con la creación de nuevas áreas de manglar. Para esto, fue construido un vivero para producir plantas de Avicennia germinans y Rhizophora mangle , a la vez que se obtuvieron individuos del medio natural para ambas especies. Para su plantación se consideró el intervalo de mareas, áreas de baja energía, salinidad, zonación de cada especie y un diseño experimental de bloques completos al azar. Los resultados indicaron una mayor supervivencia y crecimiento de las plantas de vivero que las extraídas del medio natural. La supervivencia de plantas de A. germinans (78% con contenedor, 72% sin contenedor, 34% medio natural) fue mayor que la de R. mangle (43% con contenedor, 34% sin contenedor, 2% medio natural). De igual manera, el crecimiento en altura de las plantas de A. germinans , tanto de las producidas en vivero (3.2 cm mes-1), como las extraídas del medio natural (1.5 cm mes-1), fue mayor que las de R. mangle (producidas en vivero: 1.4 cm mes-1; extraídas del medio natural: 0.8 cm mes-1). No se presentó colonización natural durante el periodo de estudio, por lo que son recomendables las plantas de vivero para iniciar la forestación de isletas artificiales, considerando las mareas, la zonación natural local, áreas de baja energía y sobre todo, el hidroperiodo.

Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.

Within the last few decades mangrove forests worldwide have been experiencing high annual rates of loss and many of those that remain have undergone considerable degradation. To understand the condition of these forests, various optical remote sensing platforms have been used to map and monitor these wetlands, including the use of these data for biophysical parameter mapping. For many mangrove forests a reliable source of optical imagery is not possible given their location in quasi-permanent cloud cover or smoke covered regions. In such cases it is recommended that Synthetic Aperture Radar (SAR) be considered. The purpose of this investigation was to examine the relationships between various ALOS-PALSAR modes, acquired from eight images, and mangrove biophysical parameter data collected from a black mangrove ( Avicennia germinans ) dominated forest that has experienced considerable degradation. In total, structural data were collected from 61 plots representing the four common stand types found in this degraded forest of the Mexican Pacific: tall healthy mangrove ( n = 17), dwarf healthy mangrove ( n = 15), poor condition mangrove ( n = 13), and predominantly dead mangrove ( n = 16). Based on backscatter coefficients, significant negative correlation coefficients were observed between filtered single polarization ALOS PALSAR (6.25 m) HH backscatter and Leaf Area Index (LAI). When the dead stands were excluded ( n = 45) the strength of these relationships increased. Moreover, significant negative correlation coefficients were observed with stand height, Basal Area (BA) and to a lesser degree with stem density and mean DBH. With the coarser spatial resolution dual-polarization and quad polarization data (12.5 m) only a few, and weaker, correlation coefficients were calculated between the mangrove parameters and the filtered HH backscatter. However, significant negative values were once again calculated for the HH when the 16 dead mangrove stands were removed from the sample. Conversely, strong positive significant correlation coefficients were calculated between the cross-polarization HV backscatter and LAI when the dead mangrove stands were considered. Although fewer in comparison to the HH correlations, a number of VV backscatter based relationships with mangrove parameters were observed from the quad polarization mode and, to a lesser extent, with the one single VV polarization data. In addition to backscatter coefficients, stepwise multiple regression models of the mangrove biophysical parameter data were developed based on texture parameters derived from the grey level co-occurrence matrix (GLCM) of the ALOS data. A similar pattern to the backscatter relationships was observed for models based on the single polarization unfiltered data, with fairly strong coefficients of determination calculated for LAI and stem height when the dead stands were excluded. In contrast, similar coefficients of determination with biophysical parameters were observed for the dual and quad polarization multiple regression models when the dead stands were both included and excluded from the analyses. An estimated mangrove LAI map of the study area, derived from a multiple regression model of the quad polarization texture parameters, showed comparable spatial patterns of degradation to a map derived from higher spatial resolution optical satellite data.

When dead stands are included, the strongest overall relationships between the ultra-fine backscatter incidence angle of ∼32° and the various structural parameters were found using the horizontal-horizontal HH polarization/horizontal-vertical HV polarization ratio. However, if the dead stands are not included, then significant relationships with the ultra-fine data were only calculated with the HH data. Similar results were observed using the corresponding incidence angle ∼33° of the fine beam data. When a shallower incidence angle was considered ∼39°, fewer and weaker relationships were calculated. Moreover, no significant relationships were observed if the dead stands were excluded from the sample at this incidence angle. The highest correlation coefficients using the steepest incidence ∼27° were found with the co-polarized HH, vertical-vertical VV polarization modes. Several polarimetric parameters entropy, pedestal height, surface roughness, alpha angle based on the decomposition of the scattering matrix of the fine beam mode at this incidence angle were also found to be significantly correlated to mangrove structural data. The highest correlation R = 0.71 was recorded for entropy and LAI. When the dead stands were excluded, volume scattering was found to be the most significant polarimetric parameter. Finally, multiple regression models, based on texture measures derived from both the grey level co-occurrence matrix GLCM and the sum and difference histogram SADH of the ultra-fine data, were developed to estimate mangrove parameters. The results indicate that only models derived from the HH data are significant and that several of these were strong predictors of all but stem density.

Mangrove photosynthetic activity and, consequently, physiological stress can be monitored indirectly using leaf chlorophyll-a (Chla) measurements. Recent studies have demonstrated the feasibility of mangrove leaf Chla content estimation from in situ hyperspectral vegetation indices (VI) but no such research has been conducted using data collected from contrasting seasons (i.e. dry and rainy). In this study, mangrove leaves were collected in a sub-tropical forest of the Mexican Pacific for Chla content determination and in situ hyperspectral measurements (450–1,000 nm). Specifically, we tested 35 VI to estimate Chla content based on a leaf sample of 360 collected from the same trees during both the dry and rainy seasons. The forest examined contained three species of mangrove (Rhizophora mangle, Avicennia germinans and Laguncularia racemosa) exhibiting various conditions of health (dwarf condition, tall and healthy). A principal component analysis, followed by linear regression analyses, were conducted in order to identify those VI that best predict mangrove leaf Chla content during the two seasons. The results indicate that VI derived from hyperspectral measurements collected during the dry season are better at estimating leaf Chla content than those collected during the rainy season. Among the 35 VI, the Vog1 (R740/R720) index was found to be the best predictor of mangrove leaf Chla content, resulting in R 2 values of 0.80 and 0.68 for the dry and rainy season respectively. These results would suggest that for identifying variation in mangrove forest stress (i.e. health) in sub-tropical regions, hyperspectral measurements should be carried out during the dry season.

The purpose of this investigation was to determine the feasibility of using the chlorophyll content index (cci) from a ccm-200 unit as an estimator of the seasonal variation of leaf pigment [chlorophyll a (chla), chlorophyll b (chlb), and total chlorophyll (tchl = chla + chlb)] content for a range of mangrove species within a degraded environment of the Mexican pacific. Two seasons (dry and rainy) of measurements were made on six mangrove classes: healthy and dwarf Avicennia germinans (Linnaeus) Linnaeus, healthy and poor condition Rhizophora mangle Linnaeus, and healthy and poor condition Laguncularia racemosa (Linnaeus) c.f. gaertn. Tests of leaf pigment contents from 360 cci readings (30 per class) indicated that each equation was a valid predictor of chla and tchl for all six mangrove classes during both seasons. However, there was a poorer fit (lower R 2 ) for the three species in poor/dwarf condition during the rainy season. chla and tchl were statistically well correlated with all of the cci data; however, the correlating chlb were lower (R 2 < 0.68) for all classes except dwarf condition A. germinans (R 2 = 0.80). The strong relationship observed between the readings from the portable ccm-200 and the pigment content suggest that the handheld ccm-200 can be a portable cost-effective tool for quickly predicting chla and tchl content for a range of mangrove forests.

The use of spectral response curves for estimating nitrogen (N) leaf concentrations generally has been found to be a challenging task for a variety of plant species. In this investigation, leaf N concentration and corresponding laboratory hyperspectral data were examined for two species of mangrove (Avicennia germinans, Rhizophora mangle) representing a variety of conditions (healthy, poor condition, dwarf) of a degraded mangrove forest located in the Mexican Pacific. This is the first time leaf nitrogen content has been examined using close range hyperspectral remote sensing of a degraded mangrove forest. Simple comparisons between individual wavebands and N concentrations were examined, as well as two models employed to predict N concentrations based on multiple wavebands. For one model, an Artificial Neural Network (ANN) was developed based on known N absorption bands. For comparative purposes, a second model, based on the well-known Stepwise Multiple Linear Regression (SMLR) approach, was employed using the entire dataset. For both models, the input data included continuum removed reflectance, band depth at the centre of the absorption feature (BNC), and log (1/BNC). Weak to moderate correlations were found between N concentration and single band spectral responses. The results also indicate that ANNs were more predictive for N concentration than was SMLR, and had consistently higher r2 values. The highest r2 value (0.91) was observed in the prediction of black mangrove (A. germinans) leaf N concentration using the BNC transformation. It is thus suggested that artificial neural networks could be used in a complementary manner with other techniques to assess mangrove health, thereby improving environmental monitoring in coastal wetlands, which is of prime importance to local communities. In addition, it is recommended that the BNC transformation be used on the input for such N concentration prediction models.

The effect of five constant temperatures (20°C, 23°C, 26°C, 29°C and 32°C) on the growth of juvenile arched swimming crabs, Callinectes arcuatus, was evaluated over a 360-day experimental period. The crabs were reared in a recirculating system. The growth rate was significantly greater (p

Amongst the most threatened ecosystems on Earth, mangrove forests are also one of the more difficult to work in due to their growth in mud and open water coastal zones and their dense tangled stems, branches and prop roots. Consequently, there has been an impetus to employ remotely sensed imagery as a means for rapid inventory of these coastal wetlands. To date, the majority of mangrove maps derived from satellite imagery utilize a simple mangrove classification scheme which does not distinguish mangrove species and may not be useful for conservation and management purposes. Although more elaborate satellite based mangrove classification schemes are being developed, given their enhanced complexity they deserve additional justification for end users. The purpose of this study was to statistically examine the appropriateness of one such classification scheme based on an inventory of field data. In January of 2007 and May of 2008, 61 field sample plots were selected in a stratified random fashion based on a previous classification of a degraded mangrove forest of the Isla La Palma (Sinaloa, Mexico) using Landsat TM5 data. Unlike other previous Landsat TM based classifications of this region, which simply identified the mangrove forests as one class, the mangroves were classified (i.e. mapped) according to four conditions; healthy tall, healthy dwarf, poor condition, and dead mangroves. Within each sample plot, all mangroves of diameter of breast height (dbh) greater than 2.5 cm were identified and their height, condition and dbh recorded. An estimated Leaf Area Index (LAI) value also was obtained for each sample and the shortest distance from the center of each sample plot to open flowing water was determined using a geographic information system (GIS) overlay procedure. These data were then used to calculate mean values for the four classes as well as to determine stem densities, basal areas, and the Shannon–Wiener diversity index. In order to assess the appropriateness of this mangrove classification scheme a discriminant analysis approach was then applied to these field data. The results indicate this forest has undergone severe degradation, with decreasing mean tree heights, mean dbh and species diversity. In regards to the discriminant analysis procedure, further classification of these field plots and cross-validation based on these significant variables provided high classification accuracy thus validating the appropriateness of the satellite based image classification scheme. Moreover, the discriminant analysis indicated that the estimated LAI, mean height, and mean dbh are significant in the separation of the classification of mangrove forest condition along these field sample plots.

We described, through a vegetation profile, the forest structure (density, basal area, tree height, and species composition), the productivity dynamics (based on litterfall) and the species phenology of distinct physiognomic types of mangroves in three locations of the La Mancha lagoon system in Veracruz, Mexico, during a complete annual cycle. We also evaluated the microtopography and ground water salinity along the profile and their relationship with forest structure and productivity. The South location showed four physiognomic types, whose forest attributes decreased as they were farther from the lagoon shore. Productivity and environment variables significantly varied among these physiognomic types. The Center location had two physiognomic types; there were significant differences in productivity and microtopography among these types, but not in salinity. The North location included two fragments of a basin forest type, and a pasture among them; productivity significantly varied among these forests, but microtopography and salinity were statistically similar. All study sites showed the following behavior: (1) as forest structure decreased, productivity also decreased and the dominant species changed. (2) As water salinity decreased, species dominance changed and productivity increased. Reproductive structures showed a notorious seasonality during the year in all species, except in R. mangle, which showed a permanent flower and propagules production. A. germinans reproduced only in the rainy season (August and September), because of their life history characteristics, whereas L. racemosa reproduced during the months of February and March as a response of the direct entrance of the water discharges, enriched with nutrients, that come from the sugar cane and rice crops. The South location was a relatively well conserved area, whereas the two other sites showed evidences of anthropic disturbances.

To determine whether spaceborne C-band SAR data could be used alone, or in conjunction with optical data, for accurately mapping mangrove forests of the Mexican Pacific, four scenes of dual-polarized ENVISAT ASAR data, at two incidence angles, were collected for the Teacapan-Agua Brava-Las Haciendas estuarine-mangrove complex. Several combinations of these ASAR data were classified to determine the most optimal arrangement for mangrove mapping. In addition, corresponding Landsat TM data were classified using the same training sites. The overall accuracy in mapping these mangroves did improve when more than one polarization mode was employed. In general, the higher incidence angle data (~41o vs ~23o) provided better results. In all circumstances, the optical data alone provided higher classification accuracies. When contained as one mangrove class, the highest overall accuracy achieved using the ASAR data was 54% as compared to 76% for the optical data. When considering four separate mangrove classes, representing the four conditions typical of this system (dead, poor condition, healthy, tall healthy), overall accuracies dropped to 45% and 63%, respectively. With the limited penetration of C-band into canopies, it was difficult to separate healthy and tall healthy mangrove from palm and other terrestrial forests using the ASAR data. In addition to confusion amongst the four mangrove classes, the dead mangrove stands created considerable misclassification as they were readily misidentified with water and saltpan areas in the optical data and with agricultural lands in the ASAR data procedure. Given the advantage of ASAR for identifying dead stands from open water and saltpan, these data were then used in conjunction with the optical data to reduce the misclassification of these areas. Para determinar si los datos de la banda C del sensor espacial SAR pudieran utilizarse solos, o de manera simultanea con datos opticos, para hacer mapas precisos de bosques de manglar del Pacifico mexicano, se tomaron cuatro escenas de ENVISAT ASAR de doble polarizacion, con dos angulos de inclinacion, del complejo estuarino de manglar Teacapan-Agua Brava-Las Haciendas. Se clasificaron varias combinaciones de datos de ASAR con el proposito de determinar el arreglo optimo para crear mapas de manglares. Ademas, se clasificaron datos de Landsat TM para los mismos sitios de ensayo. La precision global al hacer mapas de estos manglares aumento cuando se utilizo mas de un modo de polarizacion. En general, los resultados fueron mejores cuando el angulo de incidencia fue mayor (~41o vs ~23o). En todas los casos, los datos opticos por si solos proporcionaron una clasificacion mas precisa. Con una sola clase de manglar la mayor precision global utilizando los datos de ASAR fue de 54%, comparada con 76% con los datos opticos. Cuando se consideraron las cuatro diferentes clases de manglar que representan las condiciones tipicas de este sistema (manglar muerto, pobre, sano y sano alto), la precision global se redujo hasta 45% y 63%, respectivamente. Debido a la limitada penetracion de la banda C en el follaje, utilizando datos del ASAR fue dificil diferenciar los manglares sanos y sanos altos de las palmas y otros bosques terrestres. Ademas de la confusion entre las cuatro clases de manglar, las zonas de manglares muertos resultaron erroneamente clasificadas como areas salinas y de aguas libres de vegetacion, con los datos opticos, y como tierras agricolas con los datos de ASAR. Dadas las ventajas para diferenciar areas de manglar muerto de los espejos de agua y las salinas con los datos de ASAR, estos se utilizaron de manera simultanea con datos opticos para reducir los errores en la clasificacion de estas areas.

To determine whether multipolarized spaceborne synthetic aperture radar could be used to monitor the health of a mangrove forest, leaf area index, as well as other biophysical parameter data, from stands dominated by white mangrove (Laguncularia racemosa) and located within a degraded mangrove forest were examined in relation to backscatter coefficients from ENVISAT synthetic aperture radar scenes. The results indicate that polarization and, to a lesser extent, incident angle play a significant role in the ability to estimate both leaf area index and mean tree height. No significant linear coefficients of determination were observed between the recorded parameters and the backscatter coefficient from any of the copolarized scenes. With regards to leaf area index, r2 values of 0.82 and 0.73 were calculated for the cross-polarized data at two incident angles. For mean tree height, the linear coefficient of determination was much higher for the smaller incident angle data than for the larger inciden...

et al., Sea-level rise (SLR) is one of the most conspicuous examples of the environmental impact of recent climate change. Since SLR rates are not uniform around the planet, local and regional data are needed for proper adaptation plans. Pb-dated sediment cores were analyzed to determine the trends of sediment accretion rates (SARs) at three tropical saltmarshes in the Estero de Urias lagoon (Gulf of California, Mexico), in order to estimate the SLR trends during the past ~100 years, under the assumption that these ecosystems accrete at a similar rate to SLR. A chemometric approach, including multivariate statistical analysis (factor analysis) of geochemical data (including δC; δN; C/N ratios; and Br, Na, and Cl as proxies for marine transgression) was used to identify the marine transgression in the sediment records. Based on core geochemistry, only one of the three cores provided a long-term record attributable to marine transgression. SLR trends, estimated from SARs, showed increasing values, from a minimum of 0.73 ± 0.03 mm yr at the beginning of the 20th century and up to 3.87 ± 0.12 mm yr during the period 1990–2012. The estimated SLR trend between 1950 and 1970 was comparable to the tide gauge records in Mazatlan City for the same period. Results showed the caveats and strengths of this methodology to reconstruct decadal SLR trends from the sedimentary record, which can be used to estimate long-term SLR trends worldwide in regions where monitoring data are scarce or absent., This work has been supported by the grants CONACyT CB2010-153492, PAPIIT-IN203313, CONACYT PDCPN2013-01/214349, and the CONACYT fellowship to JLSP.

To determine whether spaceborne Synthetic Aperture Radar (SAR), specifically fine beam RADARSAT-1 C-band, could be used to provide quantitative data on white mangrove (Laguncularia racemosa (Gaertner)) forests, backscatter coefficients (σ°) were examined in relation to structural parameter data collected from plots located in a mangrove forest of the Mexican Pacific. Significant coefficients of determination were recorded between the backscatter coefficients and the logarithms of both Leaf Area Index (LAI) and mean stem height at two incident angles for both the dry and wet seasons. The highest coefficients of determination for LAI (r 2 = 0.60) and mean stem height (r 2 = 0.72) were observed using the shallower (~40°) and steeper (~47°) incident angles, respectively. No significant relationships were recorded between the backscatter coefficients and either stem density, basal area or mean DBH. Given the results of this investigation, it is recommended that for cloud covered regions, fine beam RADARSAT-1 data could be used by resource managers when they require a quick method for surveying structural damage to mangroves resulting from both natural and anthropogenic causes.

The structure, litterfall production, and primary production of the mangrove stand at El Conchalito Estuary in La Paz Bay (Baja California Sur, Mexico) were...

Using both IKONOS and in situ LAI-2000 sensor data, a map of estimated LAI, based on NDVI, was created for the Agua Brava Lagoon, Mexican Pacific. The LAI values were then aggregated according to four classes; red mangrove (Rhizophora mangle), healthy white mangrove (Laguncularia racemosa), poor condition white mangrove and dead mangrove. Of the live mangrove, calculated at approximately 85% of the forest, mean LAI values of 2.49, 1.74 and 0.85 were determined for the red, healthy white and poor condition white mangrove, respectively. Excluding the dead areas, an overall estimated mangrove LAI value of 1.81 was ascertained for the 71 km2 of mapped mangrove forest. Although the results do suggest the technique as a very rapid and effective method for monitoring the condition of mangroves at the species level, potential limitations are also discussed.

Leaf Area Index (LAI) values from 124 mangrove plots were acquired within a degraded mangrove forest of the Agua Brava Lagoon System of Nayarit (Mexico) using a hand held LAI-2000 Plant Canopy Analyzer. For each plot, two values of LAI were calculated to represent approximate half radii (180°) ground coverage of 8 m and 15 m. The location of each plot was recorded at sub-meter accuracy using an Ashtech SCA-12 GPS. Using a geometrically corrected IKONOS satellite image, the mean values for both the Normalized Difference Vegetation Index (NDVI) and the simple ratio (SR) vegetation indices were also calculated for each plot. Regression analyses of the in situ LAI with both vegetation indices revealed significant positive relationships (LAI versus NDVI at 8 m ( R 2 = 0.71); LAI versus NDVI at 15 m ( R 2 = 0.70); LAI versus SR at 8 m ( R 2 = 0.73); LAI versus SR at 15 m ( R 2 = 0.72)) at the 8 m and 15 m plot sizes. Standard errors, derived from the testing of the regression models with a random sample, revealed little difference between the models. Moreover, F -tests of the residual variances also indicated no significant difference between the SR and NDVI models at both plot sizes. Consequently, the results indicate that each model could be used to successfully predict LAI. It is thus suggested that high spatial resolution IKONOS data can be employed as a valuable tool for monitoring LAI in less than ideal mangrove forests (i.e. disturbed stands).

Structure and litterfall in an Avicennia germinans mangrove stand in an arid zone on the Gulf of California, Mexico were studied. The density (4700 ha−1) and basal area (13.5 m2 ha−1) were more characteristic of a fringe-type mangrove stand, while average height (2.7 m), number of species in 0.1 ha (1), and complexity index (1.7) were closer to those of a dwarf-type mangrove. Structure is jointly influenced by a high rate of evaporation (2982 mm per year), scarce rainfall (290 mm per year, mainly in summer) and a brief period of tidal flooding (also only in the summer). Litterfall averaged 1.75 t ha−1 per year, placing it even lower than the lowest value reported so far for mangrove litterfall (2–16 t ha−1 per year). Litterfall showed a unimodal seasonal pattern, with higher values in summer. Rainfall, sea level and the ratio rainfall/evaporation explained 86% of the seasonal litterfall variability.

Beginning in the middle of the 1980s, the Gulf of California ecoregion experienced a boom in shrimp aquaculture and became the second largest producer in the western hemisphere. The moderated, but continual development of shrimp farming, in conjunction with municipal and agriculture effluents has been accompanied by concern about: (a) depletion of fishing stocks, (b) reduction of mangrove forest, (c) frequent harmful algal blooms in coastal waters and shrimp ponds, and (d) water quality deterioration. We demonstrate that environmental degradation resulted from a conjunction of factors including agriculture, untreated municipal effluents, shrimp aquaculture, increasing number of fishermen, and an absence of an effective regulatory program. We recommend the immediate implementation of an integrated coastal management program to protect the integrity of the coastal ecosystems and operate upon the principle of environmental sustainability for the different economic activities including shrimp aquaculture.

Some ecological aspects of the swimming crabs, Callinectes arcuatus and C. bellicosus are presented. Specimens were collected with a trawl net, both day and night, on a monthly basis from March 1998 to February 2000 in a coastal lagoon in northwest Mexico. A total of 1235 specimens were captured, C. bellicosus (n = 878) (abundance 0.5 to 60 ind. ha-1) was more abundant than C. arcuatus (n = 357) with an abundance from 0 to 38 ind. ha-1 during the study period. Both species were more abundant at night and usually were found in conjunction with macroalgae. Salinity (32 to 40‰) tended to favour the dominance of C. bellicosus over C. arcuatus (2.4 : 1) and the water temperature appeared to govern the breeding season (21 to 32°C). For both species, the breeding season runs from March until September (spring-summer), the recruitment of juveniles occurs during January and February (winter), and the lowest abundance of both species is found during October and November (fall). For both species, ovigerous females were observed in the mouth of the lagoon, and juveniles were found in the lagoon's interior parts. The authors think that the observed ecological patterns of the species could be extrapolated to other coastal lagoons with a similar climate, oceanography, and geomorphology.

"Six silvofishery systems were constructed to estimate the poten tial use of mangrove seedlings for nutrient removal. Two system s did not contain seedlings (i.e., control treatment), while the remaining syst ems were divided into se parate treatments using tw o mangrove species ( Laguncularia racemosa and Rhizophora mangle ). Each system cons isted of two water tanks linke d by two hoses. The first tank contained 150 poeciliid fishes, whil e the second contained a biologi cal filter of gravel and sand on the bottom, as well as a h ydroponic arrangement of 34 seedlings. Water exchange between both tanks was perfo rmed over a 24-h period, every ten days for seven month s, and the concentration of nutrients (NH 4 + , NO 2 – , NO 3 – , and PO 4 –3 ) was measured every 8 h. Laguncularia racemosa showed a higher growth rate compared to R. mangle , but there were no differences regarding the growth of fish es among the six systems. Fina l dissolved inorganic nitrogen removal was 42% in the control treatment a nd 90% in both treatments using mangroves. Dissolved inorganic phosphorus removal was 45% in the control treatment, 44% in the L. racemosa treatment, and 35% in the R. mangle treatment. Our results indica te that both mangrove species are capable of removing a considerable amount of nitrogen, but phosphorus removal was unsatisfactory."

Given the scale and rate of mangrove loss globally, it is increasingly important to map and monitor mangrove forest health in a timely fashion. This study aims to identify the conditions of mangroves in a coastal lagoon south of the city of Mazatlán, Mexico, using proximal hyperspectral remote sensing techniques. The dominant mangrove species in this area includes the red (Rhizophora mangle), the black (Avicennia germinans) and the white (Laguncularia racemosa) mangrove. Moreover, large patches of poor condition black and red mangrove and healthy dwarf black mangrove are commonly found. Mangrove leaves were collected from this forest representing all of the aforementioned species and conditions. The leaves were then transported to a laboratory for spectral measurements using an ASD FieldSpec® 3 JR spectroradiometer (Analytical Spectral Devices, Inc., USA). R2 plot, principal components analysis and stepwise discriminant analyses were then used to select wavebands deemed most appropriate for further mangrove classification. Specifically, the wavebands at 520, 560, 650, 710, 760, 2100 and 2230 nm were selected, which correspond to chlorophyll absorption, red edge, starch, cellulose, nitrogen and protein regions of the spectrum. The classification and validation indicate that these wavebands are capable of identifying mangrove species and mangrove conditions common to this degraded forest with an overall accuracy and Khat coefficient higher than 90% and 0.9, respectively. Although lower in accuracy, the classifications of the stressed (poor condition and dwarf) mangroves were found to be satisfactory with accuracies higher than 80%. The results of this study indicate that it could be possible to apply laboratory hyperspectral data for classifying mangroves, not only at the species level, but also according to their health conditions.

The removal of ammonium (NH 4 + ), nitrite (NO 2 − ), nitrate (NO 3 − ), and phosphate (PO 4 −3 ) in a closed silvofishery system was examined using three mangrove species (i.e., Avicennia germinans , Laguncularia racemosa , and Rhizophora mangle ). Specifically, six closed tanks were installed for this experiment with a population of 60 Dormitator latifrons fishes per tank. We planted 40 seedlings in each of three experimental tanks separated by species, while the remaining tanks were used as control. During 15 weeks, nutrient concentrations among the three mangrove systems presented no significant differences ( P > 0.05). However, nutrient removal variability was minimum during the last 2–5 weeks. Mangroves presented an average efficiency of 63% for the removal of NH 4 + and NO 2 − . Contrary, the average removal potential of NO 3 − and PO 4 −3 was 50%. Results from this study suggest that the three mangrove species could be used in a closed silvofishery systems for the biological removal of NH 4 + , NO 2 − , NO 3 − , and PO 4 −3 .

Hypersaline conditions are common in sub-tropical latitudes where freshwater availability is seasonal. Hence, hydroperiod plays a crucial role in providing a suitable area for the establishment of new mangrove seedlings. The purpose of this study was to assess the function of hydrological change and irradiance in the growth of afforested black mangrove (Avicennia germinans) along the upper saltpan area by creating six channels of 1 m wide by 0.3 deep and 30 m length. All channels were constructed perpendicular to the main coastline of the Urias lagoon, Pacific coast of Mexico. Seedlings of black mangrove were planted along four of the channels. After ten months, the pore-water salinity concentration within the six channels was reduced by half. Results indicate that there were no significant differences (P > 0.05) in mangrove survival among the channels. However, the optimal growth of black mangroves was near the channels edge. The growth of mangrove seedlings planted under 50% of solar attenuation was 10 times higher as compared to mangroves under direct sunlight. This study shows the feasibility of using channels to enhance tidal flow and decrease hypersaline conditions for future afforestation endeavors in arid coastlines.

In order to balance the impact of agricultural development on land around coastal lagoons with the protection of aquatic resources, knowledge of the role of the sedimentary phase in the entrapment or availability of nutrients in the water column in areas affected by agroindustrial outlets is important. The Ensenada del Pabellon coastal on the Pacific coast of Mexico was chosen to be analyzed. The input of ammonium and orthophosphate from sediment using semicontrolled benthic chambers near a sugar cane factory outlet was compared to non altered sediment. Phosphate and ammonia loading from agroindustrial outlets has been the primary cause of eutrophication. The inputs of ammonium and orthophosphates from the sediment to the water column depend on their concentration in the agroindustrial outlet's waste water, the local morphology, the tide, and biotic assimilation, in order of importance. Sediment in non-altered revealed maxima of 7.8 mg m-2 d-1 of NH+4 and 1.4 mg m-2 d-1 of PO-3_4, whereas in one outlet that greatly transfigures the environment, maxima of 223 mg m-2 d-1 of NH+4 and 67 mg m-2 d-1 of PO-3_4 were recorded, which represent an increase greater than 20 times the normal diffusion. These figures varied markedly in space and time. Results from the study indicated that existing levels of nutrient could endanger the future of this ecosystem, including its sustainable fisheries.