Mangrove phenology and environmental drivers derived from remote sensing in Southern Thailand

© 2019 by the authors. Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8-9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies

Mangrove Phenology and Environmental Drivers Derived from Remote Sensing in Southern Thailand

Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8–9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.</jats:p

Loss and Gain in Mangrove Surrounding the Lençóis Maranhense National Park: An Integrated Approach Using Remote Sensing and SIG Data

Brazil harbors the second largest expanse of mangroves in the world, trailing only behind Indonesia. In a regional context, the state of Maranhão stands out, encompassing approximately 36% of Brazil’s total mangrove area, including a portion located on the eastern coast in the Lençóis Maranhenses. This study played a crucial role in identifying the areas of gain, loss, and stability in the mangroves surrounding the Lençóis Maranhenses National Park over a historical period spanning from 1985 to 2019. The study provided detailed maps depicting spatial changes, such as migration and attenuation that occurred in the mangroves due to the influence of aeolian dunes and wind patterns in the region. This long-term analysis, the first of its kind to examine the annual expansion of forest loss in the remaining mangroves around the Lençóis Maranhenses in recent decades, revealed a reduction in the central mangrove areas between 1985 and 2019. This decline can be attributed not only to intense tourist activity and climate change but also to the movement and invasion of sand dunes in certain areas, as observed near the villages of Caburé and Paulino Neves (Pequenos Lençóis) in December2022. Wind plays a fundamental role as a transformative agent in the local landscape. Through the analysis of wind roses using ERA5 reanalysis data and meteorological stations from the Aeronautics (São Luís and Parnaíba), it was possible to identify and characterize the prevalence of northeast trade winds in the Lençóis Maranhenses region during the years 1985 to 2019, with average speeds ranging from 6 to 8 m/s. The advancement of dunes onto the mangroves surrounding the Lençóis Maranhenses results in burial, reduction, and even migration of mangrove patches. Additionally, over the years, population growth and increasing tourism pressure along the banks of the Preguiças River have drawn attention to the need to implement control and conservation measures in the mangroves to prevent further disturbances in this environment

Variación fenológica de Rhizophora mangle, Conocarpus erectus y Laguncularia racemosa en Isla Múcura, Parque Nacional Natural Los Corales del Rosario y de San Bernardo, Caribe colombiano

Mangroves are strategic coastal marine ecosystems with a wide variety of services to humanity. However, they are vulnerable to natural and anthropogenic disturbances, being fragmentation a more significant threat. Consistent with the above, the Corales del Rosario y de San Bernardo (PNNCRSB) have been identified as a conservation object value of the PNN. The most common mangrove species at PNNCRSB are the red mangrove Rhizophora mangle, the Zaragoza Conocarpus erectus, and the yellow Laguncularia racemosa. Currently, the available information and the monitoring program for this protected area are limited to coverage data, so there is limited information available on the phenology of these species, despite knowing that the latter responds to environmental changes in the ecosystem. Therefore, this research aimed to evaluate the variation of phenological events (production of fruits, flowers, and leaves) of red, zaragoza and yellow mangroves in the PNNCRSB for two years and its relationship with intra-annual climatic patterns. The results show that there are temporal patterns of the variation of the phenological events.  In the case of R. mangle, it did not show leaf drops but presented fruits and flowers during the 24 months. Something similar was observed for C. erectus. Robust and significant canonical correlations (R &gt;6; p &lt;0.05) were also found for groups of climatic environmental variables and phenological events in the three species in the two years of study. Therefore, it is inferred that there are suitable environmental conditions for mangroves development and the climatic patterns affect the phenology of the species in the study area. Finally, phenological characteristics of the species are proposed as an important input for decision making such as restoration processes, since they allow knowing the periods of time indicated to carry out activities of collecting propagules, setting up nurseries and planting seedlings in degraded areas.Los manglares son ecosistemas marino costeros estratégicos ofrecen una variedad de servicios a la humanidad. No obstante, son vulnerables a perturbaciones naturales y antropogénicas, dentro de las cuales la fragmentación representa una mayor amenaza. Consecuente con lo anterior, han sido identificados como valor objeto de conservación del PNN Los Corales del Rosario y de San Bernardo (PNNCRSB), siendo las especies más representativas el mangle rojo Rhizophora mangle, el zaragoza Conocarpus erectus y el amarillo Laguncularia racemosa. Actualmente, la información existente y el programa de monitoreo de esta área protegida se limita a datos de coberturas, por lo que no existe información disponible sobre la fenología de estas especies. Por lo anterior, esta investigación se propuso evaluar la variación de eventos fenológicos (producción de frutos, flores y hojas) de mangle rojo, zaragoza y amarillo en el PNNCRSB durante 2014-2015 y su relación con patrones climáticos intra-anuales. Los resultados muestran que existen patrones temporales de la variación de los eventos fenológicos. En el caso de R. mangle, no evidenció caída de hojas, pero sí presentó frutos y flores durante los 24 meses. Algo similar se observó para C. erectus. También se encontraron correlaciones canónicas robustas y significativas (R &gt; 6; p &lt;0,05) de grupos de variables ambientales climáticas y los eventos fenológicos en las tres especies en los dos años de estudio. Con lo anterior se infiere que existen condiciones ambientales idóneas para su desarrollo y que los patrones climáticos inciden sobre la fenología de las especies de mangle en el área de estudio. Finalmente, las características fenológicas de las especies se proponen como insumo importante para la adopción de medidas de manejo como procesos de restauración, pues permiten conocer los periodos de tiempo indicados para realizar actividades de recolecta de propágulos, montaje de viveros y siembra de plántulas en zonas degradadas

Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in the Greater Hinggan Mountain Area: The Algorithm and Application for Eliminating Phenological Impacts

Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent growth period to study the vegetation restoration after the Greater Hinggan Mountain forest fire in the year 1987. The influence of phenology on vegetation monitoring was analyzed through three aspects: band characteristics, normalized difference vegetation index (NDVI) and disturbance index (DI) values. The comparison of the band characteristics shows that in the blue band and the red band, the average reflectance values of the study area after eliminating phenological influence is lower than that without eliminating the phenological influence in each year. In the infrared band, the average reflectance value after eliminating the influence of phenology is greater than the value with phenological influence in almost every year. In the second shortwave infrared band, the average reflectance value without phenological influence is lower than that with phenological influence in almost every year. The analysis results of NDVI and DI values in the study area of each year show that the NDVI and DI curves vary considerably without eliminating the phenological influence, and there is no obvious trend. After eliminating the phenological influence, the changing trend of the NDVI and DI values in each year is more stable and shows that the forest in the region was impacted by other factors in some years and also the recovery trend. The results show that the spatio-temporal data fusion approach used in this study can eliminate vegetation phenology effectively and the elimination of the phenology impact provides more reliable information about changes in vegetation regions affected by the forest fires. The results will be useful as a reference for future monitoring and management of forest resources

A novel approach to modelling mangrove phenology from satellite images: a case study from Northern Australia

Around the world, the effects of changing plant phenology are evident in many ways: from earlier and longer growing seasons to altering the relationships between plants and their natural pollinators. Plant phenology is often monitored using satellite images and parametric methods. Parametric methods assume that ecosystems have unimodal phenologies and that the phenology model is invariant through space and time. In evergreen ecosystems such as mangrove forests, these assumptions may not hold true. Here we present a novel, data-driven approach to extract plant phenology from Landsat imagery using Generalized Additive Models (GAMs). Using GAMs, we created models for six different mangrove forests across Australia. In contrast to parametric methods, GAMs let the data define the shape of the phenological curve, hence showing the unique characteristics of each study site. We found that the Enhanced Vegetation Index (EVI) model is related to leaf production rate (from in situ data), leaf gain and net leaf production (from the published literature). We also found that EVI does not respond immediately to leaf gain in most cases, but has a two- to three-month lag. We also identified the start of season and peak growing season dates at our field site. The former occurs between September and October and the latter May and July. The GAMs allowed us to identify dual phenology events in our study sites, indicated by two instances of high EVI and two instances of low EVI values throughout the year. We contribute to a better understanding of mangrove phenology by presenting a data-driven method that allows us to link physical changes of mangrove forests with satellite imagery. In the future, we will use GAMs to (1) relate phenology to environmental variables (e.g., temperature and rainfall) and (2) predict phenological changes

Los biotipos del bosque del manglar de Puerto Pizarro – Tumbes y su relación con la capacidad de secuestro de carbono y valoración económica durante las estaciones del año

El ecosistema del bosque del manglar de Puerto Pizarro (Tumbes, Perú) con sus biotipos más abundantes Rhizophora mangle, Avicennia germinans y Laguncularia racemosa, concibe diversos bienes y servicios al ambiente, entre estos, la captura de carbono, se requiere de información básica para implementar medidas en su utilización, con estrategias de mitigación y valoración por el importante servicio ambiental que ofrecen. El objetivo fue cuantificar y valorar económicamente la reserva de carbono por biotipo durante las estaciones climatológicas. El área de estudio fue de 830,14 ha, la muestra de campo estuvo constituida por 41 parcelas de 1 ha. La metodología de la investigación comprendió los protocolos utilizados por Kauffman et al. (2013) para carbono de manglar, y las tablas de volúmenes para tres especies de mangle utilizadas por Prestegui (2014). Utilizando ecuaciones alométricas, no se utilizó el método destructivo. Los árboles de R. mangle, conservaron los árboles de mayor DAP (Diámetro a la altura del pecho) y capturaron el 6,02% del Carbono, como incremento durante las estaciones, durante el verano se capturó el mayor porcentaje promedio 2,72%, (respecto a la biomasa inicial), los árboles de 15,0 a 19,9 cm de DAP capturaron el 3,26% durante el verano. Por biotipo la mayor captura de carbono se dio en L. racemosa, a continuación A. germinans y R. mangle. Las tres especies almacenaron carbono en 86,5 t/ha CO2 e valorizado en $ 5 023,6/ha. Estos valores expresan su importancia para que los beneficios puedan ser utilizados con los actuales mecanismos de mercado y ayuden al trabajo local de preservación. El resultado expresó que la biomasa y la reserva de carbono tuvieron mayor incremento en verano, según la dimensión diamétrica y la población de cada biotipo y la mejor estación climatológica fue verano

Examining spatiotemporal changes in the phenology of Australian mangroves using satellite imagery

Nicolás Younes investigated the phenology of Australian mangroves using satellite imagery, field data, and generalized additive models. He found that satellite-derived phenology changes with location, frequency of observation, and spatial resolution. Nicolás challenges the common methods for detecting phenology and proposes a data-driven approach