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Harmful algal bloom (HAB) events in front of Pisco River, inside Paracas Bay and Lagunillas inlet on the southern coast of Peru was identified from a satellite index (IOPifa) generated with daily high-resolution satellite data of phytoplankton absorption (aphy,GIOP) and non-algal detrital material plus CDOM (adCDOM,GIOP) from the Generalized Inherent Optical Properties (GIOP) model of Modis-Aqua, Viirs-Snpp and Viirs-Jpss1 satellites were used. Phytoplankton density field data sampling from HAB's monitoring programs of IMARPE of 2018 and 2019 were used to validate and identify the extent and spatio-temporal variability of these events. The satellite index (IOPifa) identified for Modis-Aqua 9 active HABs, 8 events in final conditions and 6 events that do not represent HAB conditions, while for Viirs-Snpp found 14 active HABs, 7 events in decaying bloom conditions and 13 events that do not represent HABs; and for Viirs-Jpss1 the index identified 7 active events, 14 in final bloom conditions and 6 that do not represent HABs conditions. The one-factor anova model was applied (p-value = 0.32 > 0.05), indicating that there is no evidence of a difference in the population means of the indices for each sensor. Subsequently, the pairwise multiple comparisons analysis with a 95 % confidence level of Tukey's test confirmed that there are no significant differences in the satellite index value, the differences could be associated with the spectral characteristics of the cell density of the species community and the oceanographic and environmental conditions. The spatial overlap between the in situ harmful algal blooms areas and the calculated satellite index, shows the capacity of the IOP satellite data for the HABs detection. However, it was also evidenced that some HAB events with high phytoplankton cell density had low IOPifa values, while other events with lower cell density were easily identified by the satellite index. This would indicate the ability of the ocean inherent optical properties to differentiate the phytoplankton types that cause algal blooms.

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Hurricane Katrina (category 5 with maximum wind of 280 km/h when the eye is in the central Gulf of Mexico) made landfall near New Orleans on August 29, 2005, causing millions of cubic meters of disaster debris, severe flooding, and US$125 billion in damage. Yet, despite numerous reports on its environmental and economic impacts, little is known about how much debris has entered the marine environment. Here, using satellite images (MODIS, MERIS, and Landsat), airborne photographs, and imaging spectroscopy, we show the distribution, possible types, and amount of Katrina-induced debris in the northern Gulf of Mexico. Satellite images collected between August 30 and September 19 show elongated image features around the Mississippi River Delta in a region bounded by 92.5°W-87.5°W and 27.8°N-30.25°N. Image spectroscopy and color appearance of these image features indicate that they are likely dominated by driftwood (including construction lumber) and dead plants (e.g., uprooted marsh) and possibly mixed with plastics and other materials. The image sequence shows that if aggregated together to completely cover the water surface, the maximal debris area reached 21.7 km2 on August 31 to the east of the delta, which drifted to the west following the ocean currents. When measured by area in satellite images, this perhaps represents a historical record of all previously reported floating debris due to natural disasters such as hurricanes, floodings, and tsunamis.

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Although the role of livestock in future food systems is debated, animal proteins are unlikely to completely disappear from our diet. Grasslands are a key source of primary productivity for livestock, and feed-food competition is often limited on such land. Previous research on the potential for sustainable grazing has focused on restricted geographical areas or does not consider inter-annual changes in grazing opportunities. Here, we developed a robust method to estimate trends and interannual variability (IV) in global livestock carrying capacity (number of grazing animals a piece of land can support) over 2001-2015, as well as relative stocking density (the reported livestock distribution relative to the estimated carrying capacity [CC]) in 2010. We first estimated the aboveground biomass that is available for grazers on global grasslands based on the MODIS Net Primary Production product. This was then used to calculate livestock carrying capacities using slopes, forest cover, and animal forage requirements as restrictions. We found that globally, CC decreased on 27% of total grasslands area, mostly in Europe and southeastern Brazil, while it increased on 15% of grasslands, particularly in Sudano-Sahel and some parts of South America. In 2010, livestock forage requirements exceeded forage availability in northwestern Europe, and southern and eastern Asia. Although our findings imply some opportunities to increase grazing pressures in cold regions, Central Africa, and Australia, the high IV or low biomass supply might prevent considerable increases in stocking densities. The approach and derived open access data sets can feed into global food system modelling, support conservation efforts to reduce land degradation associated with overgrazing, and help identify undergrazed areas for targeted sustainable intensification efforts or rewilding purposes.

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While weather stations generally capture near-surface ambient air temperature (Ta) at a high temporal resolution to calculate daily values (i.e., daily minimum, mean, and maximum Ta), their fixed locations can limit their spatial coverage and resolution even in densely populated urban areas. As a result, data from weather stations alone may be inadequate for Ta-related epidemiology particularly when the stations are not located in the areas of interest for human exposure assessment. To address this limitation in the Megalopolis of Central Mexico (MCM), we developed the first spatiotemporally resolved hybrid satellite-based land use regression Ta model for the region, home to nearly 30 million people and includes Mexico City and seven more metropolitan areas. Our model predicted daily minimum, mean, and maximum Ta for the years 2003-2019. We used data from 120 weather stations and Land Surface Temperature (LST) data from NASA's MODIS instruments on the Aqua and Terra satellites on a 1 × 1 km grid. We generated a satellite-hybrid mixed-effects model for each year, regressing Ta measurements against land use terms, day-specific random intercepts, and fixed and random LST slopes. We assessed model performance using 10-fold cross-validation at withheld stations. Across all years, the root-mean-square error ranged from 0.92 to 1.92 K and the R 2 ranged from .78 to .95. To demonstrate the utility of our model for health research, we evaluated the total number of days in the year 2010 when residents ≥65 years old were exposed to Ta extremes (above 30°C or below 5°C). Our model provides much needed high-quality Ta estimates for epidemiology studies in the MCM region.

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The Brazilian Cerrado is a global biodiversity hotspot with notoriously high rates of native vegetation suppression and wildfires over the past three decades. As a result, climate change can already be detected at both local and regional scales. In this study, we used three different approaches based on independent datasets to investigate possible changes in the daytime and nighttime temperature and air humidity between the peak of the dry season and the beginning of the rainy season in the Brazilian Cerrado. Additionally, we evaluated the tendency of dew point depression, considering it as a proxy to assess impacts on biodiversity. Monthly increases of 2.2-4.0℃ in the maximum temperatures and 2.4-2.8℃ in the minimum temperatures between 1961 and 2019 were recorded, supported by all analyzed datasets which included direct observations, remote sensing, and modeling data. The warming raised the vapor pressure deficit, and although we recorded an upward trend in absolute humidity, relative humidity has reduced by ~15%. If these tendencies are maintained, gradual air warming will make nightly cooling insufficient to reach the dew point in the early hours of the night. Therefore, it will progressively reduce both the amount and duration of nocturnal dewfall, which is the main source of water for numerous plants and animal species of the Brazilian Cerrado during the dry season. Through several examples, we hypothesize that these climate changes can have a high impact on biodiversity and potentially cause ecosystems to collapse. We emphasize that the effects of temperature and humidity on Cerrado ecosystems cannot be neglected and should be further explored from a land use perspective.

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The space-borne measured fine-mode aerosol optical depth (fAOD) is a gross index of column-integrated anthropogenic particulate pollutants, especially over the populated land. The fAOD is the product of the AOD and the fine-mode fraction (FMF). While there exist numerous global AOD products derived from many different satellite sensors, there have been much fewer, if any, global FMF products with a quality good enough to understand their spatiotemporal variations. This is key to understanding the global distribution and spatiotemporal variations of air pollutants, as well as their impacts on global environmental and climate changes. Modifying our newly developed retrieval algorithm to the latest global-scale Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product (Collection 6.1), a global 10-year FMF product is generated and analyzed here. We first validate the product through comparisons with the FMF derived from Aerosol Robotic Network (AERONET) measurements. Among our 169,313 samples, the satellite-derived FMFs agreed with the AERONET spectral deconvolution algorithm (SDA)-retrieved FMFs with a root-mean-square error (RMSE) of 0.22. Analyzed using this new product are the global patterns and interannual and seasonal variations of the FMF over land. In general, the FMF is large (>0.80) over Mexico, Myanmar, Laos, southern China, and Africa and less than 0.5 in the Sahelian and Sudanian zones of northern Africa. Seasonally, higher FMF values occur in summer and autumn. The linear trend in the satellite-derived and AERONET FMFs for different countries was explored. The upward trend in the FMFs was particularly strong over Australia since 2008. This study provides a new global view of changes in FMFs using a new satellite product that could help improve our understanding of air pollution around the world.

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Problems with vector surveillance are a major barrier for the effective control of vector-borne disease transmission through Latin America. Here, we present results from a 80-week longitudinal study where Aedes aegypti (L.) (Diptera: Culicidae) ovitraps were monitored weekly at 92 locations in Puntarenas, a coastal city in Costa Rica with syndemic Zika, chikungunya and dengue transmission. We used separate models to investigate the association of either Ae. aegypti-borne arboviral cases or Ae. aegypti egg counts with remotely sensed environmental variables. We also evaluated whether Ae. aegypti-borne arboviral cases were associated with Ae. aegypti egg counts. Using cross-correlation and time series modeling, we found that arboviral cases were not significantly associated with Ae. aegypti egg counts. Through model selection we found that cases had a non-linear response to multi-scale (1-km and 30-m resolution) measurements of temperature standard deviation (SD) with a lag of up to 4 weeks, while simultaneously increasing with finely-grained NDVI (30-m resolution). Meanwhile, median ovitrap Ae. aegypti egg counts increased, and respectively decreased, with temperature SD (1-km resolution) and EVI (30-m resolution) with a lag of 6 weeks. A synchrony analysis showed that egg counts had a travelling wave pattern, with synchrony showing cyclic changes with distance, a pattern not observed in remotely sensed data with 30-m and 10-m resolution. Spatially, using generalized additive models, we found that eggs were more abundant at locations with higher temperatures and where EVI was leptokurtic during the study period. Our results suggest that, in Puntarenas, remotely sensed environmental variables are associated with both Ae. aegypti-borne arbovirus transmission and Ae. aegypti egg counts from ovitraps.

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The objectives of this study are: (i) to evaluate the space-temporal variability of fire foci by environmental satellites, CHIRPS and remote sensing products based on applied statistics, and (ii) to identify the relational pattern between the distribution of fire foci and the environmental, meteorological, and socioeconomic variables in the mesoregions of Minas Gerais (MG) - Brazil. This study used a time series of fire foci from 1998 to 2015 via BDQueimadas. The temporal record of fire foci was evaluated by Mann-Kendall (MK), Pettitt (P), Shapiro-Wilk (SW), and Bartlett (B) tests. The spatial distribution by burned area (MCD64A1-MODIS) and the Kernel density - (radius 20 km) were estimated. The environmental variables analyzed were: rainfall (mm) and maximum temperature (°C), besides proxies to vegetation canopy: NDVI, SAVI, and EVI. PCA was applied to explain the interaction between fire foci and demographic, environmental, and geographical variables for MG. The MK test indicated a significant increasing trend in fire foci in MG. The SW and B tests were significant for non-normality and homogeneity of data. The P test pointed to abrupt changes in the 2001 and 2002 cycles (El Niño and La Niña moderated), which contributes to the annual increase and in winter and spring, which is identified by the Kernel density maps. Burned areas highlighted the northern and northwestern regions of MG, Triângulo Mineiro, Jequitinhonha, and South/Southwest MG, in the 3rd quarter (increased 17%) and the 4th quarter (increased 88%). The PCA resulted in three PCs that explained 71.49% of the total variation. The SAVI was the variable that stood out, with 11.12% of the total variation, followed by Belo Horizonte, the most representative in MG. We emphasize that the applied conceptual theoretical model defined here can act in the environmental management of fire risk. However, public policies should follow the technical-scientific guidelines in the mitigation of the resulting socioeconomic - environmental damages.

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Since 2011, huge amounts of Sargassum algae are detected in the equatorial Atlantic, causing large strandings events on the coasts of the West Indies, Brazil and West Africa. The distribution of this stock shows strong annual and interannual variability, whose drivers are not settled yet. Here we use satellite Sargassum observations from MODIS and currents from an ocean reanalysis to simulate the passive transport of algae in 2017. Wind effect was necessary to fit the observed distribution. Simulations reasonably reproduce the satellite monthly distribution for up to seven months, confirming the prominent role of transport in the distribution cycle. Annual cycle appears as a zonal exchange between eastern (EAR) and western accumulation regions (WAR). EAR is well explained by advection alone, with sharp meridional distribution controlled by converging currents below the inter-tropical Convergence Zone. Instead, WAR is not explained by advection alone, suggesting local growth.

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Photosynthesis of the Amazon rainforest plays an important role in the regional and global carbon cycles, but, despite considerable in situ and space-based observations, it has been intensely debated whether there is a dry-season increase in greenness and photosynthesis of the moist tropical Amazonian forests. Solar-induced chlorophyll fluorescence (SIF), which is emitted by chlorophyll, has a strong positive linear relationship with photosynthesis at the canopy scale. Recent advancements have allowed us to observe SIF globally with Earth observation satellites. Here we show that forest SIF did not decrease in the early dry season and increased substantially in the late dry season and early part of wet season, using SIF data from the Tropospheric Monitoring Instrument (TROPOMI), which has unprecedented spatial resolution and near-daily global coverage. Using in situ CO2 eddy flux data, we also show that cloud cover rarely affects photosynthesis at TROPOMI's midday overpass, a time when the forest canopy is most often light-saturated. The observed dry-season increases of forest SIF are not strongly affected by sun-sensor geometry, which was attributed as creating a pseudo dry-season green-up in the surface reflectance data. Our results provide strong evidence that greenness, SIF, and photosynthesis of the tropical Amazonian forest increase during the dry season.

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