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Extreme climate events such as storms and severe droughts are becoming more frequent under the warming climate. In the tropics, excess rainfall carried by hurricanes causes massive flooding and threatens ecosystems and human society. We assessed recent major floodings on the tropical island of Puerto Rico after Hurricane Maria in 2017 and Hurricane Fiona in 2022, both of which cost billions of dollars damages to the island. We analyzed the Sentinel-1 synthetic aperture radar (SAR) images right after the hurricanes and detected surface inundation extent by applying a random forest classifier. We further explored hurricane rainfall patterns, flow accumulation, and other possible drivers of surface inundation at watershed scale and discussed the limitations. An independent validation dataset on flooding derived from high-resolution aerial images indicated a high classification accuracy with a Kappa statistic of 0.83. The total detected surface inundation amounted to 10,307 ha after Hurricane Maria and 7949 ha after Hurricane Fiona for areas with SAR images available. The inundation patterns are differentiated by the hurricane paths and associated rainfall patterns. We found that flow accumulation estimated from the interpolated Fiona rainfall highly correlated with the ground-observed stream discharges, with a Pearson's correlation coefficient of 0.98. The detected inundation extent was found to depend strongly on hurricane rainfall and topography in lowlands within watersheds. Normal climate, which connects to mean soil moisture, also contributed to the differentiated flooding extent among watersheds. The higher the accumulated Fiona rain and the lower the mean elevation in the flat lowlands, the larger the detected surface flooding extent at the watershed scale. Additionally, the drier the climate, which might indicate drier soils, the smaller the surface flooding areas. The approach used in this study is limited by the penetration capability of C-band SAR; further application of L-band images would expand the detection to flooding under dense vegetation. Detecting flooding by applying machine learning techniques to SAR satellite images provides an effective, efficient, and reliable approach to flood assessment in coastal regions on a large scale, hence helping to guide emergency responses and policy making and to mitigate flooding disasters. [ABSTRACT FROM AUTHOR]

Reforestation often occurs when the economy shifts from agriculture to industry and services such as tourism. However, there is a lack of coherent knowledge and investigation about the impact of reforestation in the tropics on hydrological variability as well as flood risks. It is unclear how changes in forest cover and pattern will affect flood risks and watershed response to future altered rainfall intensity. This study uses the Soil Water Assessment Tool (SWAT+) to simulate the impact of reforestation, the locality of forest, and the concentrated rainfall on the hydrology of the largest watershed in Puerto Rico. SWAT+ is a computer model simulating watershed hydrology driven by meteorological input and the characteristics of soils and land use. We hypothesized that increased forest cover, especially at low elevation range, would reduce flood risk and that reduced rain days while maintaining the mean annual rainfall invariant would increase stream discharge variability. We found that reforestation significantly reduced large discharges but increased small discharges; that forest at low elevation tended to reduce large and extreme discharges in comparison with forest at high elevation; and that more concentrated rainfall not only increased the rainfall variability but also increased the discharge variability. However, both the impact of shifting forest locality and the response of watershed to altered rainfall intensity strongly depended on geophysical factors such as ranges of elevation and slope. Moving forests to lower elevation in subbasins with steeper slopes showed a stronger reduction in extreme discharges than in subbasins with flatter slopes. On the other hand, subbasins with steeper slopes tended to response more strongly to more concentrated rainfall with greater increase in discharge variability than subbasins with flatter slopes. To cope with future increased climate variability, our results favor reforestation at lower elevation for watershed with large elevation ranges and steep slopes. [ABSTRACT FROM AUTHOR]

Context: Hurricanes are major threats to coastal mangrove ecosystems. Inundation has been implicitly reported to associate with mangrove damages and mortality. However, there have been no spatial statistical analyses of the impact of inundation on mangrove recovery at landscape scales. Objectives: Our objectives are to detect spatiotemporal patterns of inundation after major hurricanes and to explore explicitly the role of inundation in mangrove recovery at landscape scale. Methods: Using C-band Synthetic Aperture Radar images, we detected the spatiotemporal pattern of surface flood and derived the spatial distribution of inundation depth under mangrove canopies based on surrounding surface flood and elevation along northern Puerto Rico coasts after major hurricanes in 2017. Based on the Enhanced Vegetation Index, we derived the short-term hurricane impact and the recovery ratio from 2018 to 2021, and analyzed the impact and the recovery of mangrove greenness by means of spatial error models. Results: The identification of surface flood reached very high accuracy. The severe impact is significantly explained by greater gust windspeed during the hurricane and lower elevation. More importantly, retarded mangrove greenness recovery is significantly explained by severer impacts, longer and deeper inundation, and heavier hurricane rainfall. Conclusions: Spatiotemporal heterogeneity in flood depth plays a significant and essential role in mangrove recovery and delayed mortality after major hurricanes. The derived flood depth turns out to be a better explanator of mangrove recovery than elevation, which highlights importance of landscape hydrology and topography with respect to mangrove response and restoration after major hurricanes. [ABSTRACT FROM AUTHOR]

The coastal mangrove forest bears important ecosystem functions and services, including the protection of shorelines and coastal communities. While coastal mangroves often suffer severe damage during storms, understanding the vulnerability and resistance of mangroves to the damage at a landscape scale is crucial for coastal mangrove management and conservation. In September 2017, two consecutive major hurricanes caused tremendous damage to the coastal mangroves in the Caribbean. By utilizing LiDAR data taken before and after the hurricanes in a basin mangrove forest in Northeast Puerto Rico, we analyzed the spatial variation of a canopy structure before the hurricanes and hurricane-induced canopy height reduction and explored possible drivers by means of spatial regressions. Regarding the canopy structure, we found that the pre-hurricane canopy height of the mangrove forest decreased with elevation and distance to the freshwater/sewage canals within the forest, and these two drivers explained 82% of variations in the mangrove canopy height. The model, thus, implies that freshwater and nutrient inputs brought by the canals tend to promote the canopy height, and mangrove trees at lower elevation are especially more advantageous. Similarly, tree densities decreased with the canopy height but increased with the elevation and the distance to the canals. We also found that this mangrove forest suffered on average a 53% canopy height reduction, reflecting mostly heavy crown defoliation and the rupture of branches. The regression, which explains 88% of spatial variation in the canopy height reduction, showed that mangroves with a higher canopy or lower density, or growing in lower elevation, or being closer to the canals suffered more damage. Our findings indicate that delivered freshwater/sewage by means of human-made canals has a strong impact on the canopy structure as well as its resistance to tropical storms. Freshwater and sewage tend to release the salinity stress and nutrient deficit and, thus, to promote the mangrove canopy height. However, the addition of freshwater and nutrients might also increase the risk of mangrove damage during the storms probably because of an altered allometry of assimilates. [ABSTRACT FROM AUTHOR]

Tropical dry forest is vulnerable to increased climate variability with more frequent and severe storms. Studies of hurricane impact on tropical dry forest often focused on individual tree traits. How trees in tropical dry forests work together to combat wind damage is still unclear. To address this, we integrated ground-observed ecosystem structure from National Ecological Observation Network (NEON) with airborne-LiDAR images and analyzed resistance in forest structure of Guánica dry forest in Puerto Rico to major hurricanes in 2017 at the forest-stand level. Using each plot instead of the individual tree as the base unit, we regressed mean changes in stem height and fractions of lost or damaged stems at 15 plots on mean stem diameter, mean and standard deviation of stem height, stem density, and topography. Meanwhile, using the LiDAR-derived canopy heights, we compared the changes in canopy height before and after the hurricanes and regressed spatially the canopy height change on prior-hurricane tree cover, canopy height, and rugosity. We found that the damage was small in places with high stem density or high tree cover. Ground-observed damage in terms of height reduction significantly increased with the standard deviation of stem height, an index of roughness, but decreased with the mean stem diameter of the plots. LiDAR-detected damage in terms of reduction in canopy height was also found to decrease with tree cover and mean canopy height when the canopy height was small or moderate but increase with the rugosity. The fraction of lost stems significantly decreased with the stem density, and the fraction of damaged stems significantly increased with the roughness and the plot elevation. The collective parameters of forest stand quantified from ground-observation and LiDAR, such as stem density, tree cover, and canopy roughness or rugosity, highlighted mutual supports of trees and played important roles in resisting damages to the tropical dry forest during major hurricanes. [ABSTRACT FROM AUTHOR]

Despite the overall trend of worldwide deforestation over recent decades, reforestation has also been found and is expected in developing countries undergoing fast urbanization and agriculture abandonment. The consequences of reforestation on landscape patterns are seldom addressed in the literature, despite their importance in evaluating biodiversity and ecosystem functions. By analyzing long-term land cover changes in Puerto Rico, a rapidly reforested (6 to 42% during 1940-2000) and urbanized tropical island, we detected significantly different patterns of fragmentation and underlying mechanisms among forests, urban areas, and wetlands. Forest fragmentation is often associated with deforestation. However, we also found significant fragmentation during reforestation. Urban sprawl and suburb development have a dominant impact on forest fragmentation. Reforestation mostly occurs along forest edges, while significant deforestation occurs in forest interiors. The deforestation process has a much stronger impact on forest fragmentation than the reforestation process due to their different spatial configurations. In contrast, despite the strong interference of coastal urbanization, wetland aggregation has occurred due to the effective implementation of laws/regulations for wetland protection. The peak forest fragmentation shifted toward rural areas, indicating progressively more fragmentation in forest interiors. This shift is synchronous with the accelerated urban sprawl as indicated by the accelerated shift of the peak fragmentation index of urban cover toward rural areas, i.e., 1.37% yr-1 in 1977-1991 versus 2.17% yr-1 in 1991-2000. Based on the expected global urbanization and the regional forest transition from deforested to reforested, the fragmented forests and aggregated wetlands in this study highlight possible forest fragmentation processes during reforestation in an assessment of biodiversity and functions and suggest effective laws/regulations in land planning to reduce future fragmentation.