Hurricane-induced rainfall is a stronger predictor of tropical forest damage in Puerto Rico than maximum wind speeds

Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems

Impacts of Hurricane Maria on Land and Convection Modification Over Puerto Rico

Hurricane Maria drastically altered the landscape across the island of Puerto Rico. This article investigates modifications to surface-atmospheric interactions due to Hurricane Maria induced land damage and the associated impacts on local convective dynamics. Herein, we employed LANDSAT-8 image mosaics to quantify the hurricane induced land modification. Results of the analysis indicate that the island suffered significant forest damage—much of which registered as a 28.35% increase in barren land and a 10.85% increase in pasture. Smaller changes included a decrease in cultivated agricultural land cover by 0.76%, along with wetland and water increases of 0.62% and 0.25%, respectively. Pre and post-Maria land classifications were then assimilated into the Regional Atmospheric Modeling System cloud resolving model for the simulation of the June 23 to July 2, 2018 period under two land conditions. Results of the numerical experiments indicate that surface to atmosphere interactions were significantly modified when the land cover was altered, and that the highest deviations between pre- and post-Maria convection occurred over elevated areas with extreme hurricane induced land changes, such as the Cordillera Central mountain range and the El Yunque rainforest

MONITORING CANOPY CHANGE CAUSED BY HURRICANES: LIDAR VS OPTICAL REMOTELY SENSED DATA

Hurricanes and other extreme weather events cause immense amounts of environmental damages across varieties of human and natural systems. Canopies are among the most vulnerable to extreme wind and precipitation brought by hurricanes due to their elevated positions. This study evaluates the effectiveness of using optical remotely sensed data in monitoring forest canopy damage in relation to canopy height changes derived from LiDAR data following two major hurricanes: Hurricane Florence in 2018 and Hurricane Maria in 2017. The study found that LiDAR data is effective in capturing the canopy damage before and after the disturbance events, while the Enhanced Vegetation Index (EVI) derived from optical imagery for the same area during the same time did not show the same level of sensitivity to canopy changes. The finding implies that timely LiDAR data collection is indispensable for accurate canopy damage assessment by agencies, such as NASA or NOAA following hurricane disturbances.Master of Art

Using low-cost remote sensing data for geohazard modelling and analysis in Small Island Developing States (examples of Dominica and Cape Verdes).

Geohazards such as flooding and debris flows pose serious threats to livelihood, the physical and built environment especially in mountainous Small Island Developing States (SIDS). Geohazards cause an economic loss of over $2 billion and approximately 300 to 600 deaths and injuries across the Caribbean and Pacific SIDS annually. To mitigate the negative impacts of flooding and debris flow, it is necessary to model and map areas that that susceptible to these hazards and to inform local officials about the potential risk. The study was undertaken on selected localities in two SIDS, specifically Dominica and the Cape Verde. These islands lie on the Atlantic Hurricane Line and are prone to hazards such as flooding and debris flow. A typical example is the 2017 Hurricane Maria that triggered landslides, debris flows and flooding in Dominica, causing substantial loss of life, destruction of properties and economic losses. These islands are SIDS and so they face major challenges in tackling these hazards due to limited financial and human resources coupled with lack of technological advancement. This study utilised low-cost remote sensing data such as drone-derived DEMs and orthophotographs in RAMMS and HEC-RAS to model and map areas vulnerable to debris flow and flooding hazards. Movement of boulders during Hurricane Maria aggravated the level of damages to properties and infrastructures. Therefore, drone-derived orthophotographs were applied in ImageJ to analyse size of boulders moved in relations to the damages and fatalities recorded. Results of the study demonstrated that these methods can be applied in other SIDS to mitigate impact of geohazards such as floods and debris flow

Tradeoffs and synergies among ecosystem services, biodiversity conservation, and food security in 2 coffee agroforestry

Concerns over the capacity of the world’s existing agricultural land to provide food for the global population under climate change and continued biodiversity loss have set the stage for a prevailing narrative of inherent tradeoffs with agricultural production. However, a strict focus on increasing production can undermine attempts to build more sustainable and equitable food systems. Coffee, a major export crop of tropical countries, offers a unique opportunity to examine how management practices can drive a variety of outcomes for food security, ecosystem services, and biodiversity conservation. Our study examined this intersection to identify tradeoffs and synergies using compiled data from Puerto Rico. At the island level, we analyzed data on coffee yield and area sown under shade or sun management. At the farm level, we analyzed management variables (percent shade cover, maximum canopy height, ground cover, and crop richness), non-provisioning ecosystem service variables (total farm carbon storage, soil organic carbon storage, coffee plant carbon biomass, and hurricane resistance and resilience), and biodiversity variables (ant, bird, and lizard richness and abundance). At the island level, we found that area sown was the most significant predictor of yield, suggesting no obvious tradeoff between yield and shade in coffee farms. At the farm level, canopy cover was negatively correlated with ground cover and positively correlated with crop richness, suggesting a synergy between agroforestry and food security. We detected mostly synergies resulting from agroforestry management and no tradeoffs among ecosystem services and biodiversity. Shade canopy cover significantly increased total carbon storage, coffee plant biomass, hurricane resistance and bird species richness. Shade canopy height had a similar positive effect on total farm carbon storage while crop richness had a positive effect on farm resilience following Hurricane Maria. Ground cover was positively associated with soil carbon storage and pest-controlling lizard abundance. Tradeoffs related to agroforestry management included an inverse relationship between ground cover and hurricane resistance, and greater dominance of an invasive ant species in farms with higher shade canopies. We discuss implications of practicing agroforestry principles in this smallholder coffee system and highlight opportunities for maximizing biodiversity conservation, ecosystem services, and food security.Master of ScienceSchool for Environment and SustainabilityUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/167238/1/Mayorga, Bella_Thesis.pd

Cultural Heritage and Local Ecological Knowledge under Threat: Two Caribbean Examples from Barbuda and Puerto Rico

While the impacts to the infrastructures in Barbuda and Puerto Rico by Hurricanes Irma and Maria have received attention in the news media, less has been reported about the impacts of these catastrophic events on the tangible and intangible cultural heritage of these Caribbean islands. This report provides an assessment of the impacts on the cultural heritage by these storms; tangible heritage includes historic buildings, museums, monuments, documents and other artifacts and intangible heritage includes traditional artistry, festivities, and more frequent activities such as religious services and laundering. While the physical destruction was massive, the social contexts in which these islands existed lessened the resiliency of the people to respond and rebuild after the storms. While change may be inevitable for Barbuda and Puerto Rico, disaster capitalism is threatening the cultures of the people, and may result in the loss of local knowledge and practices

Stem-inhabiting fungal communities differ between intact and snapped trees after hurricane Maria in a Puerto Rican tropical dry forest

Hurricanes impact forests by damaging trees and altering multiple ecosystem functions. As such, predicting which individuals are likely to be most affected has crucial economic importance as well as conservation value. Tree stem-inhabiting fungal communities, notably rot-causing agents, have been mentioned as a potential factor of tree predisposition to hurricane damage, but this assumption remains poorly explored. To examine this relationship, we sampled the stem wood of intact and damaged trees shortly after Hurricane Maria in a Puerto Rican dry tropical forest in 2017. We categorized samples depending on two types: trees with intact stems and trees in which stems were snapped. We extracted fungal environmental DNA of wood from 40 samples consisting of four different tree species. Fungal community taxonomic and functional richness and composition was assessed using high-throughput DNA metabarcoding. We found that snapped trees harbored significantly higher fungal operational taxonomic unit (OTU) richness than the intact trees and that the composition of the stem-inhabiting fungal communities diverged consistently between intact and snapped trees. On average, snapped trees’ fungal communities were relatively enriched in “other saprotrophs” guild category and depleted in endophytes. Conversely, intact trees had high relative abundances of Clonostachys, a mycoparasitic endophyte, suggesting that endophytic fungi might act as biocontrols in tree stems. Overall, our results support the hypothesis that stem-inhabiting fungal communities could represent a predisposition factor of tree damage caused by hurricanes in tropical dry forests

Lower socioeconomic status neighborhoods in Puerto Rico have more diverse mosquito communities and higher Aedes aegypti abundance

Mosquito community dynamics in urban areas are influenced by an array of both social and ecological factors. Human socioeconomic factors (SEF) can be related to mosquito abundance and diversity as urban mosquito development sites are modified by varying human activity, e.g., level of abandoned structures or amount of accumulated trash. The goal of this study was to investigate the relationships among mosquito diversity, populations of Aedes aegypti, and SEF in a tropical urban setting. Mosquitoes were collected using BG Sentinel 2 traps and CDC light traps during three periods between late 2018 and early 2019 in San Juan, Puerto Rico, and were identified to species. SEFs (i.e. median household income, population density, college-level educational attainment, unemployment, health insurance coverage, percentage of households below the poverty line, amount of trash and level of abandoned homes) were measured using foot surveys and U.S. Census data. We found 19 species with the two most abundant species being Culex quinquefasciatus (n = 10 641, 87.6%) and Ae. aegypti (n = 1558, 12.8%). We found a positive association between Ae. aegypti abundance and mosquito diversity, which were both negatively related to SES and ecological factors. Specifically, lower socioeconomic status neighborhoods had both more Ae. aegypti and more diverse communities, due to more favorable development habitat, indicating that control efforts should be focused in these areas

A multi-temporal landsat satellite imagery analysis

The Central Region of Mozambique (Sofala Province) bordering on the active cyclone area of the southwestern Indian Ocean has been particularly affected by climate hazards. The Cyclone Idai, which hit the region in March 2019 with strong winds causing extensive flooding and a massive loss of life, was the strongest recorded tropical cyclone in the Southern Hemisphere. The aim of this study was to use pre-and post-cyclone Idai Landsat satellite images to analyze temporal changes in Land Use and Land Cover (LULC) across the Sofala Province. Specifically, we aimed—(i) to quantify and map the changes in LULC between 2012 and 2019; (ii) to investigate the correlation between the distance to Idai’s trajectory and the degree of vegetation damage, and (iii) to determine the damage caused by Idai on different LULC. We used Landsat 7 and 8 images (with 30 m resolution) taken during the month of April for the 8-year period. The April Average Normalized Difference Vegetation Index (NDVI) over the aforementioned period (2012–2018, pre-cyclone) was compared with the values of April 2019 (post-cyclone). The results showed a decreasing trend of the productivity (NDVI 0.5 to 0.8) and an abrupt decrease after the cyclone. The most devastated land use classes were dense vegetation (decreased by 59%), followed by wetland vegetation (−57%) and shrub land (−56%). The least damaged areas were barren land (−23%), barren vegetation (−27%), and grassland and dambos (−27%). The Northeastern, Central and Southern regions of Sofala were the most devastated areas. The Pearson Correlation Coefficient between the relative vegetation change activity after Idai (NDVI%) and the distance to Idai’s trajectory was 0.95 (R-square 0.91), suggesting a strong positive linear correlation. Our study also indicated that the LULC type (vegetation physiognomy) might have influenced the degree of LULC damage. This study provides new insights for the management and conservation of natural habitats threatened by climate hazards and human factors and might accelerate ongoing recovery processes in the Sofala Province.publishersversionpublishe

Index-based Approach with Remote Sensing for the Assessment of Extreme Weather Impact on Watershed Vegetation Dynamics

Spatial technologies such as satellite remote sensing can be used to identify vegetation dynamics over space and time, which play a critical role in earth observations. Biophysical and biochemical features associated with vegetation cover can then be used to elucidate climate change impact such as floods and droughts on ecosystem that may in turn affect watershed-scale water resources management. Unlike single flood or drought event, intermittent extreme weather events may exert more physiological and biological pressures on the canopy vegetation. This study aims to investigate the climate change impacts on canopy vegetation, which occurred from March 2017 to October 2017 in the Santa Fe River Watershed, Florida, the United States of America. First, this study explores the effect of Hurricane Irma on vegetation dynamics via the pre and post landfall conditions in terms of biophysical and biochemical features. The environmental system analysis compares a suite of remote sensing indices: enhanced vegetation index (EVI), leaf area index (LAI), fraction of photosynthetically active radiation (FPAR), evapotranspiration (ET), land surface temperature (LST), gross primary productivity (GPP), and global vegetation moisture index (GVMI) for a holistic assessment. The satellite images from MODIS (Moderate Resolution Imaging Spectroradiometer) were projected from the MODIS Sinusoidal projection to WGS84 geographic coordination systems to conduct the essential spatial analysis. In addition, the evolution of features associated with the vegetation was analyzed in terms of a new indicator, the functional capacity of the different land uses for grassland, evergreen forested, deciduous forested, and agricultural land uses to elevate our understanding of the ecosystem\u27s sustainability and possible recovery processes as a response to damage caused by the Hurricane Irma event. Urban land use and open water space showed a low level of EVI, LAI, FPAR, GVMI, whereas LST and ET were significantly higher compared to the forested and agricultural land uses. Coupling LAI and LST,EVI and GVMI, or EVI and LST confirms the hypotheses of the study, namely that biophysical features pre and post landfall of Hurricane Irma exhibit significant spatial and temporal variations, and integration of pairwise comparisons of biophysical and biochemical features can better portray the impacts driven by the landfall of Hurricane Irma than a single biophysical feature. The functional capacity of the ecosystem can be derived in terms of EVI, LAI, GVMI, and LST analysis over grassland, evergreen forested, deciduous forested, and agricultural land to quantitively reflect the ecosystem response due to landfall of Hurricane Irma. Secondly, emphasis was placed on determining the impacts of alternating adverse flood and drought events on four vegetative land use types via remote sensing and contrasting the vegetation canopy resilience, resistance, and elasticity in intermittent extreme weather events from March to Oct. 2017 in the same subtropical watershed. Nonlinear extreme weather events in sequence discriminated the marginal resilience, resistance, and thus elasticity of four land uses showing high resilience and elasticity in transitions of dry and wet events. It is indicative that thermodynamics driven LST served as the energy source that explains the forcing of variations of these vegetation indices and sustainability indicators