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The literature shows that communities under different socio-economic conditions suffer different levels of damage in disasters. In addition to the physical intensity of hazards, such differences are also related to the varying abilities of communities to prepare for and respond to disasters. This study analyzes the spatial patterns of building damage in Hurricane Ian in 2022 and investigates the socio-economic disparities related to the damage. Specifically, this study employs NASA's Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane. Then, it uses statistical analysis to assess the relationships between building damage and hurricane intensity, building conditions, and socio-economic variables at the building and census tract levels. Furthermore, the study applies geographically weighted regression (GWR) to examine the spatial variation of the damage factors. The results provide valuable insights into the potential factors related to building damage and the spatial variation in the factors. The results also reveal the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience. Moreover, the study provides actionable information for policymakers, emergency responders, and community leaders in formulating strategies to mitigate the impact of future hurricanes by identifying vulnerable communities and population groups. [ABSTRACT FROM AUTHOR]

An estimated 2.7 million septic systems in Florida, USA are potential ground and surface water contaminant sources that may affect environmental and human health. This study examined the spatial distribution of septic systems, coastal surface water contamination, and related environmental factors of coastal Florida watersheds at the 8-digit hydrologic unit code level. Hydrology, in situ sampling data, and other ancillary data were combined in a geographic information system to examine spatial relationships. Spatial distribution data were correlated to nitrogen, Enterococci counts, and beach closures tabulated since 2000, 2007, and 2012. Significant positive correlations (α = 0.05) with nitrogen and Enterococci counts were consistent for percent agricultural cover, percent combined urban and agricultural cover, septic tank density, population density, and septic tank density in poorly drained soils. Beach closures since 2012 were significantly positively correlated (α = 0.05) to average impervious cover (IC) and percent urbanization. Statistics indicated that Enterococci counts, nitrogen, and beach closures may be related to specific environmental factors and septic tank densities. The combination of septic tanks in urban regions with high IC prone to elevated runoff could also be a factor in surface water contamination. Data availability was also highlighted as a limitation due to infrequent spatial and temporal sampling. [ABSTRACT FROM AUTHOR]

With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class. [ABSTRACT FROM AUTHOR]

Traditionally, the criteria used to measure conservation success or failure are based on biological factors. Biological factors include changes in the amount of targeted conserved species, biodiversity, and total area conserved. However, conservation efforts are not simply a matter of biological concern; environmental, political, social, and conflict pressures on different scales (ranging from local to global) also have strong influences on the outcome of conservation. These other factors can either pose threats to or enhance conservation, but are not addressed by current criteria. Using a proposed holistic rubric that includes interdisciplinary fields, this paper examines a set of conservation factors on different scales – ranging from local to global – to determine their importance in conservation. The paper analyses positive factor influences with more successful conservation and negative factor influences with less successful, or failed, conservation attempts. Neutral and non‐applicable factor influences are also identified, defined, and ranked as a standardization mechanism. The determination of success changed when the holistic rubric was applied to conservation projects in Costa Rica, Mekong Valley, and Cameroon. In the Costa Rica case study, conservation success for Guanacaste and Talamanca national parks is rated ‘moderately low’. In the case of Mekong Valley, conservation success is rated ‘low’ for Lower Mekong, ‘moderately low’ for Greater Annamites, and ‘low’ for Phong Nha‐Ke Bang national parks. Cameroon's Congo Basin and Sangha Tri‐National conservation efforts are both rated ‘low’, while Dja Faunal is rated ‘very low’. We conclude that if conservation efforts are to attain a high level of success, the strategy for global conservation must move away from the traditional biological approach, which focuses mainly on biological concerns, and embrace a holistic approach, which in addition to biological concerns, addresses environmental, political, social, and conflict pressures, which have strong influences on the outcomes of conservation. [ABSTRACT FROM AUTHOR]