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1. Spatial Assessment of Community Resilience from 2012 Hurricane Sandy Using Nighttime Light

   https://doi.org/10.3390/rs13204128  

   Xu, Jinwen; Qiang, Yi (October 2021, Remote Sensing)

   Quantitative assessment of community resilience is a challenge due to the lack of empirical data about human dynamics in disasters. To fill the data gap, this study explores the utility of nighttime lights (NTL) remote sensing images in assessing community recovery and resilience in natural disasters. Specifically, this study utilized the newly-released NASA moonlight-adjusted SNPP-VIIRS daily images to analyze spatiotemporal changes of NTL radiance in Hurricane Sandy (2012). Based on the conceptual framework of recovery trajectory, NTL disturbance and recovery during the hurricane were calculated at different spatial units and analyzed using spatial analysis tools. Regression analysis was applied to explore relations between the observed NTL changes and explanatory variables, such as wind speed, housing damage, land cover, and Twitter keywords. The result indicates potential factors of NTL changes and urban-rural disparities of disaster impacts and recovery. This study shows that NTL remote sensing images are a low-cost instrument to collect near-real-time, large-scale, and high-resolution human dynamics data in disasters, which provide a novel insight into community recovery and resilience. The uncovered spatial disparities of community recovery help improve disaster awareness and preparation of local communities and promote resilience against future disasters. The systematical documentation of the analysis workflow provides a reference for future research in the application of SNPP-VIIRS daily images. 

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2. Multi-Dimensional Output-Oriented Power System Resilience based on Degraded Functionality

   https://doi.org/10.1109/PESGM46819.2021.9638220  

   Valinejad, Jaber; Mili, Lamine; Van Der Wal, C. Natalie; Von Spakovsky, Michael; Xu, Yijun (July 2021, 2021 IEEE Power & Energy Society General Meeting (PESGM))

   Power systems serve social communities that consist of residential, commercial, and industrial customers. As a result, the disaster resilience of a power system should account for social community resilience. The social behavior and psychological features of all stakeholders involved in a disaster influence the level of power system preparedness, mitigation, recovery, adaptability, and resilience. Hence, there is a need to consider the social community's effect on the power system and the dependence between them in determining a power system's resilient to human-made and natural hazards. The social community, such as a county, city, or state, consists of various stakeholders, e.g., social consumers, social prosumers, and utilities. In this paper, we develop a multi-dimensional output-oriented method to measure resilience. The three key ideas for measuring power system resilience are the multi-dimensionality, output-oriented, and degraded functionality aspects of the power system. To this end, we develop an artificial society based on neuroscience, social science, and psychological theories to model the behavior of consumers and prosumers and the interdependence between power system resilience, comsumer and prosumer well-being, and community capital. Both mental health and physical health are used as metrics of well-being, while the level of cooperation is used to measure community capital resilience. 

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3. Dormancy dynamics and dispersal contribute to soil microbiome resilience

   https://doi.org/10.1098/rstb.2019.0255  

   Sorensen, Jackson W.; Shade, Ashley (May 2020, Philosophical Transactions of the Royal Society B: Biological Sciences)

   In disturbance ecology, stability is composed of resistance to change and resilience towards recovery after the disturbance subsides. Two key microbial mechanisms that can support microbiome stability include dormancy and dispersal. Specifically, microbial populations that are sensitive to disturbance can be re-seeded by local dormant pools of viable and reactivated cells, or by immigrants dispersed from regional metacommunities. However, it is difficult to quantify the contributions of these mechanisms to stability without, first, distinguishing the active from inactive membership, and, second, distinguishing the populations recovered by local resuscitation from those recovered by dispersed immigrants. Here, we investigate the contributions of dormancy dynamics (activation and inactivation), and dispersal to soil microbial community resistance and resilience. We designed a replicated, 45-week time-series experiment to quantify the responses of the active soil microbial community to a thermal press disturbance, including unwarmed control mesocosms, disturbed mesocosms without dispersal, and disturbed mesocosms with dispersal after the release of the stressor. Communities changed in structure within one week of warming. Though the disturbed mesocosms did not fully recover within 29 weeks, resuscitation of thermotolerant taxa was key for community transition during the press, and both resuscitation of opportunistic taxa and immigration contributed to community resilience. Also, mesocosms with dispersal were more resilient than mesocosms without. This work advances the mechanistic understanding of how microbiomes respond to disturbances in their environment. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’. 

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4. Functional properties improve predictions of long‐term productivity invariability but not resistance to drought

   https://doi.org/10.1002/ecy.70421  

   Perez, Sierra B; Lau, Jennifer A (May 2026, Ecology)

   Abstract Identifying the factors mediating the resilience and invariability of plant communities and their associated ecosystem functions is critical to understand the ecological impacts of climate change. Prior work has explored how classic “community properties” (characterizing a community by species composition) regulate the resilience and invariability of ecosystem functioning. Mechanistically, community properties influence resilience and invariability via species' traits, and as a result, “functional properties” (characterizing a community via functional traits) might better predict these qualities. For example, functional traits associated with conservative resource‐use strategies (e.g., short stature, low specific leaf area [SLA], high leaf dry matter content [LDMC]) are expected to promote both resistance to periods of stress or resource limitation and long‐term invariability. While there is a strong conceptual basis linking functional traits and functional diversity to resilience and invariability, empirical evidence is thus far mixed, and sourcing accurate functional trait data may be challenging. Therefore, it is important to know if community properties are sufficient for evaluating the resilience and invariability of ecosystem functioning, or if functional properties provide necessary insights. Capitalizing on a decades‐long study, we tested the effects of plant functional and community properties on the resistance of ecosystem functioning (a component of resilience) to drought or long‐term invariability. Including functional properties did not improve our ability to explain primary productivity resistance to droughts but considerably improved our explanatory power for productivity invariability. Our results supported expectations that conservative trait strategies promote ecosystem functioning resistance to perturbations and temporal invariability. These findings highlight that the utility of functional properties in explaining the resilience and invariability of ecosystem functioning may depend on the attribute under consideration and that functional properties may primarily be useful for identifying the traits promoting resilience and invariability. 

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5. Understanding post-disaster population recovery patterns

   https://doi.org/10.1098/rsif.2019.0532  

   Yabe, Takahiro; Tsubouchi, Kota; Fujiwara, Naoya; Sekimoto, Yoshihide; Ukkusuri, Satish V. (February 2020, Journal of The Royal Society Interface)

   null (Ed.)

   Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such extreme events are limited. Here, we study the macroscopic population recovery patterns in disaster affected regions, by observing human mobility trajectories of over 1.9 million mobile phone users across three countries before, during and after five major disasters. We find that, despite the diversity in socio-economic characteristics among the affected regions and the types of hazards, population recovery trends after significant displacement resemble similar patterns after all five disasters. Moreover, the heterogeneity in initial and long-term displacement rates across communities in the three countries were explained by a set of key common factors, including the community’s median income level, population, housing damage rates and the connectedness to other cities. Such insights discovered from large-scale empirical data could assist policymaking in various disciplines for developing community resilience to disasters. 

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