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1. Explaining Patterns of Biodiversity Across Neon Sites Using Landsat-Based Disturbance Metrics

   https://doi.org/10.1109/IGARSS47720.2021.9554859  

   Van Doninck, Jasper; Smith, Annie C.; Knott, Jon; Record, Sydne; Zarnetske, Phoebe L. (July 2021, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS)

   Disturbance regimes can strongly influence geographic patterns of biodiversity. The types of disturbances and their frequencies can have varying impacts on different dimensions of biodiversity and taxonomic groups, and their influence can also vary with spatial scale. Yet disturbance layers are lacking at sufficiently high spatial resolution and extent to uncover these relationships with biodiversity. We detected disturbances for the conterminous United States from Landsat time series using the established LandTrendr temporal segmentation with a novel secondary classification that incorporates spatial context. We then included these disturbance layers, aggregated to metrics at different temporal and spatial scales, into model of species richness at National Ecological Observatory Network sites. 

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2. Monitoring Forest Infestation and Fire Disturbance in the Southern Appalachian Using a Time Series Analysis of Landsat Imagery

   https://doi.org/10.3390/rs12152412  

   Khodaee, Mahsa; Hwang, Taehee; Kim, JiHyun; Norman, Steven P.; Robeson, Scott M.; Song, Conghe (August 2020, Remote Sensing)

   null (Ed.)

   The southern Appalachian forests have been threatened by several large-scale disturbances, such as wildfire and infestation, which alter the forest ecosystem structures and functions. Hemlock Woolly Adelgid (Adelges tsugae Annand, HWA) is a non-native pest that causes widespread foliar damage and eventual mortality, resulting in irreversible tree decline in eastern (Tsuga canadensis) and Carolina (T. caroliniana) hemlocks throughout the eastern United States. It is important to monitor the extent and severity of these disturbances over space and time to better understand their implications in the biogeochemical cycles of forest landscapes. Using all available Landsat images, we investigate and compare the performance of Tasseled Cap Transformation (TCT)-based indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Disturbance Index (DI) in capturing the spectral-temporal trajectory of both abrupt and gradual forest disturbances (e.g., fire and hemlock decline). For each Landsat pixel, the temporal trajectories of these indices were fitted into a time series model, separating the inter-annual disturbance patterns (low frequency) and seasonal phenology (high frequency) signals. We estimated the temporal dynamics of disturbances based on the residuals between the observed and predicted values of the model, investigated the performance of all the indices in capturing the hemlock decline intensity, and further validated the results with the number of individual dead hemlocks identified from high-resolution aerial images. Our results suggested that the overall performance of NDVI, followed by TCT wetness, was most accurate in detecting both the disturbance timing and hemlock decline intensity, explaining over 90% of the variability in the number of dead hemlocks. Despite the overall good performance of TCT wetness in characterizing the disturbance regime, our analysis showed that this index has some limitations in characterizing disturbances due to its recovery patterns following infestation. 

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3. Not-so-random forests: Comparing voting and decision tree ensembles for characterizing partial harvest events

   https://doi.org/10.1016/j.jag.2023.103561  

   Pasquarella, Valerie J.; Morreale, Luca L.; Brown, Christopher F.; Kilbride, John B.; Thompson, Jonathan R. (December 2023, International Journal of Applied Earth Observation and Geoinformation)

   Ensemble-based change detection can improve map accuracies by combining information from multiple datasets. There is a growing literature investigating ensemble inputs and applications for forest disturbance detection and mapping. However, few studies have evaluated ensemble methods other than Random Forest classifiers, which rely on uninterpretable “black box” algorithms with hundreds of parameters. Additionally, most ensemble-based disturbance maps do not utilize independently and systematically collected field-based forest inventory measurements. Here, we compared three approaches for combining change detection results generated from multi-spectral Landsat time series with forest inventory measurements to map forest harvest events at an annual time step. We found that seven-parameter degenerate decision tree ensembles performed at least as well as 500-tree Random Forest ensembles trained and tested on the same LandTrendr segmentation results and both supervised decision tree methods consistently outperformed the top-performing voting approach (majority). Comparisons with an existing national forest disturbance dataset indicated notable improvements in accuracy that demonstrate the value of developing locally calibrated, process-specific disturbance datasets like the harvest event maps developed in this study. Furthermore, by using multi-date forest inventory measurements, we are able to establish a lower bound of 30% basal area removal on detectable harvests, providing biophysical context for our harvest event maps. Our results suggest that simple interpretable decision trees applied to multi-spectral temporal segmentation outputs can be as effective as more complex machine learning approaches for characterizing forest harvest events ranging from partial clearing to clear cuts, with important implications for locally accurate mapping of forest harvests and other types of disturbances. 

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4. Structural complexity and primary production resistance are coupled in a temperate forest

   https://doi.org/10.3389/ffgc.2022.941851  

   Niedermaier, Kerstin M.; Atkins, Jeff W.; Grigri, Maxim S.; Bond-Lamberty, Ben; Gough, Christopher M. (July 2022, Frontiers in Forests and Global Change)

   The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response. 

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5. Long‐term responses to large‐scale disturbances: spatiotemporal variation in gastropod populations and communities

   https://doi.org/10.1111/oik.09605  

   Presley, Steven J.; Willig, Michael R. (July 2023, Oikos)

   The Anthropocene is characterized by complex, primarily human‐generated, disturbance regimes that include combinations of long‐term press (e.g. climate change, pollution) and episodic pulse (e.g. cyclonic storms, floods, wildfires, land use change) disturbances. Within any regime, disturbances occur at multiple spatial and temporal scales, creating complex and varied interactions that influence spatiotemporal dynamics in the abundance, distribution and biodiversity of organisms. Moreover, responses to disturbance are context dependent, with the legacies of previous disturbances affecting responses to ensuing perturbations. We use three decades of annual data to evaluate the effects of repeated pulse disturbances and global warming on gastropod populations and communities in Puerto Rico at multiple spatial scales. More specifically, we quantify 1) the relative importance of large‐scale and small‐scale aspects of disturbance on variation in abundance, biodiversity and species composition; and 2) the spatial scales at which populations and communities integrate information in the spatially heterogenous environments created by disturbances. Gastropods do not exhibit consistent decreases in abundance or biodiversity in association with global warming: abundance for many species has increased over time and species richness does not evince a temporal trend. Nonetheless, gastropods are sensitive to hurricane severity, spatial environmental variation and successional trajectories of the flora. In addition, they exhibit context dependent (i.e. legacy effects) responses that are scale dependent. The Puerto Rican biota has evolved in a disturbance‐mediated system. This historical exposure to repeated, severe hurricane‐induced disturbances has imbued the biota with high resistance and resilience to the current disturbance regime, resulting in an ability to persist or thrive under current environmental conditions. Nonetheless, these ecosystems may yet be threatened by worsening direct and indirect effects of climate change. In particular, more frequent and severe hurricanes may prevent the establishment of closed canopy forests, negatively impacting populations and communities that rely on these habitats. 

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