Forest Drought Response Index (ForDRI): A New Combined Model to Monitor Forest Drought in the Eastern United States

Tadesse, Tsegaye; Hollinger, David Y.; Bayissa, Yared A.; Svoboda, M.; Fuchs, Brian; Zhang, Beichen; Demissie, Getachew; Wardlow, Brian D.; Bohrer, Gil; Clark, Kenneth L.; Desai, Ankur R.; Gu, Lianhong; Noormets, Asko; Novick, Kimberly A.; Richardson, Andrew D.

doi:10.20944/preprints202009.0673.v1

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…Potential exists to combine SIF, reflectance, chlorophyll content (or canopy chlorophyll content indices, CCCIs) to extract more information from these data, which provide diagnostic information about biotic and abiotic stressors affecting canopy photosynthesis (Peteinatos et al 2016). New hybrid indices that combine remotely sensed data with climatic data and forest characteristics are also being developed (Tadesse et al 2020) and show promise to provide reliable, large scale indicators of forest drought stress.…”

Section: Forest Healthmentioning

confidence: 99%

A new generation of sensors and monitoring tools to support climate-smart forestry practices

et al. 2021

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Climate-smart forestry (CSF) is an emerging branch of sustainable adaptive forest management aimed at enhancing the potential of forests to adapt to and mitigate climate change. It relies on much higher data requirements than traditional forestry. These data requirements can be met by new devices that support continuous, in-situ monitoring of forest conditions in real time. We propose a comprehensive network of sensors, i.e. a wireless sensor network (WSN), that can be part of a world-wide network of interconnected uniquely addressable objects, an Internet of Things (IoT), which can make data available in near real time to multiple stakeholders, including scientists, foresters, and forest managers, and may partially motivate citizens to participate in big data collection. The use of in-situ sources of monitoring data as ground-truthed training data for remotely sensed data can boost forest monitoring by increasing the spatial and temporal scale of the monitoring, leading to a better understanding of forest processes and potential threats. Here, some of the key developments and applications of these sensors are outlined, together with guidelines for data management. Examples are given of their deployment to detect early warning signals (EWS) of ecosystem regime-shifts in terms of forest productivity, health and biodiversity. Analysis of the strategic use of these tools highlights the opportunities for engaging citizens and forest managers in this new generation of forest monitoring.

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Section: Forest Healthmentioning

confidence: 99%

A new generation of sensors and monitoring tools to support climate-smart forestry practices

et al. 2021

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“…Drought resulted in loss of 5740.9ha dense forest and loss of 5666.2ha of sparse forest in 2017 as compared to 2016 on yabelo forest. Drought resulted in plant mortality as suggested by(Tadesse et al 2020;Ji and Peters 2003). But, based on vegetation types and structure the way forests respond to drought is differ.…”

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confidence: 99%

Impact of Drought on Forest Cover Change in Yabelo Forest in Semi-arid Region of Ethiopia

Wolteji

Gizawu

Gemeda

2022

Preprint

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Drought is a key challenge of third world countries whose economies are based on agriculture. Also, lack of rainfall plays a major role in exacerbating climate change. Drought is resulting in a decline in vegetation greenness and plant mortality specifically in semi-arid region. In this study, satellite-based drought assessment was used to characterize drought, and its impact on forest in semi-arid region of Ethiopia. Drought severity and forest cover change were detected over the period between 2014, and 2022 using geographic information system and remote sensing techniques. Vegetation condition index (VCI) and normalized difference vegetation index (NDVI) are used to detect drought severity over the past decades. Results show that 2015, 2017, 2019and 2022 were the most drought years. The spatial forest covers is significantly decreased during severe drought years. Minimum dense forest was observed in 2017and 2019 over spatial extend of 0.80 ha and 124.6 ha, respectively during drought years. To evaluate how precipitation deficit affect forest function, simple linear regression is performed. Result of (R2=0.49 and P=0.05) indicate that, nearly 50% of forest greenness is influenced by precipitation deficit. This study suggested that remote sensing indices are very crucial to characterize drought pattern at small “scale” particularly in assessment of drought impact on forest resource.

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Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics

Ewane

Mohan

Bajaj³

et al. 2023

Remote Sensing

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Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner.

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Forest Drought Response Index (ForDRI): A New Combined Model to Monitor Forest Drought in the Eastern United States

Cited by 3 publications

References 45 publications

A new generation of sensors and monitoring tools to support climate-smart forestry practices

A new generation of sensors and monitoring tools to support climate-smart forestry practices

Impact of Drought on Forest Cover Change in Yabelo Forest in Semi-arid Region of Ethiopia

Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics

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