Sentinel-2 Analysis of Spruce Crown Transparency Levels and Their Environmental Drivers After Summer Drought in the Northern Eifel (Germany)

Montzka, Carsten; Tewes, Andreas; Vereecken, Harry; Bayat, Bagher; Mengen, David

doi:10.3389/ffgc.2021.667151

Cited by 16 publications

(16 citation statements)

References 65 publications

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“…The stands are located between 390 and 525 m a.s.l., representing a shallow elevation gradient. This area was severely affected by the European heatwave in 2018, resulting in trees affected by extremely dry conditions and subsequent bark beetle infestations (Montzka et al 2021;Obladen et al 2021;Spiecker & Kahle 2023).…”

Section: Study Site Plant Materials and Phenotypic Characterizationmentioning

confidence: 99%

Circadian rhythm and redox homeostasis candidate genes showed association with shallow elevation in Norway spruce

Caré,

Chano,

Erley

et al. 2024

Plant Biol J

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The analysis of genetic variation underlying local adaptation in natural populations, together with the response to different external stimuli, is currently a hot topic in forest sciences, with the aim of identifying genetic markers controlling key phenotypic traits of interest for their inclusion in restoration and breeding programs. In Europe, one of the main tree species is Norway spruce (Picea abies (L.) H.Karst.). Using the MassARRAY® platform, 568 trees from North Rhine‐Westphalia (Germany) were genotyped with 94 single nucleotide polymorphisms (SNPs) related to circadian and growth rhythms, and to stress response. The association analysis of the selected markers with health status and elevation was performed using three different methods, and those identified by at least two of these were considered as high confidence associated SNPs. While just five markers showed a weak association with health condition, 32 SNPs were correlated with elevation, six of which were considered as high confidence associated SNPs, as indicated by at least two different association methods. Among these genes, thioredoxin and pseudo response regulator 1 (PRR1) are involved in redox homeostasis and ROS detoxification, APETALA2‐like 3 (AP2L3), a transcription factor, is involved in seasonal apical growth, and a RPS2‐like is a disease resistance gene. The function of some of these genes in controlling light‐dependent reactions and metabolic processes suggests signatures of adaptation to local photoperiod and the synchronization of the circadian rhythm. This work provides new insights into the genetic basis of local adaptation over a shallow elevation gradient in Norway spruce.

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Section: Study Site Plant Materials and Phenotypic Characterizationmentioning

confidence: 99%

Circadian rhythm and redox homeostasis candidate genes showed association with shallow elevation in Norway spruce

Caré,

Chano,

Erley

et al. 2024

Plant Biol J

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“…Large parts of the slopes and the upper parts of the Urft catchment are covered by broad-leaved and coniferous forests (Figure 3, Table S1) (Corine Landcover, 2018). The coniferous forest mainly consists of spruce which was introduced in the area in the 19th century (Montzka et al, 2021). Less inclined areas are used as pastures and for agriculture.…”

Section: Study Areamentioning

confidence: 99%

115 years of sediment deposition in a reservoir in Central Europe: Topographic change detection

Stauch,

Dörwald,

Esch

et al. 2023

Earth Surf Processes Landf

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Reservoirs have become an important component in the worldwide river sediment flux. Reservoirs prevent downstream sediment transport and have become a major sediment sink. In this study, sediment deposition during the last 115 years in the Urft Reservoir in western Germany is reconstructed. The Urft Reservoir is the oldest reservoir in the Eifel Mountains and was almost completely drained in 2020. This enabled a detailed mapping of the lake bottom using an unmanned aerial system and the computation of a high‐resolution digital surface model. Topographic maps with a nominal resolution of 1:1000 from the time prior to the construction of the dam (around 1900) were used to construct a pre‐reservoir elevation model. A digital elevation model of difference (DoD) was calculated from these two datasets for the reservoir floor (0.72 km2). Based on the DoD, a net sediment accumulation of 1.16 × 106 m3 was calculated alongside a propagated volume error of 6.91 × 105 m3, resulting in a mean accumulation of 1.54 m. Conservative vertical error propagation results in an average level of detection (LoD) of 1.8 m. In contrast, the comparison of the DoD with 47 cores in the upper part of the reservoir showed a mean difference of −0.11 m, indicating a high, independently assessed accuracy of the DoD. Three depositional hotspots were identified in the reservoir. One is close to the Urft dam where very fine sediments are draped across the pre‐reservoir topography. Two areas are related to reservoir management. Sediment deposition in the Urft Reservoir has been comparably low in comparison to other regions globally, resulting in a 3.25% ± 1.93% loss of reservoir volume between 1905 and 2020. To analyse the effect of strong flooding events, a subset of the reservoir was analysed after an extreme event in July 2021, but accumulation did almost entirely not exceed the LoD.

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“…Multiple large-scale studies demonstrated the accurate assessment of forest disturbance and recovery [23,24]. Recent studies integrating optical imagery confirm drought-induced declines in forest health [25,26]. In particular, the analysis of products combining different remote sensing sensors at high spatial and temporal scale (e.g., Sentinel-1, Sentinel-2, Landsat) have gained in importance and popularity in institutional monitoring systems [12,23,27,28].…”

Section: Introductionmentioning

confidence: 99%

Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data

et al. 2023

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Monitoring forest conditions is an essential task in the context of global climate change to preserve biodiversity, protect carbon sinks and foster future forest resilience. Severe impacts of heatwaves and droughts triggering cascading effects such as insect infestation are challenging the semi-natural forests in Germany. As a consequence of repeated drought years since 2018, large-scale canopy cover loss has occurred calling for an improved disturbance monitoring and assessment of forest structure conditions. The present study demonstrates the potential of complementary remote sensing sensors to generate wall-to-wall products of forest structure for Germany. The combination of high spatial and temporal resolution imagery from Sentinel-1 (Synthetic Aperture Radar, SAR) and Sentinel-2 (multispectral) with novel samples on forest structure from the Global Ecosystem Dynamics Investigation (GEDI, LiDAR, Light detection and ranging) enables the analysis of forest structure dynamics. Modeling the three-dimensional structure of forests from GEDI samples in machine learning models reveals the recent changes in German forests due to disturbances (e.g., canopy cover degradation, salvage logging). This first consistent data set on forest structure for Germany from 2017 to 2022 provides information of forest canopy height, forest canopy cover and forest biomass and allows estimating recent forest conditions at 10 m spatial resolution. The wall-to-wall maps of the forest structure support a better understanding of post-disturbance forest structure and forest resilience.

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Sentinel-2 Analysis of Spruce Crown Transparency Levels and Their Environmental Drivers After Summer Drought in the Northern Eifel (Germany)

Cited by 16 publications

References 65 publications

Circadian rhythm and redox homeostasis candidate genes showed association with shallow elevation in Norway spruce

Circadian rhythm and redox homeostasis candidate genes showed association with shallow elevation in Norway spruce

115 years of sediment deposition in a reservoir in Central Europe: Topographic change detection

Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data

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