Forest structure following natural disturbances and early succession provides habitat for two avian flagship species, capercaillie (Tetrao urogallus) and hazel grouse (Tetrastes bonasia)

Kortmann, Mareike; Heurich, Marco; Latifi, Hooman; Rösner, Sascha; Seidl, Rupert; Müller, Jörg; Thorn, Simon

doi:10.1016/j.biocon.2018.07.014

Cited by 31 publications

(31 citation statements)

References 67 publications

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“…(5) The vertical heterogeneity of the vegetation (Kortmann et al. ) was quantified by the Simpson index for canopy height. This index was calculated among the quantile height values (10, 25, 50, 75, 90% quantile strata) using the function diversity of the R package vegan (Oksanen et al.…”

Section: Methodsmentioning

confidence: 99%

“…) or height skewness of the returns located between 1.5 m and 5 m (Kortmann et al. ) have been used to describe vegetation. However, these metrics may be difficult to interpret or communicate because they are not used as field metrics by managers (such as the percentage of vegetation cover by layer and the number of trees).…”

Section: Introductionmentioning

confidence: 99%

“…; Kortmann et al. ), with a view toward management advice for species conservation. To date, the efficiency of these two types of metrics (PC area‐based and OO) in extracting pertinent structural information on forest structure for modeling forest species distribution has not been evaluated.…”

Section: Introductionmentioning

confidence: 99%

“…PC area-based metrics summarize the characteristics of the point cloud within a given region of interest (typically a square pixel). Variables such as the standard deviation of the 10 th percentile (Zellweger et al 2013), the proportion of echoes above 5 m (Melin et al 2016) or height skewness of the returns located between 1.5 m and 5 m (Kortmann et al 2018) have been used to describe vegetation. However, these metrics may be difficult to interpret or communicate because they are not used as field metrics by managers (such as the percentage of vegetation cover by layer and the number of trees).…”

Section: Introductionmentioning

confidence: 99%

“…This type of approach has been widely used as a forest management tool by exploiting single tree detection methods (Othmani et al 2013;Munoz et al 2015). Several recent studies used OO metrics to produce easier interpretable variables such as gaps, percentage of deciduous trees and edge length (Rechsteiner et al 2017;Kortmann et al 2018), with a view toward management advice for species conservation. To date, the efficiency of these two types of metrics (PC area-based and OO) in extracting pertinent structural information on forest structure for modeling forest species distribution has not been evaluated.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the performance of object‐oriented LiDARpredictors for forest bird habitat suitability modeling

Glad

Reineking

Montadert

et al. 2019

Remote Sens Ecol Conserv

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Habitat suitability models (HSMs) are widely used to plan actions for species of conservation interest. Models that will be turned into conservation actions need predictors that are both ecologically pertinent and fit managers’ conceptual view of ecosystems. Remote sensing technologies such as light detection and ranging (LiDAR) can describe landscapes at high resolution over large spatial areas and have already given promising results for modeling forest species distributions. The point‐cloud (PC) area‐based LiDAR variables are often used as environmental variables in HSMs and have more recently been complemented by object‐oriented (OO) metrics. However, the efficiency of each type of variable to capture structural information on forest bird habitat has not yet been compared. We tested two hypotheses: (1) the use of OO variables in HSMs will give similar performance as PC area‐based models; and (2) OO variables will improve model robustness to LiDAR datasets acquired at different times for the same area. Using the case of a locally endangered forest bird, the capercaillie (Tetrao urogallus), model performance and predictions were compared between the two variable types. Models using OO variables showed slightly lower discriminatory performance than PC area‐based models (average ΔAUC = −0.032 and −0.01 for females and males, respectively). OO‐based models were as robust (absolute difference in Spearman rank correlation of predictions ≤ 0.21) or more robust than PC area‐based models. In sum, LiDAR‐derived PC area‐based metrics and OO metrics showed similar performance for modeling the distribution of the capercaillie. We encourage the further exploration of OO metrics for creating reliable HSMs, and in particular testing whether they might help improve the scientist–stakeholder interface through better interpretability.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assessing the performance of object‐oriented LiDARpredictors for forest bird habitat suitability modeling

Glad

Reineking

Montadert

et al. 2019

Remote Sens Ecol Conserv

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A replicated study on the response of spider assemblages to regional and local processes

Müller

Brandl

Cadotte

et al. 2022

Ecological Monographs

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Understanding species richness variation among local communities is one of the central topics in ecology, but the complex interplay of regional processes, environmental filtering, and local processes hampers generalization on the importance of different processes. Here, we aim to unravel drivers of spider community assembly in temperate forests by analyzing two independent data sets covering gradients in elevation and forest succession. We test the following four hypotheses: (H1) spider assemblages within a region are limited by dispersal, (H2) local environment has a dominant influence on species composition and (H3) resources, and (H4) biotic interactions both affect species richness patterns. In a comprehensive approach, we studied species richness, abundance, taxonomic composition, and trait-phylogenetic dissimilarity of assemblages. The decrease in taxonomic similarity with increasing spatial distance was very weak, failing to support H1. Functional clustering of species in general and with canopy openness strongly supported H2. Moreover, this hypothesis was supported by a positive correlation between environmental and taxonomic similarity and by an increase in abundance with canopy openness. Resource determination of species richness (H3) could be confirmed only by the decrease of species richness with canopy cover. Finally, decreasing species richness with functional clustering indicating effects of biotic interactions (H4) could only be found in one analysis and only in one data set. In conclusion, our findings indicate that spider assemblages within a region are mainly determined by local environmental conditions, while resource availability, biotic interactions and dispersal play a minor role. Our approach shows that both the analysis of different aspects of species diversity and replication of community studies are necessary to identify the complex interplay of processes forming local assemblages.

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Spaceborne LiDAR for characterizing forest structure across scales in the European Alps

Mandl

Stritih

Seidl

et al. 2023

Remote Sens Ecol Conserv

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The launch of NASA's Global Ecosystem Dynamics Investigation (GEDI) mission in 2018 opens new opportunities to quantitatively describe forest ecosystems across large scales. While GEDI's height‐related metrics have already been extensively evaluated, the utility of GEDI for assessing the full spectrum of structural variability—particularly in topographically complex terrain—remains incompletely understood. Here, we quantified GEDI's potential to estimate forest structure in mountain landscapes at the plot and landscape level, with a focus on variables of high relevance in ecological applications. We compared five GEDI metrics including relative height percentiles, plant area index, cover and understory cover to airborne laser scanning (ALS) data in two contrasting mountain landscapes in the European Alps. At the plot level, we investigated the impact of leaf phenology and topography on GEDI's accuracy. At the landscape‐scale, we evaluated the ability of GEDIs sample‐based approach to characterize complex mountain landscapes by comparing it to wall‐to‐wall ALS estimates and evaluated the capacity of GEDI to quantify important indicators of ecosystem functions and services (i.e., avalanche protection, habitat provision, carbon storage). Our results revealed only weak to moderate agreement between GEDI and ALS at the plot level (R2 from 0.03 to 0.61), with GEDI uncertainties increasing with slope. At the landscape‐level, however, the agreement between GEDI and ALS was generally high, with R2 values ranging between 0.51 and 0.79. Both GEDI and ALS agreed in identifying areas of high avalanche protection, habitat provision, and carbon storage, highlighting the potential of GEDI for landscape‐scale analyses in the context of ecosystem dynamics and management.

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Forest structure following natural disturbances and early succession provides habitat for two avian flagship species, capercaillie (Tetrao urogallus) and hazel grouse (Tetrastes bonasia)

Cited by 31 publications

References 67 publications

Assessing the performance of object‐oriented LiDARpredictors for forest bird habitat suitability modeling

Assessing the performance of object‐oriented LiDARpredictors for forest bird habitat suitability modeling

A replicated study on the response of spider assemblages to regional and local processes

Spaceborne LiDAR for characterizing forest structure across scales in the European Alps

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