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  • 1
    Online Resource
    Online Resource
    MDPI AG ; 2020
    In:  Forests Vol. 11, No. 5 ( 2020-05-13), p. 546-
    In: Forests, MDPI AG, Vol. 11, No. 5 ( 2020-05-13), p. 546-
    Abstract: Drought episodes are predicted to increase their intensity and frequency globally, which will have a particular impact on forest vitality, productivity, and species distribution. However, the impact of tree species interaction on forest vulnerability to drought is not yet clear. This study aims to assess how deciduous saplings react to drought and whether tree species diversity can buffer the impact of drought stress on tree saplings. Based on field measurements of crown defoliation and species diversity, vulnerability, drought recovery, and species interaction were analyzed. Fieldwork was carried out in Central Eastern Germany in 2018 during the vegetation season and repeated in 2019. Ten random saplings were measured in each of the 218 plots (15 × 15 m) with 2051 saplings in total out of 41 tree species. We found that 65% of the saplings experienced defoliation during the drought of 2018, of which up to 13% showed complete defoliation. At the species level, Fagus sylvatica L. and Betula pendula Roth. saplings were less affected ( 〈 55%), whereas Carpinus betulus L., Sorbus aucuparia L., and Frangula alnus Mill. saplings were the most affected (≥85%). One year later, in 2019, C. betulus and S. aucuparia had a faster recovery rate than F. sylvatica, B. pendula, Quercus spp., and Crataegus spp. (p 〈 0.001). Furthermore, we showed that forest stands with high sapling species diversity had a reduced vitality under drought stress (p 〈 0.001), indicating a higher competition for resources. The study provides evidence that F. sylvatica saplings can withstand and survive to persistent drought. Species-specific responses to drought are essential to be considered for implementing adaptive forest management strategies to mitigate the impact of climate change.
    Type of Medium: Online Resource
    ISSN: 1999-4907
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2527081-3
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  • 2
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  Forest Ecology and Management Vol. 509 ( 2022-04), p. 120075-
    In: Forest Ecology and Management, Elsevier BV, Vol. 509 ( 2022-04), p. 120075-
    Type of Medium: Online Resource
    ISSN: 0378-1127
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2016648-5
    detail.hit.zdb_id: 751138-3
    SSG: 23
    SSG: 12
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  • 3
    In: Remote Sensing, MDPI AG, Vol. 15, No. 5 ( 2023-03-06), p. 1463-
    Abstract: Automatic identification and mapping of tree species is an essential task in forestry and conservation. However, applications that can geolocate individual trees and identify their species in heterogeneous forests on a large scale are lacking. Here, we assessed the potential of the Convolutional Neural Network algorithm, Faster R-CNN, which is an efficient end-to-end object detection approach, combined with open-source aerial RGB imagery for the identification and geolocation of tree species in the upper canopy layer of heterogeneous temperate forests. We studied four tree species, i.e., Norway spruce (Picea abies (L.) H. Karst.), silver fir (Abies alba Mill.), Scots pine (Pinus sylvestris L.), and European beech (Fagus sylvatica L.), growing in heterogeneous temperate forests. To fully explore the potential of the approach for tree species identification, we trained single-species and multi-species models. For the single-species models, the average detection accuracy (F1 score) was 0.76. Picea abies was detected with the highest accuracy, with an average F1 of 0.86, followed by A. alba (F1 = 0.84), F. sylvatica (F1 = 0.75), and Pinus sylvestris (F1 = 0.59). Detection accuracy increased in multi-species models for Pinus sylvestris (F1 = 0.92), while it remained the same or decreased slightly for the other species. Model performance was more influenced by site conditions, such as forest stand structure, and less by illumination. Moreover, the misidentification of tree species decreased as the number of species included in the models increased. In conclusion, the presented method can accurately map the location of four individual tree species in heterogeneous forests and may serve as a basis for future inventories and targeted management actions to support more resilient forests.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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  • 4
    Online Resource
    Online Resource
    Elsevier BV ; 2023
    In:  Forest Ecosystems ( 2023-9), p. 100140-
    In: Forest Ecosystems, Elsevier BV, ( 2023-9), p. 100140-
    Type of Medium: Online Resource
    ISSN: 2197-5620
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2760380-5
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  • 5
    In: Forest Ecosystems, Elsevier BV, Vol. 9 ( 2022), p. 100002-
    Type of Medium: Online Resource
    ISSN: 2197-5620
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2760380-5
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  • 6
    Online Resource
    Online Resource
    MDPI AG ; 2019
    In:  Forests Vol. 10, No. 4 ( 2019-04-11), p. 326-
    In: Forests, MDPI AG, Vol. 10, No. 4 ( 2019-04-11), p. 326-
    Abstract: Pinus cembra L. is a key species of high elevation forest ecosystems in Europe. However, in most mountain ranges, its importance has declined considerably. Remnant populations are often isolated and their dynamics and functioning are not well understood. Here, we apply novel approaches in pattern analysis to two P. cembra populations in the Carpathian Mountains in order to identify commonalities and divergences in their spatial structure and dynamics. Four study sites (1.2 ha each) were investigated within the treeline ecotone in two protected areas that differ in terms of protection status. Based on height and diameter, the individuals were classified into three size-classes: sapling, intermediate and adult trees. Spatial distribution and interactions between tree sizes were analyzed using point pattern analysis. The overall structure of all trees was aggregated at a small distance and regular at a greater distance in the population from the Natura 2000 site (p = 0.002), while in the National Park population it was a random pattern. However, the general patterns do not apply to tree size classes and the relationship among them. In the Natura 2000 site, there was no correlation, all the trees were mixed, regardless of their size. In the National Park, the sapling and intermediate were strongly clustered (p = 0.001), but the adult trees were spatially separated from all juveniles, forming patches at a lower elevation. In both areas, spatial patterns indicate the dynamics of the P. cembra population. Whereas in the National Park population, there is evidence of an upward shift, which cannot be confirmed in Natura 2000, where size classes are completely mixed and the dynamic does not translate into an expansion of the population area. The spatial differences between the two populations indicate that conservation strategies need to be developed more individually to support the regeneration of these isolated populations.
    Type of Medium: Online Resource
    ISSN: 1999-4907
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527081-3
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  • 7
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2023-07-04)
    Abstract: Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2553671-0
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  • 8
    In: Science of The Total Environment, Elsevier BV, Vol. 872 ( 2023-05), p. 162167-
    Type of Medium: Online Resource
    ISSN: 0048-9697
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1498726-0
    detail.hit.zdb_id: 121506-1
    SSG: 12
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  • 9
    In: Global Change Biology, Wiley, Vol. 26, No. 1 ( 2020-01), p. 119-188
    Abstract: Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
    Type of Medium: Online Resource
    ISSN: 1354-1013 , 1365-2486
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2020313-5
    SSG: 12
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  • 10
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2022
    In:  Scientific Reports Vol. 12, No. 1 ( 2022-02-03)
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-02-03)
    Abstract: Climate change impacts the structure, functioning, and distribution of species and ecosystems. It will shift ecosystem boundaries, potentially affecting vulnerable ecosystems, such as tropical Africa's high mountain ecosystems, i.e., afroalpine ecosystems, and their highly susceptible uniquely adapted species. However, ecosystems along these mountains are not expected to respond similarly to the change. The ericaceous woody vegetation, located between the low-elevation broadleaf forests and high-elevation afroalpine vegetation, are anticipated to be affected differently. We hypothesize that projected climate change will result in an upward expansion and increasing dominance of ericaceous vegetation, which will negatively impact the endemic rich afroalpine ecosystems of the extensive Sanetti plateau. Hence, we modeled the impact of future climate change on the distribution of ericaceous vegetation and discussed its effect on bordering ecosystems in the Bale Mountains. We applied four familiar correlative modeling approaches: bioclim, domain, generalized linear methods, and support vector machines. We used WorldClim’s bioclimatic variables as environmental predictors and two representative concentration pathways (RCPs) of the IPCC Fifth Assessment Report climate change scenarios, namely RCP4.5 and RCP8.5 for future climate projection. The results indicate increased ericaceous vegetation cover on the midaltitude of northwestern and northern parts of the massif, and the Sanetti plateau. We observed upward range expansion and increase of close ericaceous vegetation in midaltitudes, while receding from the lower range across the massif. Moreover, the current ericaceous vegetation range correlates to the temperature and precipitation trends, reaffirming the critical role of temperature and precipitation in determining species distributions along elevational gradients. The results indicate the high likelihood of considerable changes in this biodiversity hotspot in Eastern Africa.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2615211-3
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