ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    facet.materialart.
    Unknown
    Cryptogamic organisms are a substantial source and sink for volatile organic compounds in the Amazon region (2021)
    Nature Publishing Group UK
    Details
    Publication Date: 2023-12-16
    Description: Cryptogamic organisms such as bryophytes and lichens cover most surfaces within tropical forests, yet their impact on the emission of biogenic volatile organic compounds is unknown. These compounds can strongly influence atmospheric oxidant levels as well as secondary organic aerosol concentrations, and forest canopy leaves have been considered the dominant source of these emissions. Here we present cuvette flux measurements, made in the Amazon rainforest between 2016–2018, and show that common bryophytes emit large quantities of highly reactive sesquiterpenoids and that widespread lichens strongly uptake atmospheric oxidation products. A spatial upscaling approach revealed that cryptogamic organisms emit sesquiterpenoids in quantities comparable to current canopy attributed estimates, and take up atmospheric oxidation products at rates comparable to hydroxyl radical chemistry. We conclude that cryptogamic organisms play an important and hitherto overlooked role in atmospheric chemistry above and within tropical rainforests.
    Description: Cryptogamic organisms such as bryophytes and lichens contribute substantially to emissions of secondary organic aerosol precursors as well as to the uptake of atmospheric oxidation products over the Amazon rainforest, suggest measurements at a remote Amazon rainforest site.
    Description: Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) https://doi.org/10.13039/501100002347
    Description: https://doi.org/10.17871/atto.232.15.860
    Keywords: ddc:577.3 ; Atmospheric chemistry ; Biogeochemistry ; Plant sciences
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 2
    facet.materialart.
    Unknown
    Vegetation Greenness in Northeastern Brazil and Its Relation to ENSO Warm Events (2018)
    Details
    Publication Date: 2021-03-29
    Description: The spatio-temporal variability of trends in vegetation greenness in dryland areas is a well-documented phenomenon in remote sensing studies at global to regional scales. The underlying causes differ, however, and are often not well understood. Here, we analyzed the trends in vegetation greenness for a semi-arid area in northeastern Brazil (NEB) and examined the relationships between those dynamics and climate anomalies, namely the El Nino Southern Oscillation (ENSO) for the period 1982 to 2010, based on annual Normalized Difference Vegetation Index (NDVI) values from the latest version of the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI dataset (NDVI3g) dataset. Against the ample assumption of ecological and socio-economic research, the results of our inter-annual trend analysis of NDVI and precipitation indicate large areas of significant greening in the observation period. The spatial extent and strength of greening is a function of the prevalent land-cover type or biome in the study area. The regression analysis of ENSO indicators and NDVI anomalies reveals a close relation of ENSO warm events and periods of reduced vegetation greenness, with a temporal lag of 12 months. The spatial patterns of this relation vary in space and time. Thus, not every ENSO warm event is reflected in negative NDVI anomalies. Xeric shrublands (Caatinga) are more sensitive to ENSO teleconnections than other biomes in the study area.
    Description: Open-Access-Publikationsfonds 2014
    Keywords: NDVI3g; GIMMS; AVHRR; El Nino; inter-annual trends; teleconnections ; 551
    Language: English
    Type: article , publishedVersion
    Format: 18
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 3
    facet.materialart.
    Unknown
    The Structure of Climate Variability Across Scales (2021)
    Details
    Publication Date: 2021-10-07
    Description: Abstract One of the most intriguing facets of the climate system is that it exhibits variability across all temporal and spatial scales; pronounced examples are temperature and precipitation. The structure of this variability, however, is not arbitrary. Over certain spatial and temporal ranges, it can be described by scaling relationships in the form of power laws in probability density distributions and autocorrelation functions. These scaling relationships can be quantified by scaling exponents which measure how the variability changes across scales and how the intensity changes with frequency of occurrence. Scaling determines the relative magnitudes and persistence of natural climate fluctuations. Here, we review various scaling mechanisms and their relevance for the climate system. We show observational evidence of scaling and discuss the application of scaling properties and methods in trend detection, climate sensitivity analyses, and climate prediction.
    Keywords: 551.6 ; scaling ; climate variability ; memory ; scaling mechanisms ; paleoclimate ; power law
    Language: English
    Type: map
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 4
    facet.materialart.
    Unknown
    Climate-induced hysteresis of the tropical forest in a fire-enabled Earth system model (2021)
    In:  European Physical Journal - Special Topics
    Details
    Publication Date: 2022-03-21
    Description: Tropical rainforests are recognized as one of the terrestrialtipping elements which could have profound impacts on the global cli-mate, once their vegetation has transitioned into savanna or grasslandstates. While several studies investigated the savannization of, e.g., theAmazon rainforest, few studies considered the influence of fire. Fire isexpected to potentially shift the savanna-forest boundary and henceimpact the dynamical equilibrium between these two possible vegeta-tion states under changing climate. To investigate the climate-inducedhysteresis in pan-tropical forests and the impact of fire under future cli-mate conditions, we employed the Earth system model CM2Mc, whichis biophysically coupled to the fire-enabled state-of-the-art dynamicglobal vegetation model LPJmL. We conducted several simulation ex-periments where atmospheric CO2concentrations increased (impactphase) and decreased from the new state (recovery phase), each withand without enabling wildfires. We find a hysteresis of the biomassand vegetation cover in tropical forest systems, with a strong regionalheterogeneity. After biomass loss along increasing atmospheric CO2concentrations and accompanied mean surface temperature increase ofabout 4°C (impact phase), the system does not recover completely intoits original state on its return path, even though atmospheric CO2concentrations return to their original state. While not detecting large-scale tipping points, our results show a climate-induced hysteresis intropical forest and lagged responses in forest recovery after the climatehas returned to its original state. Wildfires slightly widen the climate-induced hysteresis in tropical forests and lead to a lagged response inforest recovery by ca. 30 years.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 5
    facet.materialart.
    Unknown
    Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest (2022)
    In:  Proceedings of the National Academy of Sciences of the United States of America (PNAS)
    Details
    Publication Date: 2023-12-15
    Description: Tipping elements are nonlinear subsystems of the Earth system that have the potential to abruptly shift to another state if environmental change occurs close to a critical threshold with large consequences for human societies and ecosystems. Among these tipping elements may be the Amazon rainforest, which has been undergoing intensive anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations from climatological rainfall regimes may cause local forest collapse that cascades through the coupled forest–climate system. We develop a conceptual dynamic network model to isolate and uncover the role of atmospheric moisture recycling in such tipping cascades. We account for heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, a future climate characterized by permanent drought conditions could trigger a transition to an open canopy state particularly in the southern Amazon. The loss of atmospheric moisture recycling contributes to one-third of the tipping events. Thus, by exceeding local thresholds in forest adaptive capacity, local climate change impacts may propagate to other regions of the Amazon basin, causing a risk of forest shifts even in regions where critical thresholds have not been crossed locally.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 6
    facet.materialart.
    Unknown
    The Dystopian Impulse of Contemporary Cli-Fi: Lessons and Questions from a Joint Workshop of the IASS and the JFKI (FU Berlin) (2016)
    In:  IASS Working Paper
    Details
    Publication Date: 2023-07-18
    Language: English
    Type: info:eu-repo/semantics/workingPaper
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION RIFS
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...