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Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

Dataset used to analyize role of climate variability

Sensitivity of the global agricultural sector to changes in climate policy - EU countries compared to the rest of the world

The files contain data from the FAOSTAT database used in the article: DOI:10.2478/oszn-2023-0012 File content: Agricultural emissions data for the period 1961-2020 Population data for 1950-2020 Production value from agriculture for the period 1961-2020 Agricultural area for the period 1961-2020 The layout of the tables and the description of the columns is the same as the FAOSTAT database methodology

Dataset for the submitted manuscript titled 'Response of Southern Ocean Resource Stress in a Changing Climate'

Netcdf output files of Primary Production, carbon export, Fe and Mn limitations, and deficiencies from PISCES-QUOTA model with Mn limitation (described in Anugerahanti and Tagliabue, 2023) forced by historical IPSL CM5A climate model simulation (1850-2005) and RCP8.5 high emission IPSL CM5A simulation (2005-2100) on the ORCA2 grid, as described and discussed in Anugerahanti and Tagliabue, in the manuscript submitted for Geophysical Research Letters. Due to the large size of the files, this has been collated to only contain surface/ upper 100m south of 40S.

opencc-zeroApr 2024View details →

dryad40/100

Climate change may alter the signal of plant facilitation in Mediterranean drylands

Facilitation is an ecological interaction that has allowed plant lineages to survive past climate aridification. This same interaction can be expected to buffer the effects of current climate change, which is tending to become more arid in the Mediterranean basin. However, facilitation may wane when stress conditions are extreme. Here we argue that the erosion of the facilitation signal between Quercus ilex and its nurses detected by García-Fayos et al. (2020) along 50 years in the eastern Iberian Peninsula may have been due to the reversion of facilitation to competition imposed by an increasingly arid climate. To support this speculation, we reconstructed the climatic niche of Q. ilex and its nurses as well as the local climate change occurring in the populations studied. We found that the decreasing trend in precipitation is pushing Q. ilex out of its climatic optimum in the stressful (semi-arid) but not in the mild (sub-humid) habitats. These results suggest that facilitation will be unable to mitigate the effects of climate change, especially those related to aridification. However, other scenarios linking climatic change with herbivory and rural abandonment should be considered to fully understand the past, present and future of facilitation interactions. Reconstructing past interactions can serve as an early warning signal about the future of populations in the face of climate change.

FIGURE 1 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 1. Geographic sketch showing the location of the plant-bearing sites. For locality numbers see Table 1.

FIGURE 6 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 6. Representation of modern European vegetation formations for the test set of fossil assemblages as delivered by Drudges 1 and 2. Formation H - Hygrophilous thermophytic mixed deciduous broadleaved forests; Formation G - Thermophilous mixed deciduous broadleaved forests; Formation F - Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation D - Mesophytic and hygromesophytic coniferous and mixed broadleaved-coniferous forests; Formation C - Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation. More detailed information on subdivisions and units is available in Appendix 9.

FIGURE 4 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 4. Representation of East Asian and European vegetation types and formations as delivered by Drudges 1 and Drudge 2 for the IPR Similarity, Taxonomic Similarity (TS), and Results Mix. See also Appendix 8.

FIGURE 8 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 8. Mean annual temperature (MAT), warm-month mean temperature (WMMT), and cold-month mean temperature (CMMT) based on CLAMP and the Coexistence Approach (CA) for the fossil plant record (sources are Kvaček et al., 2011; Teodoridis and Kvaček, 2015; Teodoridis et al., 2009, 2012, 2015, 2017). black columns: minimum CA. light grey columns: maximum CA, narrow, dark grey columns: CLAMP result. For more comprehensive climate data see Appendix 10.

FIGURE 9 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 9. Climate parameters of the modern European vegetation Formations F, G, and H based on Bohn et al. (2004) and Traiser and Mosbrugger (2004) represented as columns spanning the minimum and maximum of the respective data. Vegetation of Formation F tends to lower temperatures (note, however, that climate data for formations F.3 – F.1 are more complex). Vegetation of Formation G tends to lower MAP. Asterisks indicate single data points (no climate interval was available). The data are listed in Appendix 11. Abbreviations: MAT = mean annual temperature; WMMT = warm-month mean temperature; CMMT = cold-month mean temperature; MAP = mean annual precipitation.

opencc-by-4.0Apr 2024View details →

Data: Managing European Alpine forests with close-to-nature forestry to improve climate change mitigation and multifunctionality

The repository contains the data supporting the findings of the study: Managing European Alpine forests with close-to-nature forestry to improve climate change mitigation and multifunctionality Abstract: Close-to-nature forestry (CNF) has a long tradition in European Alpine forest management, playing a crucial role in ensuring the continuous provision of biodiversity and forest ecosystem services, including protection against natural hazards. However, climate change is causing huge uncertainties about the future applicability of CNF in the Alpine region. The question arises as to whether current CNF practices are still suitable for adapting forests to climate change impacts while also meeting the increasing societal demands regarding Alpine forests, including their potential contribution to climate change mitigation. To answer this question, we simulated forest development using the ForClim forest model at two Alpine study sites, together representing a large biogeographic gradient from high-elevation inner Alpine forests (Switzerland) to lower-elevation south-eastern Alpine forests (Slovenia). The simulations considered three climate scenarios (historical climate, SSP2‑4.5 and SSP5-8.5) and six alternative management strategies, including both current CNF management practices and climate-adapted versions. Using a multi-criteria decision analysis framework, we assessed the joint impacts of climate and management on biodiversity and key ecosystem services of the investigated regions, including carbon sequestration (CS) inside and outside the forest ecosystem boundary.  The joint effects of climate change and CNF varied, both among and within the study sites along the biogeographical gradient. While CS was more resistant to climate change under current CNF at the south-eastern Alpine site, it was more sensitive at the inner Alpine site, where CS potentials decreased at lower elevations. This adverse effect could be partly mitigated by fostering the use of climate-adapted tree species. However, current CNF and adaptations of it did not meet multiple management objectives equally well: while protection from gravitation hazards and timber production also benefited from this silvicultural practice, biodiversity benefited from CNF variants with low-intensity or no management.  In conclusion, CNF has a high potential to continue fulfilling its crucial role in European Alpine forests. A differentiated approach will be needed in the future, however, to identify forest stands where adaptive measures are required, especially at sites particularly vulnerable to climate change. In combination with less intensively managed or unmanaged areas, CNF provides a management portfolio that will help European Alpine forests to meet the demands of future society. Data: There is one folder for each case study, including:  <ul> <li>simulated biodiverstiy and ecosystem service indicators</li> <li>forest stand metadata</li> <li>normlized utility values for indicators</li> <li>partial utility values for biodiversity and ecosystem service groups</li> </ul> This study was conducted as part of the ONEforest project, which received funding from the European Union's Horizon 2020 research and innovation programme under the grant agreement Nº 101000406.

opencc-by-4.0Apr 2024View details →

Impacts of Quaternary climatic changes on the diversification of riverine cichlids in the lower Congo River

Climatic and geomorphological changes during the Quaternary period impacted global patterns of speciation and diversification across a wide range of taxa, but few studies have examined these effects on African riverine fishes. The lower Congo River is an excellent natural laboratory for understanding complex speciation and population diversification processes as it is hydrologically extremely dynamic and recognized as a continental hotspot of diversity harboring many narrowly endemic species. A previous study using genome-wide SNP data highlighted the importance of dynamic hydrological regimes to the diversification and speciation in lower Congo River cichlids. However, historical climate and hydrological changes (e.g., reduced river discharge during extended dry periods) have likely also influenced ichthyofaunal diversification processes in this system. The lower Congo River offers a unique opportunity to study climate-driven changes in river discharge, given the massive volume of water from the entire Congo basin flowing through this short stretch of the river. Here, we, for the first time, investigate the impacts of paleoclimatic factors on ichthyofaunal diversification in this system by inferring divergence times and modeling patterns of gene flow in four endemic lamprologine cichlids, including the blind cichlid, Lamprologus lethops.

FIGURE 3 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 3. Modern vegetation types/formations delivered as proxies by Drudges 1 and 2 for the test set of fossil assemblages. Shown are the five best fitted results for the Taxonomic Similarity (TS) and the overall scores (synthesis of all similarity approaches), i.e., 25 proxies for every plant assemblage. Pastel colours represent East Asian vegetation types, bright colours European vegetation formations. For more detailed information see Appendix 4 which provides interactive colour signature (moving the cursor over the columns provides the designation of the proxies and their relevance for every fossil assemblage).

FIGURE 2 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 2. Modern vegetation types/formations delivered as proxies by Drudges 1 and 2 for the test set of fossil assemblages. Shown are the five best fitted results for the IPR Similarities based on Drudge 1 and Drudge 2 and for the Results Mix based on Drudge 1 and Drudge 2. Pastel colours represent East Asian vegetation types, bright colours European vegetation formations. For more detailed information see Appendix 4 which provides interactive colour signature (moving the cursor over the columns provides the designation of the proxies and their relevance for every fossil assemblage).

FIGURE 7 in Modern vegetation proxies reflect Palaeogene and Neogene vegetation evolution and climate change in Europe, Turkey, and Armenia

FIGURE 7 (previous page). Representation of modern European vegetation formations for the test set of fossil assemblages as delivered by Drudges 1 and 2 in more detail (see also Appendix 9). Formation H: H001, Colchic lowland to submontane mixed oak forests, in black; H002, Hyrcanian lowland-colline mixed broadleaved forests, in dark grey; H003, Hyrcanian colline to montane oak forests, in light grey. Formation G: G.1 - Subcontinental thermophilous (mixed) pedunculate oak and sessile oak forests, in black; G.2 - Sub-Mediterranean-subcontinental thermophilous bitter oak and Balkan oak and mixed forests, in dark grey; G.3 - Sub-Mediterranean and meso-supra-Mediterranean downy oak and mixed forests, in light grey; G.4 - Iberian supra- and meso-Mediterranean oak forests, in white. Formation F: F.1 - Species-poor acidophilous oak and mixed oak forests, in black; F.2 - Mixed oak-ash forests, in dark grey; F.3 - Mixed oak-hornbeam forests, in light grey; F.4 Lime-pedunculate oak forests, in white; F.5 - Beech and mixed beech forests, hatched lower left to upper right; F.6 - Oriental beech forests and hornbeam-oriental beech forests, hatched upper left to lower right; F.7 - Caucasian mixed hornbeam-oak forests, hatched vertically. Formation F, F.5 - Beech and mixed beech forests: F.5.1.1 - Species-poor oligotrophic to mesotrophic beech and mixed beech forests, lowland(-colline) types, in black; F.5.1.2 - Species-poor oligotrophic to mesotrophic beech and mixed beech forests, colline-submontane types, in dark grey; F.5.1.3 - Species-poor oligotrophic to mesotrophic beech and mixed beech forests, montane-altimontane types, in light grey; F.5.2.1 - Species-rich eutrophic and eu-mesotrophic beech and mixed beech forests, colline-submontane types, in white; F.5.2.2 - Species-rich eutrophic and eu-mesotrophic beech and mixed beech forests, colline-submontane types, hatched lower left to upper right; F.5.2.3 and 4 - Species-rich eutrophic and eu-mesotrophic beech and mixed beech forests, montane-altimontane types, hatched upper left to lower right. Formation D: D.1 - Western boreal spruce forests, in black; D.2 - Eastern boreal pine-spruce and fir-spruce forests, in dark grey; D.3 - Hemiboreal spruce and fir-spruce forests with broad-leaved trees, in light grey; D.4 - Montane to altimontane, partly submontane fir and spruce forests in the nemoral zone, in white; D.5 - Boreal and hemiboreal pine forests, hatched lower left to upper right; D.6 - Montane to altimontane (subalpine) pine forests in the nemoral zone; hatched upper left to lower right.

opencc-by-4.0Nov 2024View details →

Response of Vegetation Canopy Growth to Climate Change in Northeast China

Our study uniquely addresses gaps in existing research by investigating how vegetation canopy changes during various growth phases—development (April-June), maturation (July-August), and senescence (September-October)—and how these changes respond to preseason climatic factors. We highlight significant findings, such as the early advancement of the canopy maturation phase and the delayed senescence, particularly in forested areas. Moreover, we demonstrate that preseason air temperature exerts a considerable influence on canopy growth, with a transition from positive to negative correlations across different phases and vegetation types.The results contribute to understanding vegetation dynamics under climate change and provide actionable insights for sustainable agricultural, forestry, and animal husbandry management.

opencc-by-4.0Dec 2024View details →

Literature review of the enablers and barriers to stakeholder and citizen engagement in climate change adaptation process (as part of Adaptation AGORA project)

This dataset is the result of collaborative work for Deliverable 4.1 (WP4; T4.1) of the Adaptation AGORA project. This database was used to conduct a literature review of the enablers and barriers to stakeholder and citizen engagement in climate change adaptation process. It contains 123 papers retrived from Web of Science Databse in June 2023. We used a keyword search to identify and select articles that fell within the scope of our research, with each article containing at least one keyword related to climate change adaptation solutions, climate change, co-production, citizen and stakeholder involvement and factors (enablers and barriers).  We divided the coding framework into four main sections: <ul> <li> Section 1 collected basic information about the paper (i.e., date, journal, authors, type of study and methods for data collection). </li> <li> Section 2 sought to better understand the adaptation initiatives treated in the paper. Here, we analysed 5 variables (the adaptation solutions type, sectors, benefits, scale, and location).  </li> <li> Section 3 collected characteristics of the climate change adaptation co-production process, including the definition of co-production, the type of the co-production process, its outputs, and the methods used to engage stakeholders. </li> <li> Section 4 described the factors that enable or hinder the co-production process and their influence on different aspects of the process. After naming and defining each driver, we recorded the main type of factor, its impact, origin, and spatial and temporal scale of influence; the stakeholders who were responsible for and influenced by the factor, and the impacts on the various steps and outcomes of the co-production process. </li> </ul>

opencc-by-4.0Nov 2024View details →

CLIMATE CHANGE EFFECTS ON A SUBTROPICAL COASTAL SHALLOW LAKE FROM HEATWAVE INDEXES

This zipped folder contains the files used to generate the results of this article, submitted to the journal Earth Systems and Environment.

opencc-by-4.0Apr 2023View details →

Global surface water quality datasets under uncertain climate and socio-economic change, derived from the dynamical surface water quality model (DynQual) at 5 arcmin spatial resolution

<pre>Global ~10km (5 arcmin) surface water quality data from the dynamical surface water quality model (DynQual) from 2005-2100, with annual and monthly temporal resolution. Simulations are made under three combined climate and socio-economic scenarios (SSP1-RCP2.6; SSP3-RCP7.0 and SSP5-RCP8.5) and using five general circulation model (GFDL-ESM4; UKESM1-0-LL; MPI-ESM1-2-hr; IPSL-CM6A-LR and MRI-ESM2-0), following the ISIMIP3b protocol (<a href="https://protocol.isimip.org/#/ISIMIP3b">https://protocol.isimip.org/#/ISIMIP3b</a>). Output data are provided at annual and monthly temporal resolution over WorldClim time periods (2005-2020; 2021-2040; 2041-2060; 2061-2080; 2081-2100). Output data includes: - Discharge (m3 s-1) - Water temperature (K) - Total dissolved solids (TDS) load (g s-1) - Biological oxygen demand (BOD) load (g s-1) - Fecal coliform (FC) load (million cfu s-1) - Salinity; as indicated by TDS concentrations (mg l-1) - Organic pollution; as indicated by BOD concentrations (mg l-1) - Pathogen/bacterial pollution; as indicated by FC concentrations (cfu 100ml-1) Note. A minimum discharge threshold of 0.1 m3 s-1 was used when computing TDS, BOD and FC concentrations, as uncertainties in absolute values of water availabilities have large impacts on resulting in-stream concentrations. Concentrations in these gridcells are assigned as NA. Full time series of these variables at 30 arcmin (0.5 degree) can be found at: <a href="https://zenodo.org/records/14677534">https://zenodo.org/records/14677534</a>.</pre>

opencc-by-4.0Jan 2021View details →

Data associated with the publication "Multi-decadal increase of forest burned area in Australia is linked to climate change"

Data from various sources related to fires in Australian forests, associated with the publication "Multi-decadal increase of forest burned area in Australia is linked to climate change"

A standardised climate change hazard vocabulary for heritage

This dataset (.xlsx) is a vocabulary of climate change hazards for heritage. Hazards are the potential occurrences of natural or physical events that may cause damage or loss. Previously there had been no definitive list of climate hazards for heritage that were directly connected to changing climatic processes. This project addresses this gap by linking the created hazards to the Climatic Impact-Drivers (CIDs) produced by the Intergovernmental Panel on Climate Change (IPCC). The vocabulary consists of 52 primary and key related hazards for heritage. It is international in its remit. The list will be published as a vocabulary on <a href="https://www.heritage-standards.org.uk/fish-vocabularies/" target="_blank" rel="noopener">the Forum on Information Standards in Heritage (FISH)</a> where it can be accessed in multiple formats <a href="https://heritagedata.org/live/schemes/38076.html">including linked data</a>. This .xlsx format places the hazards in relationship to each other and in their CID context. Candidate terms can be submitted to the research group Heritage Environmental Risk and Data Analytics <a href="mailto:herada@ucl.ac.uk" target="_blank" rel="noopener noreferrer">herada@ucl.ac.uk</a> (terms submitted to <a href="mailto:Terminologies@HistoricEngland.org.uk">Terminologies@HistoricEngland.org.uk</a> will be directed to the research group for approval). An accompanying <a href="https://historicengland.org.uk/research/results/reports/13-2024?search=13%2F2024&searchType=research+report">Historic England Research Report</a> provides more information, including the methodology of the project (available in both English and Welsh). The authors are interested in hearing from users of the vocabulary, specifically those that link the hazards to observed impacts of climate change on parts of the historic environment. This dataset was produced as part of a funded 6-month project between Historic England and the UCL Institute for Sustainable Heritage on developing a standardised vocabulary of climate change hazards for the historic environment. The Welsh version of the dataset was translated in 2025 by Lingo Soar, in collaboration with Fforest Fawr UNESCO Geopark, and as part of the UK National Commission for UNESCO's Climate Change and UNESCO Heritage project.