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2,260 results for “Climatic change”
Multi-omics for Understanding Climate Change (MUCC) database v2.0.0
<p>This is the Multi-omics for Understanding Climate Change (MUCC database) version 2.0.0. This current version is based on amplicon and metagenomic sequencing of Old Woman Creek (OWC), Prairie Pothole Region(PPR7 and PPR8), Jean Lafitte National Historical Park and Preserve (JLA), AmeriFlux site US-LA2 (LA2), Stordalen Mire (STM-fen and STM-bog), AmeriFlux site-ID US-Twt (TWI), and Peatland Responses Under Changing Environments (SPRUCE) and wetland soils. Additionally, this includes metatranscriptome sequencing from OWC. In the future, this will be expanded to include more data from these sites and from additional wetlands.</p> <p>OWC, PPR, JLA and LA2 data are deposited in NCBI Bioproject PRJNA1007388</p> <p>Stordalen Mire MAGs are deposited in BioProject PRJNA386538</p> <p>AmeriFlux site-ID US-Twt are deposited in SRA SRP003022, SRA SRP010671, SRP010730, SRP010738, SRP010741, SRP010747, SRP010748, SRP010751, SRP010862, SRP010870, and SRP011309. </p> <p>SPRUCE data are deposited in PRJNA638786 and PRJNA638601</p> <p> </p> <p>Files and datasets included here: </p> <ol> <li><strong>16S.zip </strong>16S amplicon sequencing data and site metadata for 1,112 samples (fastq files)</li> <li><strong>MQ_HQ_MAGs.zip </strong>Database of 4745 Medium and High Quality MAGs (fasta files)</li> <li><strong>MUCC_v2.0.0_HQMQ_genes.faa.zip </strong>MAG amino acid gene sequences derived from DRAM gene calls (fasta file)</li> <li><strong>MUCC_v2.0.0_HQMQ_annotations.tsv </strong>MAG DRAM ANNOTATIONS</li> <li><strong><strong>owc_metat_table_methanoregula_genes.csv </strong></strong>Metatranscriptomic expression per genes in <em>Methanoregula</em> across 133 metatranscriptomes (csv table)</li> <li><strong>gtdbtk.ar53.decorated.tree </strong>newick file for GTDB de novo work flow <em>Methanoregula</em> MAG tree</li> <li><strong>Newick_gene_trees.zip </strong>Trees used in blast identification of methylotrophic gene homologs to curate MR for methylotrophy</li> <li><strong>fasta_reference_genes.zip </strong>FASTA reference files of genes used as BLAST query to mine Methanoregula MAGs for genes involved in detoxification of reactive oxygen species (ROS) and methanogenic metabolism of methylated compounds</li> <li><strong>protpipeliner.py </strong>Python script is a modification of protpipeliner.rb for building RAXML trees</li> <li><strong>classification_w_outgroup.txt </strong>Taxonomy and corresponding MAG ID for <em>Methanregula </em>used in the tree (Figure 5B)</li> <li><strong>Methanoregula_metabolism_summary.xlsx </strong>The DRAM annotations of the <em>Methanoregula </em>MAGs from MUCC, GTDB, and JGI</li> <li><strong>Methanoregula_physiology.txt </strong>Curation of <em>Methanoregula</em> MAGS for physliogical functions of interest</li> <li><strong>Methanoregula_MAGs_list.txt </strong>Comprehensive list of all <em>Methanoregula </em>MAGs used and what database they were sourced from</li> <li><strong>Methanoregula_MAGs_DB.zip </strong>Database of 108 <em>Methanregula</em> MAGs</li> </ol>
UK climate hazard and climate change adaptation resources for heritage
<p><span>This dataset (.xlsx) is a compendium of climate change hazard data and adaptation resources for cultural heritage. It was created by JBA Consulting for Historic England and is accompanied by a <a href="https://historicengland.org.uk/research/results/reports/16-2024">research report</a> which provides the background, methodology, and results of the project. One aim of the project was to identify and compile climate hazard resources (data and tools) that could assist those managing the UK historic environment, with specific attention paid to data availability, spatial resolution, and format. </span></p> <p><span> </span><span>The project identified 73 datasets and 38 tools. The datasets were linked to relevant climate hazards from a standardised hazard vocabulary (<a href="../records/10868587">Thomas, 2024</a>). The attached pdf file provides further details on how to use the dataset. Further information can be found in the report, and questions can be addressed to Kate Guest at <a href="mailto:Kate.Guest@HistoricEngland.org.uk">Kate.Guest@HistoricEngland.org.uk</a>. </span></p>
Inter- and intraspecific selection in alien plants: how population growth, functional traits and climate responses change with residence time
<p><strong>Aim: </strong>When alien species are introduced to new ranges, climate or trait mismatches may initially constrain their population growth. However, inter- and intraspecific selection in the new environment should cause population growth rates to increase with residence time. Using a species-for-time approach, we test whether with increasing residence time (a) negative effects of climatic mismatches between the species' new and native range on population growth weaken, and (b) functional traits converge towards values that maximize population growth in the new range.</p> <p><strong>Location:</strong> Germany.</p> <p><strong>Time period: </strong>12,000 years BP to present.</p> <p><strong>Major taxa studied: </strong>46 plant species of the Asteraceae family.</p> <p><strong>Methods:</strong> We set up a common-garden mesocosm-experiment using annual plant species with a wide range of residence times (7-12,000 years) and followed their population dynamics over two years. We calculated climatic distance between the common garden and the species' native range. We also measured key functional traits of each species to analyse trait-demography relationships and test trait convergence with increasing residence time.</p> <p><strong>Results: </strong>We found no support for the hypothesis that negative effects of climatic mismatches on population growth weaken with residence time. However, seed mass had a clear negative effect on population growth. As expected under such strong directional selection between or within species, increasing residence time led seed mass to converge to low values that increase population growth. Accordingly, population growth tended to increase with residence time.</p> <p><strong>Main conclusions: </strong>We identify trait but not climatic mismatches as important constraints on population growth of invaders. Understanding how inter- and intraspecific selection shapes functional traits of alien species should improve the predictability of future invasions and help understanding limits to the population growth and spread of invaders already present. In a broader context, this study contributes to the conceptual integration of invasion biology with community, functional, and population ecology.</p>
Major population splits coincide with episodes of rapid climate change in a forest-dependent bird
<p>Climate change influences population demography by altering patterns of gene flow and reproductive isolation. Direct mutation rates offer the possibility for accurate dating on the within-species level but are currently only available for a handful of vertebrate species. Here, we use the first directly estimated mutation rate in birds to study the evolutionary history of pied flycatchers (Ficedula hypoleuca). Using a combination of demographic inference and environmental niche modelling, we show that all major population splits in this forest-dependent system occurred during periods of increased climate instability and rapid global temperature change. We show that the divergent Spanish subspecies originated during the Eemian-Weichselian transition 115 – 104 thousand years ago (kya), and not during the last glacial maximum (26.5 - 19 kya), as previously suggested. The magnitude and rates of climate change during the glacial-interglacial transitions that preceded population splits in pied flycatchers were similar to, or exceeded, those predicted to occur in the course of the current, human-induced climate crisis. As such, our results provide a timely reminder of the strong impact that episodes of climate instability and rapid temperature changes can have on species' evolutionary trajectories, with important implications for the natural world in the Anthropocene.</p>
Data from: Accelerated shifts in terrestrial life zones under rapid climate change
<p>Datasets depicting historical (1901-1920), contemporary (1979-2013), and future (2061-2080) life zones as global rasters at 30 arc-second resolution in GeoTiff format are included, which were produced for the study "Accelerated shifts in terrestrial life zones under rapid climate change", published in <i>Global Change Biology</i> by Elsen <i>et al</i>. Life zones are determined by distinct combinations of biotemperature and precipitation and represent broad-scale ecosystem types (<i>sensu</i> Holdridge<span class="MsoFootnoteReference"><span class="MsoFootnoteReference">[1]</span></span>). For the future period, life zone maps were produced using five general circulation models (GCMs: CESM1-BGC, MPI-ESM-MR, ACCESS1-3, MIROC5, and CMCC-CM), each under two representative concentration pathways (RCPs: RCP4.5 and RCP8.5). An ensemble mean across all five GCMs is also included for each RCP. All input datasets are publicly available and, along with the complete methodology, are described in Elsen <i>et al.</i></p> <div> <div> <p class="MsoFootnoteText"><span class="MsoFootnoteReference"><span class="MsoFootnoteReference">[1]</span></span> Holdridge, LR (1947) Determination of world plant formations from simple climatic data. <i>Science</i>, <b>105</b>, 367–368.</p> </div> </div>
Dataset for "Winter inverse lake stratification under historic and future climate change"
<p>Summary results for Woolway et al., Winter inverse lake stratification under historic and future climate change. See README file for specific information on the variables provided.</p>
Existing land uses constrain climate change mitigation potential of forest restoration in India
<p>The datasets were developed as part of the publication "Existing land uses constrain climate change mitigation potential of forest restoration in India". Please refer to the manuscript for processing details.<br> <br> ForestBioclimaticEnvelop_ProjectionUTM is the bioclimatic envelope of forests developed. The data is in raster format (GeoTIFF 32bit Float) where pixel values = 1 represent the bioclimatic envelope of forests and remaning pixel values are NA. The spatial resolution is 60m in WGS 84 UTM 43N projection system.</p> <p>FinalOpportunity_AfterExclusions_ProjectionUTM is the feasible area of opportunity, after all exclusions of land uses and covers that cannot naturally regenerate to forests. The data is in raster format (GeoTIFF 32bit Float) where pixel values = 1 represent the bioclimatic envelope of forests and remaning pixel values are NA. The spatial resolution is 60m in WGS 84 UTM 43N projection system.</p>
How melanism affects the sensitivity of lizards to climate change
<p>The impact of climate change on global biodiversity is firmly established, but the differential effect of climate change on populations within the same species is rarely considered. In ectotherms, melanism (i.e. darker integument due to heavier deposition of melanin) can significantly influence thermoregulation, as dark individuals generally heat more and faster than bright ones. Therefore, darker ectotherms might be more susceptible to climate change. Using the color-polyphenic lizard <em>Karusasaurus polyzonus</em> (Squamata: Cordylidae), we hypothesized that, under future climatic projections, darker populations will decrease their activity time more than brighter ones due to their greater potential for overheating. To test this, we mechanistically modeled the body temperatures of 56 individuals from five differently-colored populations under present and future climate conditions. We first measured morphological traits and integumentary reflectance from live animals, and then collected physiological data from the literature. We used a biophysical model to compute activity time of individual lizards as proxy for their viability, and thereby predict how different populations will cope with future climate conditions. Contrary to our expectations, we found that all populations will increase activity time and, specifically, that darker populations will become relatively more active than bright ones. This suggests that darker populations of <em>K. polyzonus</em> may benefit from global warming. Our study emphasizes the importance of accounting for variation between populations when studying responses to climate change, as we must consider these variations to develop efficient and specific conservation strategies.</p>
Mimulus cardinalis plasticity analyses and R scripts for: Spatial variation in high temperature-regulated gene expression predicts evolution of plasticity with climate change in the scarlet monkeyflower
<p>A major way that organisms can adapt to changing environmental conditions is by evolving increased or decreased phenotypic plasticity. In the face of current global warming, more attention is being paid to the role of plasticity in maintaining fitness as abiotic conditions change over time. However, given that temporal data can be challenging to acquire, a major question is whether evolution in plasticity across space can predict adaptive plasticity across time. In growth chambers simulating two thermal regimes, we generated transcriptome data for western North American scarlet monkeyflowers (<i>Mimulus cardinalis</i>) collected from different latitudes and years (2010 and 2017) to test hypotheses about how plasticity in gene expression is responding to increases in temperature, and if this pattern is consistent across time and space. Supporting the genetic compensation hypothesis, individuals whose progenitors were collected from the warmer-origin northern 2017 descendant cohort showed lower thermal plasticity in gene expression than their cooler-origin northern 2010 ancestors. This was largely due to a change in response at the warmer (40ºC) rather than cooler (20ºC) treatment. A similar pattern of reduced plasticity, largely due to a change in response at 40ºC, was also found for the cooler-origin northern versus the warmer-origin southern population from 2017. Our results demonstrate that reduced phenotypic plasticity can evolve with warming and that spatial and temporal changes in plasticity predict one another.</p>
Exposure of boreal aapa mires to climate change
<p>This repository contains four zipped data files which contain (i) the spatial distribution of aapa mire complexes (‘aapa mires’) and their wettest flark-dominated parts (‘wet aapa mires’) situated in the aapa mire and palsa mire zones of Finland, as selected for the study by Heikkinen et al. (in review), (ii) values for the six bioclimatic variables (growing degree days, mean January and July temperature, annual precipitation, and May and July water balance) averaged for the years 1981–2010, and developed for the studied aapa mires and wet aapa mires using a 50 x 50 m lattice system, and (iii) values for the same six bioclimatic variables developed for future climates and the two types of study mires, based on the global climate models for 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5), and (iv) values of climate velocity metrics calculated for the six bioclimatic variables and the two types of study mires. These data provide the essential data employed in conducting the analysis in the following work:</p> <p>Risto K. Heikkinen<sup>1</sup>, Kaisu Aapala<sup>1</sup>, Niko Leikola<sup>1</sup> and Juha Aalto<sup>2</sup>: Exposure of boreal aapa mires to climate change, in review.</p> <p><sup>1</sup> Biodiversity Centre, Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland</p> <p><sup>2 </sup>Finnish Meteorological Institute, Weather and climate change impact research, Helsinki, Finland</p> <p>The data files are embedded in four compressed zip files (one of them including a geodatabase folder with files) which include several ArcGIS compatible tiff-raster or shape files. The names and contents of the four zipped files are as follows: (1) mires.zip – includes shape files describing the location and spatial configuration of the aapa mires (‘Aapa_mires.shp’) and the wet aapa mires (‘Wet_aapa_mires.shp’) included in the study, and the borders of different mire zones in Finland (‘Mire_zones.shp’); (2) climate_data_aapa_mires.zip – includes 18 tiff raster files showing the values of the six bioclimatic variables in the studied aapa mires within the 50 x 50 m resolution grid. The data in this zipped file include climate data averaged for the years 1981 – 2010 and for the future time slice of 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5); (3) climate_data_wet_aapa_mires.zip – includes 18 tiff raster files showing the values of the six bioclimatic variables in the studied wet aapa mires within the 50 x 50 m resolution grid. Similarly as in (2), the data in this zipped file include climate data averaged for the years 1981 – 2010 and for the future time slice of 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5); (4) velocity_data_for_mires.zip – includes zipped geodatabase folder velocity_open_mires.gdb which, in turn, includes spatial ArcGIS surfaces for the climate change velocity metric calculated for all the six bioclimatic variables, and the two types of mires and the two RCPs.</p> <p>In the zipped files (2) and (3), first part of the names of the included files refer to one of the six bioclimatic variables as follows: GDD5 – growing degree days, PREC – annual precipitation, TEMP_Jan – mean January temperature, TEMP_July – mean July temperature, WAB_May – May water balance, WAB_July – July water balance; and the remaining part of the name indicates the time period, type of the RCP and that of the mire. </p> <p>It should be noted that these data are embargoed until the end of the SUMI project for which they were developed, i.e. 1.1.2023. The coordinate system for the data files is: ETRS-TM35FIN (EPSG: 3067) (or YKJ Finland/Finnish Uniform Coordinate System (EPSG: 2393)).</p> <p>Summarization of the key settings of the study is provided below. A detailed treatment is included in the manuscript Heikkinen et al. (in review). Once the manuscript is accepted for publication an updated link will be provided.</p> <p><strong>Study system:</strong> Aapa mires are waterlogged, peat-accumulating EU Habitats Directive priority habitats whose ecological conditions and biodiversity values may be jeopardized by climate change. Aapa mires depend on the surface water flows from the surroundings which makes them sensitive to hydrological alterations and falling water tables caused by land use (ditching for peatland drainage) as well as climate change (Gong et al. 2012, Sallinen et al. 2019). This sensitivity of aapa mires and their biodiversity to increasing temperatures and decreasing water balance and precipitation can be of particular concern as they occur in northern hemisphere, in areas where the largest climatic changes are projected to take place (AMAP 2017, Väliranta et al. 2017. Kolari et al. 2021). In the study by Heikkinen et al. (in review), we assess the climate exposure of these habitats by developing velocity metrics for both the aapa mire complexes (‘aapa mires’) and their wettest flark-dominated parts (‘wet aapa mires’) in Finland.</p> <p><strong>Aapa mire data: </strong>Occurrences of aapa mires were identified from the CORINE CLC2018 land cover data which is available in Finland as a 20 x 20 m resolution raster data, by focusing on the CORINE category 4121 (‘Peatbogs’) which includes various open mires occurring in aapa mire and palsa mire zones, as well as in raised bogs zones. We excluded open mires occurring in the raised bogs zone but included CORINE Peatbog occurrences both from the aapa mire and palsa mire zones. This opted for this decision because open mires in aapa and palsa mire zones share several matching ecological features, and because palsa mires may provide suitable habitats for aapa mire species under warming climate.</p> <p>The adjacent peatbog 20-m pixels in the aapa and palsa mire zones were merged and converted into contiguous peatland polygons. From these, polygons smaller than 10 ha in size were excluded because typically they show only limited number of ecological elements central to the representative aapa mires. These selected ≥10 ha peatland polygons formed the first study mire dataset, aapa mire complexes, or ‘aapa mires’ in short (i.e., the whole aapa mire ecosystem containing all embedded mire habitats therein). The second study mire dataset was constrained to include only the wettest parts of aapa mire complexes characterized by flarks, i.e., open water pools, referred here simply as ‘wet aapa mires’. These wet aapa mire occurrences are typically smaller than the whole aapa mire complexes and occur more sparsely in the landscape. Thus, the climatic exposure of wet aapa mires can be expected to be greater than that of aapa mire complexes. This will very likely cause elevated climate change adaptation challenges for habitat specialist species that require open water or permanently wet environments. The spatial data for the wet aapa mires were determined with the help of the topographic database developed by the National Land Survey of Finland (NLS), and the land cover class ‘Swamps classified as difficult, dangerous and impossible to cross’ therein.</p> <p><strong>Climate data: </strong>In the first phase, monthly average air temperature data for 1981–2010 were constructed at the 50 x 50 m spatial resolution across Finland, as described in Aalto et al. (2017) and Heikkinen et al. (2020, 2021). This was done by modelling the weather station data from 313 Fennoscandian stations together with variables of geographical location, local topography and water cover. Monthly precipitation data were developed by fitting kriging interpolation method to the data on 343 rain gauges, and the data on geographical location, topography and proximity to the sea. Based on the monthly temperature and precipitation data, six bioclimatic variables describing key ecological winter- and summer-time conditions for aapa mire ecosystems were calculated (cf. Parviainen and Luoto 2007, Ruuhijärvi 1988, Rydin and Jeglum 2006): (1) annual temperature sum above the base temperature of 5 °C (growing degree days, GDD5), (2) mean January temperature, (3) mean July temperature, (4) monthly climatic water balance calculated for May and (5) for July, and (6) annual precipitation sum. The two climatic water balance variables were calculated as the difference between the May - or July - total precipitation sum and the potential evapotranspiration (PET) in the corresponding month following Skov and Svenning (2004).</p> <p>In the second step, the data based on an ensemble of 23 global climate models from the Coupled Model Intercomparison Project (CMIP5) archives (Taylor et al. 2012) were employed to develop future climate surfaces averaged for the years 2040–2069 and the two Representative Concentration Pathways (RCP4.5 and RCP8.5). The monthly air temperature and precipitation data in these climate surfaces were interpolated to match the 50 × 50 m grid, then the change predicted by the GCMs was added to the 1981–2010 climate data, and finally, the values for the six bioclimatic variables were recalculated for the 50-m resolution grid across the whole Finland.</p> <p>In the third step, all the developed climate surface datasets were intersected by the spatial datasets of the two differently delimited aapa mire networks, i.e. ‘aapa mires’ and ‘wet aapa mires’. This allowed calculation of the climate change velocity metrics separately for the two types of aapa mires, namely, for both mire datasets by measuring the distance between climatically similar 50-m grid cells in the present and future climates by considering only locations with either (i) aapa mires, or (ii) wet aapa mires. Thus, matrix areas providing unsuitable habitat for aapa mire biodiversity were excluded and for both types of mires the distance from the present-day mire cell was linked to the nearest corresponding mire cell with similar future climatic conditions.</p> <p>The climate data for the years 1981 – 2010 and the future time slice of 2040–2069 and the two Representative Concentration Pathways (RCP4.5 and RCP8.5), clipped to the networks of the two types of aapa mires for all the six bioclimatic variables are included in the following two zipped files: ‘climate_data_aapa_mires.zip’ and ‘climate_data_wet_aapa_mires.zip’.</p> <p><strong>Climate change velocity metrics: </strong>The climate velocities for the six bioclimatic variables, developed separately for the two types of aapa mires and the two RCPs, were calculated with climate-analog method (see Brito-Morales et al. 2018). For these calculations, both the present-day and future climate data from the two RCP scenarios were converted from continuous values into categorical climate surfaces following Hamann et al. (2015). During these conversion processes, following categories and within-class ranges were used: GDD5, within-class range 50 °C; January and July temperatures, within-class range 0.5 °C; water balance of May and July, within-class range 2.5 mm; and annual precipitation, within-class range 25 mm.</p> <p>In the conversion process, the climate surfaces in each of the 50-m grid cells were reclassified into one of the 29 GDD5, 27 January temperature, 22 July temperature, 21 May water balance, 22 July water balance, and 19 annual precipitation categories. Using the reclassified climate surfaces, the minimum distances between mire grid cells with similar present-day and future climates for the six variables were determined with the Euclidean distance function in ArcGIS. In the final step of calculating the velocity metrics, the mire-to-mire distances were divided by the number of years between the two points in time (see Brito-Morales et al., 2018; Heikkinen et al., 2020).</p> <p>The derived velocity metrics for the six bioclimatic variables yielded six individual estimates of climate exposure for the two types of study mires, illustrating the magnitude of climate displacement that the local mire species communities are projected to experience (Hamann et al. 2015, Brito-Morales et al., 2018). In our study, for each contiguous aapa mire and wet aapa mire, the mean velocity value for the climate variables were calculated as the average of the 50-m grid cells included in it.</p> <p>The data on the 50-m resolution velocities for the six bioclimatic variables and the two types of aapa mires and the two RCPs are included in the zip file ‘velocity_data_for_mires.zip’.</p> <p><strong>References</strong></p> <p>Aalto, J., Riihimäki, H., Meineri, E., Hylander, K., Luoto, M. (2017) Revealing topoclimatic heterogeneity using meteorological station data. International Journal of Climatology 37, 544-556.</p> <p>AMAP (2017) Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway.</p> <p>Brito-Morales, I., García Molinos, J., Schoeman, D.S., Burrows, M.T., Poloczanska, E.S., Brown, C.J., Ferrier, S., Harwood, T.D., Klein, C.J., McDonald-Madden, E., Moore, P.J., Pandolfi, J.M., Watson, J.E.M., Wenger, A.S., Richardson, A.J. (2018) Climate Velocity Can Inform Conservation in a Warming World. Trends in Ecology & Evolution 33, 441-457.</p> <p>Gong, J., Wang, K., Kellomäki, S., Zhang, C., Martikainen, P.J., Shurpali, N. (2012) Modeling water table changes in boreal peatlands of Finland under changing climate conditions. Ecological Modelling 244, 65-78.</p> <p>Hamann, A., Roberts, D.R., Barber, Q.E., Carroll, C., Nielsen, S.E. (2015) Velocity of climate change algorithms for guiding conservation and management. Global Change Biology 21, 997-1004.</p> <p>Heikkinen, R.K., Kartano, L., Leikola, N., Aalto, J., Aapala, K., Kuusela, S., Virkkala, R. (2021) High-latitude EU Habitats Directive species at risk due to climate change and land use. Global Ecology and Conservation 28, e01664.</p> <p>Heikkinen, R.K., Leikola, N., Aalto, J., Aapala, K., Kuusela, S., Luoto, M., Virkkala, R. (2020) Fine-grained climate velocities reveal vulnerability of protected areas to climate change. Scientific Reports 10.</p> <p>Kolari, T.H.M., Sallinen, A., Wolff, F., Kumpula, T., Tolonen, K., Tahvanainen, T. (2021) Ongoing Fen–Bog Transition in a Boreal Aapa Mire Inferred from Repeated Field Sampling, Aerial Images, and Landsat Data. Ecosystems.</p> <p>Parviainen, M., Luoto, M. (2007) Climate envelopes of mire complex types in fennoscandia. Geografiska Annaler: Series A, Physical Geography 89, 137-151.</p> <p>Ruuhijärvi, R., (1988) Mire vegetation. Atlas of Finland 141-143. Biogeography, nature conservation. . National Board of Survey and Geographical Society of Finland, Helsinki, pp. 2-4.</p> <p>Rydin, H., Jeglum, J. (2006) The biology of peatlands. Oxford University Press, Oxford.</p> <p>Sallinen, A., Tuominen, S., Kumpula, T., Tahvanainen, T. (2019) Undrained peatland areas disturbed by surrounding drainage: a large scale GIS analysis in Finland with a special focus on aapa mires. Mires and Peat 24, 1-22.</p> <p>Skov, F., Svenning, J.-C. (2004) Potential impact of climatic change on the distribution of forest herbs in Europe. Ecography 27, 366-380.</p> <p>Taylor, K.E., Stouffer, R.J., Meehl, G.A. (2012) An Overview of CMIP5 and the Experiment Design. Bulletin of the American meteorological Society 93, 485-498.</p> <p>Väliranta, M., Salojärvi, N., Vuorsalo, A., Juutinen, S., Korhola, A., Luoto, M., Tuittila, E.-S. (2017) Holocene fen–bog transitions, current status in Finland and future perspectives. The Holocene 27, 752-764.</p> <p> </p>
Adaptive potential of Coffea canephora from Uganda in response to climate change
<p>Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programs. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 <i>Coffea canephora</i> trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defense pathways in coffee. Seventy-one SNPs were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like <i>DREB</i>-like and <i>MYB</i> family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, like the <i>DXMT</i> gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of <i>ex-situ</i> conservation strategies are discussed.</p>
Eocene to Oligocene vegetation and climate in the Tasmanian Gateway region controlled by changes in ocean currents and pCO2
<p>Datasets accompanying Eocene to Oligocene vegetation and climate in the Tasmanian Gateway region controlled by changes in ocean currents and pCO2 by Amoo et al.</p> <p>Supplementary table S1: Raw palynomorph assemblage data, total counts, ODP Site 1172 </p> <p>Supplementary table S2: Sporomorph-based climate estimates including MAT, WMMT, CMMT and MAP </p> <p>Supplementary table S3: Sporomorph diversity indices</p>
Drought assessment has been outpaced by climate change: Empirical arguments for a paradigm shift
<p>Derived datasets produced in the analysis of "<strong>Drought assessment has been outpaced by climate change: Empirical arguments for a paradigm shift</strong>". </p>
Factors determining regional climate change competitiveness
<p>Regional climate change competitiveness is the comprehensive ability of a region to achieve and sustain the competitive advantage and attain economic and social development under climate change constraints when compared with other regions in the process of development. This database contains the raw data illustrating the EU region’s (NUTS2) impact on climate change and the effects of the region's and sector's climate change adaptatove measures.</p>
Data repository for "Climate change increases the severity and duration of soil water stress in the temperate forest of eastern North America"
<p>Dataset provided for publication in Frontiers in Forests and Global Change : "Climate change increases the severity and duration of soil water stress in the temperate forest of eastern North America".</p>
Climate warming changes synchrony of plants and pollinators
<p></p> <p class="MsoNormal"><span>Climate warming changes the phenology of many species. When interacting organisms respond differently, climate change may disrupt their interactions and affect the stability of ecosystems. Here, we used GBIF occurrence records to examine phenology trends in plants and their associated insect pollinators in Germany since the 1980s. We found strong phenological advances in plants, but differences in the extent of shifts among pollinator groups. The temporal trends in plant and insect phenologies were generally associated with interannual temperature variation, and thus likely driven by climate change. When examining the synchrony of species-level plant-pollinator interactions, their temporal trends differed among pollinator groups. Overall, plant-pollinator interactions become more synchronized, mainly because the phenology of plants, which historically lagged behind that of the pollinators, responded more strongly to climate change. However, if the observed trends continue, many interactions may become more asynchronous again in the future. Our study suggests that climate change affects the phenologies of both plants and insects, and that it also influences the synchrony of plant-pollinator interactions.</span></p>
Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients
<p><span>Plant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates </span><span>environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (<em>Artemisia tridentata </em>Nutt.) plant communities that span </span><span>76 million ha </span><span>in the western United States. We used an individual-based plant simulation model that represents intra- and inter-specific competition for water availability, which is represented by a process-based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine-scale interpolated surfaces of functional type biomass for our study area. </span>Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of -20% to +27%), declines in perennial C<sub>3</sub> grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C<sub>4</sub> grasses. The largest declines in big sagebrush, perennial C<sub>3</sub> grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture-limited vs. temperature-limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.</p>
CESM1-SOM Climatologies used for "Climate Sensitivity is Sensitive to Changes in Ocean Heat Transport" (published in Journal of Climate, Mar 2022)
<p>CESM1-SOM climatologies.</p> <p>Pre-industrial control run = SOM_Control.cam5.0030-0059.ann.nc</p> <p>CO2-doubling experiments:</p> <ul> <li>OHT + 30% = SOM_OHFC_P30_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT + 15% = SOM_OHFC_P15_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>Control OHT = SOM_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT - 15% = SOM_OHFC_M15_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT - 30% = SOM_OHFC_M30_2XCO2_032019.cam5.0030-0059.ann.nc</li> </ul>
Phenotypic but no genetic adaptation in zooplankton 24 years after an abrupt +10°C climate change
<p>Data and scripts for Pais-Costa et al 2022</p>
A review of existing and potential blue carbon contributions to climate change mitigation in the Anthropocene
<p><span>The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. </span></p> <p><span>Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional 'blue carbon' plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches.</span></p> <p><span>The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct </span><span>anthropogenic activities and climate change</span><span>. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. </span></p> <p><span><em>Synthesis and applications:</em> </span><span>This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further.</span></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.