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de-climate-change-analysis provides statistical analysis and plotting functions to determine absolute and relative changes in climate variables. It is used by the Digital Earth Climate Change Backend Module as part of the Digital Earth Flood Event Explorer. It is developed at the Helmholtz-Zentrum Hereon (https://www.hereon.de) in collaboration with the GFZ German Research Centre for Geosciences (https://www.gfz-potsdam.de) and funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). We acknowledge funding from the Initiative and Networking Fund of the Helmholtz Association through the project "Digital Earth". {"references": ["Gitlab Repository: https://git.geomar.de/digital-earth/de-climate-change/de-climate-change-analysis"]}

Content: Workflow (data and code) to reproduce the results presented in Minoli et al. (2022): Source code of the crop calendar model (./code/01_crop_calendars) Source code of the LPJmL model (./code/02_LPJmL5.0-gsadapt) Scripts for data analysis (./code/03_data_analysis) LPJmL model outputs (./lpjml_output_*) Outputs of the GGCMI crop model evaluation tool (./ggcmi_yield_evaluation_tool_output) # LPJmL outputs in ./data refer to the following climate scenarios gfd = GFDL-ESM2M had = HadGEM2-ES ips = IPSL-CM5A-LR mir = MIROC5 wfd = WFDEI Manuscript Reference: Sara Minoli, Jonas Jägermeyr, Senthold Asseng, Anton Urfels, Christoph Müller. Global crop yields can be lifted by timely adaptation of growing periods to climate change. Nature Communications.

The increasing frequency and intensity of summer heat waves is pushing freshwater zooplankton towards their upper thermal tolerance limits. At the same time, higher temperatures and prolonged water column stratification can favor the dominance of cyanobacteria in phytoplankton. Even when not toxic or grazing resistant, these prokaryotes lack phytosterols as essential precursors for cholesterol, the main sterol in animal tissues. Cholesterol plays a crucial role in the physiological adaptation of ectotherms to high temperature. Therefore, the shift to cyanobacteria-dominated systems may increase the vulnerability of zooplankton to heatwaves by intensifying cholesterol limitation. Here, we used death time curves that take into consideration the intensity and duration of a thermal challenge and a dynamic model to study the effects of cholesterol limitation on the heat tolerance of the keystone species Daphnia magna and to simulate the cumulative mortality that could occur in a fluctuating environment over several days of heatwave. We show that increasing cholesterol limitation does not affect the slope between time-to-immobilization and temperature, but does decrease the maximal temperature that Daphnia can withstand by up to 0.74°C. This seemingly small difference is sufficient to halve the time individuals can survive heat stress. Our simulations predicted that, when facing heatwaves over several days, the differences in survival caused by cholesterol limitation build up rapidly. Considering the anticipated intensity and duration of future (2070-2099) heatwaves, cholesterol limitation could increase mortality by up to 45% and 72% under low- and medium-greenhouse-gas-emission scenarios, respectively. These results suggest that the increasing risk of cholesterol limitation due to more frequent cyanobacterial blooms could compromise the resistance of zooplankton populations to future heatwaves. More generally, this study shows the importance of considering the nutritional context in any attempt to predict ectotherm mortality with increasing temperatures in the field. We used death time curves to study the effects of cholesterol limitation on the heat tolerance of the keystone species Daphnia magna and to simulate the cumulative mortality that could occur in a fluctuating environment over several days of heatwave. In that aim, D. magna neonates were grown under controlled laboratory condition on a sterol-free, non-toxic cyanobacterial diet (Synnechococcus obliquus) supplemented with different amounts of cholesterol-containing liposomes to obtain four cholesterol concentrations of 0.25, 2.5, 5, and 8 µg per mg C. In all treatments, a small amount of eicosapentaenoic acid (20:5ω3) was also added via liposomes (resulting in 0.25 µg 20:5ω3 per mg C) in order to prevent severe 20:5ω3 limitation, thereby aiding the development of daphnids. The daphnids were grown at 27°C, a non-lethal yet super-optimal temperature. Heat tolerance (time to immobilization) of the daphnids from the different cholesterol treatments was tested on day seven at five different constant temperatures (34.5°, 35.5°, 36.5°, 37.5°, 38.5°C). Here, we provide the raw data, as well as the R scripts used to analyze the data. Funding provided by: Deutsche ForschungsgemeinschaftCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001659Award Number: KO5330/1-1Funding provided by: GDR CNRS 3716 GRET*Crossref Funder Registry ID: Award Number:

This script was created to facilitate analysis of data (see data publication) pertaining to the publication: Jongejans, L. L., Strauss, J., Lenz, J., Peterse, F., Mangelsdorf, K., Fuchs, M. and Grosse, G. (2018). Organic matter characteristics in yedoma and thermokarst deposits on Baldwin Peninsula, west Alaska. Biogeosciences 15, 6033-6048. doi:10.5194/bg-15-6033-2018. The input data stem from sediment samples taken from two permafrost exposures in west Alaska. The input parameters are total organic carbon content, bulk density, wedge ice volume, deposit thickness and coverage. The script calculates the organic carbon storage of the permafrost sediments using a bootstrapping approach. The script was written for statistical software R (version 3.6.1). The current code and the required files are available on GitHub.

Photoperiod is a common cue for seasonal plasticity and phenology, but climate change can create cue-environment mismatches for organisms that rely on it. Evolution could potentially correct these mismatches, but phenology often depends on multiple plastic decisions made during different life stages and seasons that may evolve separately. For example, Pararge aegeria (Speckled wood butterfly) has photoperiod-cued seasonal life history plasticity in two different life stages: larval development time and pupal diapause. We tested for climate-change-associated evolution of this plasticity by replicating common garden experiments conducted on two Swedish populations 30 years ago. We found evidence for evolutionary change in the contemporary larval reaction norm—although these changes differed between populations—but no evidence for evolution of the pupal reaction norm. This variation in evolution across life stages demonstrates the need to consider how climate change affects the whole life cycle to understand its impacts on phenology. Please see the main paper and readme files for full details on the methods associated with this dataset. Data on the historic experiment was digitized for this study from the original data sheets associated with Nylin et al 1989, 1995 (see main text for full citations). Data for the contemporary experiment was generated by the authors for this study, following the methods of the historic experiment. Temperature data came from the Swedish Hydrological and Meteorological Institute weather stations and was restructured, but otherwise used as provided by SHMI. Readme file is also plain text compatible (.txt). Data files are comma-separated values (.csv) format. Software files (.R) are written in in R.Funding provided by: VetenskapsrådetCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100004359Award Number: 2017-04500Funding provided by: Bolin Centre for Climate Research*Crossref Funder Registry ID: Award Number:

About NaMIx ("Sustainable mobility index to assess the location-related mobility potential", in German: "Nachhaltige-Mobilität-Index zur Bewertung des standortbezogenen Mobilitätspotentials") is a project that aims to develop an index for sustainable mobility at locations and for neighborhoods that incorporates existing data and indices and maps different spatial levels. You can find out more about the project here: https://verkehrsforschung.dlr.de/de/projekte/namix. Most of the needed data can be retrieved from OpenStreetMap (OSM). Public transport stops can be obtained from OpenStreetMap (OSM) or General Transit Feed Specification (GTFS). Please note that due to restrictions regarding the distribution of some of the used datatypes, we had to limit the functionality in comparison to what has been shown during the final project presentation. Given the current version, the locations of buildings are retrieved from OSM instead of using the BKG address dataset. In addition, schools are retrieved from OSM as well and instead of using access by foot to elementary schools and access by bike to secondary schools NaMIx version 0.2.0 computes the access to all schools obtained from OSM by walk and by bike. Installation The current version is "NaMIx-0.2.0". It computes ten indicators almost (see above) as presented at the final project presentation. Please note that current NaMIx is realised as a Jupyter Notebook and that it is currently available in German only. To run the computation, please do the following Download a version of NaMIx : You may download a copy or fork the code at NaMIx' github page. : Besides, you may download the current release here: NaMIx-0.2.0.zip NaMIx-0.2.0.tar.gz Depack the obtained file into a folder of your choice (named from now on) Open the command line in this folder Optionally create a virtual python environment (recommended) run python -m venv venv_namix run venv_namix\Scripts\activate.bat Run pip install -r requirements.txt to install all necessary dependencies Download the 0.6.0 version of UrMoAC from UrMoAC-0.6.0.zip. Extract the contents into /demo/tools so that the jar file is located directly within this folder. Download GTFS data (e.g. from MVG). Extract the contents so that can be found in /demo/input/GTFS. Start the jupyter notebook You should have a command line open in Run python -m jupyter notebook open "namix_demo.ipynb" in the notebook The notebook processes the input data, computes the individual indicators and the joined NaMIx indicator, and stores the result in a geopackage file named "/demo/namix.gpkg". Authors NaMIx was developed and implemented by Serra Yosmaoglu, Benjamin Heldt, Daniel Krajzewicz, and Simon Nieland. ChangeLog NaMIx 0.2.0 (31.10.2023) initial version License NaMIx is licensed under the Eclipse Public License 2.0. When using it, please cite it via the DOI: https://doi.org/10.5281/zenodo.8328622 (v 0.2.0) Support If you have a usage question, please contact us via email (serra.yosmaoglu@dlr.de). Disclaimer We are not responsible for the contents of the pages we link to. The software is provided "AS IS". We cannot guarantee that the software works as you expect. References Boeing, G. (2017). OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks. Computers, Environment and Urban Systems 65, 126-139. doi:10.1016/j.compenvurbsys.2017.05.004 Krajzewicz, D., Heinrichs, D. & Cyganski, R. (2017). Intermodal Contour Accessibility Measures Computation Using the 'UrMo Accessibility Computer'. International Journal On Advances in Systems and Measurements, 10 (3&4), Seiten 111-123. IARIA. Heldt, B., Yosmaoglu, S. (2023). Neues Planungswerkzeug für Quartiere: Der Nachhaltige-Mobilität-Index. Emmett. https://emmett.io/article/der-nachhaltige-mobilitaet-index.

Hydroelectricity is critical for decarbonizing global energy production, but hydropower plants affect rivers, disrupt their continuity, and threaten migrating fishes. This puts hydroelectricity production in conflict with efforts to protect threatened species and re-connect fragmented ecosystems. Assessing the impact of hydropower on fishes will support informed decision-making during planning, commissioning, and operation of hydropower facilities. Few methods estimate mortalities of single species passing through hydropower turbines, but no commonly agreed tool assesses hazards of hydropower plants for fish populations. The European Fish Hazard Index bridges this gap. This assessment tool for screening ecological risk considers constellation specific effects of plant design and operation, the sensitivity and mortality of fish species and overarching conservation and environmental development targets for the river. Further, it facilitates impact mitigation of new and existing hydropower plants of various types across Europe. The tool does not yet support VBAs. In order to use it and produce reliable results, all input fields have to be reset manually before making a new assessment. The input window contains examplary dummy data.

1. The fasting endurance hypothesis (FEH) predicts strong selection for large body size in mammals living in environments where food supply is interrupted over prolonged periods of time. The Arctic is a highly seasonal and food restricted environment, but contrary to predictions from the FEH, empirical evidence shows that Arctic mammals are often smaller than their temperate conspecifics. Intraspecific studies integrating physiology and behaviour of different-sized individuals, may shed light on this paradox. 2. We tested the FEH in free-living Svalbard reindeer (Rangifer tarandus platyrhynchus). We measured daily energy expenditure (DEE), subcutaneous body temperature (Tsc) and activity levels during the late winter in 14 adult females with body masses ranging from 46.3 to 57.8 kg. Winter energy expenditure (WEE) and fasting endurance (FE) were modelled dynamically by combining these data with body composition measurements of culled individuals at the onset of winter (14 years, n = 140) and variation in activity level throughout winter (10 years, n = 70). 3. Mean DEE was 6.3±0.7 MJ day−1. Lean mass, Tsc and activity had significantly positive effects on DEE. Across all 140 individuals, mean FE was 85±17 days (range 48–137 days). In contrast to the predictions of the FEH, the dominant factor affecting FE was initial fat mass, while body mass and FE were not correlated. Furthermore, lean mass and fat mass were not correlated. FE was on average 80% (45 days) longer in fat than lean individuals of the same size. Reducing activity levels by ~16% or Tsc by ~5% increased FE by 7%, and 4%, respectively. 4. Our results fail to support the FEH. Rather, we demonstrate that (i) the size of fat reserves can be independent of lean mass and body size within a species, (ii) ecological and environmental variation influence FE via their effects on body composition, and (iii) physiological and behavioural adjustments can improve FE within individuals. Altogether, our results suggest that there is a selection in Svalbard reindeer to accumulate body fat, rather than to grow structurally large. The methods used to collect the data are described in Trondrud et al. 2021: "Fat storage influences fasting endurance more than body size in an ungulate. Accepted in Functional Ecology. Funding provided by: Norges ForskningsrådCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100005416Award Number: KLIMAFORSK 267613