Find research datasets worth reusing

opencc-by-4.0Dec 2019View details →

Raw data for Maier et al. "Seasonal controls on the diet, metabolic activity, tissue reserves and growth of the cold-water coral Lophelia pertusa"

All raw data presented in the article: Maier SR, Bannister RJ, van Oevelen D and Kutti T: Seasonal controls on the diet, metabolic activity, tissue reserves and growth of the cold-water coral Lophelia pertusa. Coral Reefs, in press.

opencc-by-4.0Jan 2020View details →

Development of an improved two-sphere integration technique for quantifying black carbon concentrations in the atmosphere and seasonal snow

A zip file for all Datasets used in the manuscript of "Development of an improved two-sphere integration technique for quantifying black carbon concentrations in the atmosphere and seasonal snow"

opencc-by-nc-sa-4.0Mar 2020View details →

SEAS5/System4-LARSIM_ME Seasonal Streamflow Forecasts for German Waterways

The datasets provided were produced as part of the IMPREX project for work package 4, task 1 “Development of the regional and European scale reforecast dataset of hydrological extremes “, work package 4, task 2 “Analysis of the impact of changes in precipitation attributes from short to medium and climatic ranges” and work package 9, task 3 “Case studies”. Analysis of the datasets are published in Meißner et al. 2017, in Deliverable 4.2 &bdquo; The sensitivity of sub-seasonal to seasonal streamflow forecasts to meteorological forcing quality, modelled hydrology and the initial hydrological conditions “ (Arnal et al. 2017) and in Deliverable 4.3 “Forecast skill developments” (Weerts et al. 2019). The aim was to evaluate the potential skill of seasonal streamflow forecasting for the German waterways Rhine, Elbe and Danube. As seasonal meteorological forecast data the reforecast dataset from ECMWF’s Seasonal Forecast System 4 (S4 hereafter) (Molteni et al. 2011) as well as from the fifth generation of ECMWF’s Seasonal forecasting system SEAS5 (ECMWF 2017, Johnson et al. 2018, Owens & Hewson 2018) of the period 1981 – 2016 were used. The horizontal resolution of System 4 is approximately 80 km. In operational mode the ensemble consists of 51 members generated by using an ensemble of initial conditions and by the use of stochastic physics. Re-forecasts starting on the 1st of each month for the years 1981-2016 are generated with the same model as used for the operational forecast. For the period 1981 – 2011 the ensemble size varies between 15 members (initialization months January, March, April, June, July, September, October, December) and 51 members (for the remaining months). Since 2012, the ensemble size is 51 members all over the year (operational forecasts). The fifth generation of ECMWF seasonal forecasting system SEAS5 replaced System 4 in November 2017. The horizontal resolution of the model is 0.4°x0.4° (approx. 36 km). The ensemble consists of 51-members created using a combination of Sea Surface Temperature SST and atmospheric initial condition perturbations and the activation of stochastic physics (ECMWF 2017). Re-Forecasts with the ensemble size of 25 members starting on the 1st of each month for the years 1981-2016 are generated with the same model as used for the operational forecast. The hydrological model applied is called LARSIM-ME (ME – MittelEuropa = Central Europe) and is based in the model software LARSIM (Large Area Runoff SImulation Model) originally developed by Ludwig & Bremicker (2006). LARSIM-ME covers the catchments of the rivers Rhine, Elbe, Weser/Ems, Odra and Upper Danube. The total catchment size simulated by the model is approximately 800,000 km². The spatial resolution is 5 km x 5 km and the computational time-step is daily. For more details about the model see Meißner et al. (2017). The precipitation and temperature data, used to force the hydrological model in simulation mode up to the initialization of the particular forecast, is taken from the E-OBS dataset, version 18 (Haylock et al. 2008). The downward surface solar radiation is extracted from the ERA-Interim reanalysis (Dee et al. 2011) for the period 1979-2018. For further details on data processing see Meißner et al. (2017). As meteorological seasonal forecasts tend to drift towards the model climate with increasing lead-time, the outputs daily total precipitation and air temperature from S4, interpolated to a 50 km x 50 km grid (multiple of the 5 km x 5 km model grid) and from SEAS5, interpolated to a 25 km x 25 km grid, respectively, were drift-corrected with the meteorological observation dataset used for the baseline simulation. As drift correction method the quantile-quantile method (Piani et al. 2010) was used. We corrected daily values of the different variables on a monthly basis, which means each daily value of the same month is corrected by the same scaling. Separate drift correction factors were estimated for each forecast initialization date (calendar month) and monthly lead time (month 1 to month 7) based on the reforecast datasets. In the final step the corrected precipitation and temperature were downscaled to the 5 km by 5 km model grid and used as forcing to create the streamflow re-forecast dataset with LARSIM-ME. Dataset Q_OBS_DE.nc: Mean daily observed flow of the gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe for the period 1951–2017 stored as variable q_obs(time=24472, stations=8). Data originate from the database of gauge measurements of the Federal Waterways and Shipping Administration (WSV). These data were quality checked and published by the gauge-operating WSV offices. Nevertheless, data errors and inconsistencies cannot be ruled out completely, so that neither the WSV nor the BfG do accept any liability for the correctness and completeness of the data. Data source: "German Federal Waterways and Shipping Administration (WSV)", provided by the German Federal Institute of Hydrology (BfG) <a href="https://zenodo.org/record/3696446">https://zenodo.org/record/3696446</a> Dataset Q_EOBS_LME.nc: Mean daily simulated flow of the hydrological model LARSIM-ME forced by observed meteorology from the EOBS dataset and ERA-Interim stored as variable q_sim (time=13880, stations=8). Period 1979-2016, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe. <pre><code>float q_sim(time=13880, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "simulated streamflow"; :coordinates = "lat lon";</code></pre> Dataset Q_System4_LME.nc: Mean daily forecasted flow of the hydrological model LARSIM-ME forced by air temperature and precipitation of ECMWF’s Seasonal Forecast System 4 re-forecasts initialized 1st of each month for the years 1981-2016 with a lead time of 7 months. Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe. Forecast values are stored as variable q_fcast_ens(time=432, lead_time=215, realization=51, stations=8), first dimension forecast dates, second dimension lead time, third dimension realization, fourth dimension stations. <pre><code>loat q_fcast_ens(time=432, lead_time=215, realization=51, stations=8); :_FillValue = -9999.0f; // float :long_name = "forecast streamflow ensemble"; :units = "m3/s"; :coordinates = "lat lon";</code></pre> Dataset Q_SEAS5_LME.nc: Mean daily forecasted flow of the hydrological model LARSIM-ME forced by air temperature and precipitation of ECMWF’s Seasonal Forecast System SEAS5 re-forecasts initialized 1st of each month for the years 1981-2016 with a lead time of 7 months. Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe. Forecast values are stored in the variable q_fcast_ens(time=432, lead_time=215, realization=25, stations=8), first dimension forecast dates, second dimension lead time, third dimension ensemble member, fourth dimension stations. <pre><code>float q_fcast_ens(time=432, lead_time=215, realization=25, stations=8); :_FillValue = -9999.0f; // float :long_name = "forecast streamflow ensemble"; :units = "m3/s"; :coordinates = "lat lon";</code></pre> Literature Arnal, L., H. Cloke, L. Magnusson, B. Klein, D. Meissner, A. de  Tomas, J. Hunink, I. Pechlivanidis, L. Crochemore, S. Suarez, A. Solera, J. Andreu, J. Knight, F. Liggins, A. Weerts, M. H. Ramos & G. Thirel (2017): The sensitivity of sub-seasonal to seasonal streamflow forecasts to meteorological forcing quality, modelled hydrology and the initial hydrological conditions. Deliverable 4.2, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811, <a href="http://www.imprex.eu/system/files/generated/files/resource/d4-2-imprex-v1-0.pdf">http://www.imprex.eu/system/files/generated/files/resource/d4-2-imprex-v1-0.pdf</a> Dee, D. P., S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M. A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A. C. M. Beljaars, L. van de Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A. J. Geer, L. Haimberger, S. B. Healy, H. Hersbach, E. V. Holm, L. Isaksen, P. Kallberg, M. Kohler, M. Matricardi, A. P. McNally, B. M. Monge-Sanz, J. J. Morcrette, B. K. Park, C. Peubey, P. de Rosnay, C. Tavolato, J. N. Thepaut & F. Vitart (2011): The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society 137(656), 553-597 ECMWF (2017): SEAS5 user guide - Version 1.1. ECMWF, Reading, UK Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones & M. New (2008): A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. Journal of Geophysical Research: Atmospheres 113(D20), D20119 Johnson, S. J., T. N. Stockdale, L. Ferranti, M. A. Balmaseda, F. Molteni, L. Magnusson, S. Tietsche, D. Decremer, A. Weisheimer, G. Balsamo, S. Keeley, K. Mogensen, H. Zuo & B. Monge-Sanz (2018): SEAS5: The new ECMWF seasonal forecast system. Geosci. Model Dev. Discuss. 2018, 1-44 Ludwig, K. & M. Bremicker (2006): The Water Balance Model LARSIM –Design, Content and Applications. 22. C. Leibundgut, S. Demuth and J. Lange (Eds), Freiburger Schriften zur Hydrologie, Institut für Hydrologie, Universität Freiburg im Breisgau, Freiburg, 141 pp. Meißner, D., B. Klein & M. Ionita (2017): Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe. Hydrol. Earth Syst. Sci. 21(12), 6401-6423 Molteni, F., T. Stockdale, M. Balmaseda, G. Balsamo, R. Buizza, L. Ferranti, L. Magnusson, K. Mogensen, T. Palmer & F. Vitart (2011): The new ECMWF seasonal forecast system (System 4). ECMWF Research Department Technical Memorandum n. 656, Shinfield Park, Reading Owens, R. & T. R. E. Hewson (2018): ECMWF Forecast User Guide. ECMWF, Reading, doi: 10.21957/m1cs7h Piani, C., J. O. Haerter & E. Coppola (2010): Statistical bias correction for daily precipitation in regional climate models over Europe. Theoretical and Applied Climatology 99(1-2), 187-192 Weerts, A., F. Silvestro, L. Magnusson, B. Klein, I. Pechlivanidis, F. Wetterhall, D. Lavers, E. Gascon, J. Day, S. Hagelin, M. Lindskog & B. van Osnabrugge (2019): Forecast skill developments. Deliverable 4.3, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811

opencc-zeroJun 2020View details →

Data from: A seasonal shift in offspring sex ratio of the brood parasitic Brown-headed Cowbird (Molothrus ater)

Avian obligate brood parasites do not provide parental care for their eggs and young, and may therefore serve as a strong model system to test predictions of evolutionary sex-allocation theories, independent of parental modulation of primary sex ratios. However, none of the handful of previous studies examining offspring sex ratio in brood parasitic birds have revealed a bias from parity at the level of the female parasite, the host species, or temporal scale(s). This is also surprising, because in at least one brood parasite, the Brown-headed Cowbird (Molothrus ater), adult sex ratios are consistently and heavily male-biased. Here we used a large database of embryonic and nestling cowbirds' genetic sex ratios collected from nests of a single host species, the Prothonotary Warbler (Protonotaria citrea) to assess potential overall, temporal, and individual patterns of bias. Contrary to previous findings, we documented an increase in the calculated male sex ratios later in the breeding season. There was no effect of whether embryos or nestlings were sampled, implying a lack of host parental effect on shifting the primary-to-secondary sex ratios of brood parasitic offspring. Future work should explore the sex-specific survival and recruitment pattern of fledgling cowbirds raised by this and other host species to reconcile theoretical and empirical predictions and patterns.

opencc-by-4.0Jun 2020View details →

Enhancing accuracy of air quality and temperature forecasts during paddy crop-residue burning season in Delhi via chemical data assimilation

This paper examines the accuracy of Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) generated 72 h fine particulate matter (PM2.5) forecasts in Delhi during the crop residue burning season of Oct-Nov 2017 with respect to assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals, persistent fire emission assumption, and aerosol-radiation interactions. The assimilation significantly pushes the model AOD and PM2.5 towards the observations with the largest changes below 5 km altitude in the fire source regions (northeastern Pakistan, Punjab, and Haryana) as well as the receptor New Delhi. WRF-Chem forecast with MODIS AOD assimilation, aerosol-radiation feedback turned on, and real-time fire emissions reduce the mean bias by 88-195 µg/m3 (70-86%) with the largest improvement during the peak air pollution episode of 6-13 November 2017. Aerosol-radiation feedback contributes ~21%, ~25%, and ~24% to reduction in mean bias of the first, second, and third day of PM2.5 forecast. Persistence fire emission assumption is found to work really well, as the accuracy of PM2.5 forecasts driven by persistent fire emissions was only 6% lower compared to those driven by real fire emissions. Aerosol-radiation feedback extends the benefits of assimilating satellite AOD beyond PM2.5 forecasts to surface temperature forecast with a reduction in the mean bias of 0.9oC - 1.5oC (17-30%). These results demonstrate that air quality forecasting can benefit substantially from satellite AOD observations particularly in developing countries that lack resources to rapidly build dense air quality monitoring networks.

opencc-by-4.0Jul 2020View details →

Complex multi-trait responses to multivariate environmental cues in a seasonal butterfly

Dataset for 'Complex multi-trait responses to multivariate environmental cues in a seasonal butterfly'.

Data from: Intra-specific variation in tree growth responses to neighborhood composition and seasonal drought in a tropical forest

1. Functional traits are expected to provide insights into the abiotic and biotic drivers of plant demography. However, successfully linking traits to plant demographic performance likely requires the consideration of important contextual and individual-level information that is often ignored in trait-based ecology. 2. Here, we modeled 8 years of growth from 1,138 individual trees from 36 tropical rain forest species. We compared models of tree growth parameterized using individual-level versus species mean trait data. We also compared models that considered regional climatic, local biotic and whole-plant allocation contexts to those that do not. 3. Our analyses show that growth models parameterized using individual-level trait information outperformed those that used species mean trait information and that these models often contradicted one another indicating that the common practice of using species mean trait data requires more scrutiny. Additionally, we found that models including climatic, biotic and allocation contexts outperformed those that did not and provide nuanced insights into the drivers of tree growth in a tropical forest. 4. Synthesis. Here, we have shown that the development of models of tree demographic performance upon the basis of traits can be improved through a consideration of individual-level trait variation as well as phenotypic and climatic contexts. We highlight that our ability to understand the drivers of tree population and community structure and dynamics in current and in future climates will be limited if contextual and individual-level data remains understudied.

Data from: Genotypic variation in the induction and persistence of transgenerational responses to seasonal cues

Phenotypes respond to environments experienced directly by an individual, via phenotypic plasticity, or to the environment experienced by ancestors, via transgenerational environmental effects. The adaptive value of environmental effects depends not only on the strength and direction of the induced response, but also on how long the response persists within and across generations, and how stably it is expressed across environments that are encountered subsequently. Little is known about the genetic basis of those distinct components, or even whether they exhibit genetic variation. We tested for genetic differences in the inducibility, temporal persistence, and environmental stability of transgenerational environmental effects in Arabidopsis thaliana. Genetic variation existed in the inducibility of transgenerational effects on traits expressed across the life cycle. Surprisingly, the persistence of transgenerational effects into the third generation was uncorrelated with their induction in the second generation. While environmental effects for some traits in some genotypes weakened over successive generations, others were stronger or even in the opposite direction in more distant generations. Therefore, transgenerational effects in more distant generations are not merely caused by the retention or dissipation of those expressed in prior generations, but they may be genetically independent traits with the potential to evolve independently.

Data from: Among-individual and within-individual variation in seasonal migration covaries with subsequent reproductive success in a partially-migratory bird

Within-individual and among-individual variation in expression of key environmentally-sensitive traits, and associated variation in fitness components occurring within and between years, determine the extents of phenotypic plasticity and selection and shape population responses to changing environments. Reversible seasonal migration is one key trait that directly mediates spatial escape from seasonally-deteriorating environments, causing spatio-seasonal population dynamics. Yet, within-individual and among-individual variation in seasonal migration versus year-round residence, and dynamic associations with subsequent reproductive success, have not been fully quantified. We used novel capture-mark-recapture mixture models to assign individual European shags (Phalacrocorax aristotelis) to 'resident, 'early migrant' or 'late migrant' strategies in two consecutive years, using year-round local resightings. We demonstrate substantial among-individual variation in strategy within years, and directional within-individual change between years. Further, subsequent reproductive success varied substantially among strategies, and relationships differed between years; residents and late migrants had highest success in the two years respectively, matching the years in which these strategies were most frequently expressed. These results imply that migratory strategies can experience fluctuating reproductive selection, and that flexible expression of migration can be partially aligned with reproductive outcomes. Plastic seasonal migration could then potentially contribute to adaptive population responses to currently changing forms of environmental seasonality.

Data from: Patterns of annual and seasonal immune investment in a temporal reproductive opportunist

Historically, investigations of how organismal investments in immunity fluctuate in response to environmental and physiological changes have focused on seasonally breeding organisms that confine reproduction to seasons with mild environmental conditions and abundant resources. The red crossbill, Loxia curvirostra, is a songbird that can breed opportunistically if conifer seeds are abundant, on both short, cold, and long, warm days, providing an ideal system to investigate interactions between immunity, reproduction, and environmental fluctuations. In this study, we measured inter- and intra-annual variation in complement, natural antibodies, PIT54, and leukocytes in crossbills across four summers (2010-2013) and multiple seasons within one year (summer 2011-spring 2012). Overall, we observed substantial changes in crossbill immune investment among summers, with interannual variation driven largely by food resources, while seasonal variation was less pronounced and lacked a dominant predictor of immune investment. However, we found weak evidence that physiological processes (e.g., reproductive condition, moult) or abiotic factors (e.g., temperature, precipitation) affect immune investment. Collectively, this study suggests that a reproductively flexible organism may simultaneously invest in both reproduction and survival-related processes, potentially by exploiting rich patches with abundant resources. More broadly, these results emphasize the need for more longitudinal studies of trade-offs associated with immune investment.

Data from: Chemical defenses shift with the seasonal vertical migration of a Panamanian poison frog

Dendrobatid poison frogs sequester lipophilic alkaloids from their arthropod prey to use as a form of chemical defense. Some dendrobatid frogs seasonally migrate between the leaf litter of the forest floor in the dry season to the canopy in the wet season, which may yield differences in prey (arthropods) and therefore alkaloid availability over space and time. Here, we document a seasonal vertical migration of Andinobates fulguritus (the yellow-bellied poison frog) from ground to canopy between dry and wet seasons. We observed turnover in alkaloid composition between seasons and found that dry season frogs contained a lower relative quantity of alkaloids; however, there was no change in alkaloid richness between seasons. The 77 alkaloids of 13 structural classes identified in this population appear to be derived mostly from mites and ants, though the two most common alkaloids were mite derived. Our observed shifts in defensive profiles are consistent with well-documented turnover in mite and ant communities between seasons and vertical strata. As climate change is expected to lengthen and strengthen dry seasons in many tropical regions, our results suggest that arboreal poison frogs forced to the ground for longer periods of time may see a shift in the abundance of alkaloids, possibly decreasing their defensive potential. This study provides further predictions for the wide-reaching effects of climate change, even as nuanced as charismatic poison frogs losing their poisons.

opencc-by-4.0Aug 2020View details →

Data: Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning

This data file consists of state-space model-derived locations and individual data used to analyze transmitter effects for sea ducks in Eastern North America and is associated with the manuscript "Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning" published in Ecography. Columns are organized as follows: id - unique identifier species - species from which the centroid was obtained (BLSC = black scoter, COEI = common eider, LTDU = long-tailed duck, SUSC = surf scoter, WWSC = white-winged scoter) date - date of location (mm/dd/yy) jday - Julian date of location year - calendar year of location lon - longitude of location lat - latitude of location b - average assignment of location to either migrant (1) or resident (2) across all runs of the state-space model b.5 - most probable behavioral category based on average state assignment (1 = b ≤ 1.5 ; 2 = b > 1.5) sex - sex of individual (M = male, F = female) age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year capture_reg - general area where individual was captured capture_subreg - specific region within capture region where individual was captured stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration) site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.) cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.) season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)

opencc-by-4.0Aug 2020View details →

Seasonal Variability of Mercury's Sodium Exosphere Deduced from MESSENGER Data and Numerical Simulation

This is the dataset used in "Suzuki et al. (2020). Seasonal variability of Mercury's sodium exosphere deduced from MESSENGER data and numerical simulation. Journal of Geophysical Research: Planets, 125, e2020JE006472. doi:10.1029/2020JE006472".

opencc-zeroAug 2020View details →

Winds at departure shape seasonal patterns of nocturnal bird migration over the North Sea

On their migratory journeys, terrestrial birds can come across large inhospitable areas with limited opportunities to rest and refuel. Flight over these areas poses a risk especially when wind conditions en route are adverse, in which case inhospitable areas can act as an ecological barrier for terrestrial migrants. Thus, within the East-Atlantic flyway, the North Sea can function as an ecological barrier. The main aim of this study was to shed light on seasonal patterns of bird migration in the southern North Sea and determine whether departure decisions on nights of intense migration were related to increased wind assistance. We measured migration characteristics with a radar that was located 18 km off the NW Dutch coast and used simulation models to infer potential departure locations of birds on nights with intense nocturnal bird migration. We calculated headings, track directions, airspeeds, groundspeeds on weak and intense migration nights in both seasons and compared speeds between seasons. Moreover, we tested if departure decisions on intense migration nights were associated with supportive winds. Our results reveal that on the intense migration nights in spring, the mean heading was towards E, and birds departed predominantly from the UK. On intense migration nights in autumn, the majority of birds departed from Denmark, Germany and north of the Netherlands with the mean heading towards SW. Prevailing winds from WSW at departure were supportive of a direct crossing of the North Sea in spring. However, in autumn winds were generally not supportive, which is why many birds exploited positive wind assistance which occurred on intense migration nights. This implies that the seasonal wind regimes over the North Sea alter its migratory dynamics which is reflected in headings, timing and intensity of migration.

opencc-by-4.0May 2020View details →

Dataset for "Seasonal dynamics of the COS and CO2 exchange of a managed temperate grassland"

Data of measurements and model output of the publication "Seasonal dynamics of the COS and CO2 exchange of a managed temperate grassland". https://doi.org/10.5194/bg-2020-27 Data consists of micrometeorological data, COS and CO2 flux measurements for a managed temperate mountain grassland in Austria. For additional information please contact: <a href="mailto:Georg.Wohlfahrt@uibk.ac.at">Georg.Wohlfahrt@uibk.ac.at</a> changes in version 2: includes extrapolated COS mixing ratios & includes the ustar filter for the flux data changes in version 3: corrected every instance of mixing ratio with mole fraction

opencc-zeroAug 2020View details →

Climate seasonality drives ant-plant-herbivore interactions via plant phenology in an extrafloral nectary-bearing plant community

<ol> <li>Interactions between ants and plants bearing extrafloral nectaries (EFNs) are among the most common mutualisms in Neotropical regions. Plants secrete extrafloral nectar, a carbohydrate-rich food that attracts ants, which in return protect plants against herbivores. This ant-plant mutualism is subjected to temporal variation, in which abiotic factors can drive the establishment and frequency of such mutualistic interaction. However, studies investigating how abiotic factors (e.g., climate) directly and indirectly influence ant-plant-herbivore interactions are incipient.</li> <li>In this study, we investigated direct and indirect (via plant phenology) effects of temperature and rainfall on ant-plant-herbivore interactions. To address these goals, we estimated six plant phenophases (newly flushed leaves, fully-expanded leaves, deciduousness, floral buds, flowers, and fruits) monthly, the activity of EFNs and abundance of ants and herbivores in 18 EFN-bearing plant species growing in a markedly seasonal region (the Brazilian Cerrado) during a complete growing season.</li> <li>Our results showed that (i) there were marked seasonal patterns in all plant phenophases, EFN activity, and the abundance of ants and herbivores; (ii) the peak of EFN activity and ant and herbivore abundance simultaneously occurred at the beginning of the rainy season, when new leaves flushed; and (iii) rainfall directly and indirectly (via changes in theproduction of new leaves) influenced EFN activity and this in turn provoked changes in ant abundance (but not on herbivores).</li> <li> Synthesis: Overall, our results build toward a better understanding of how climate drives seasonal patterns in ant-plant-herbivore interactions, explicitly considering plant phenology over time.</li> </ol>

opencc-zeroApr 2021View details →

Effects of sampling seasons and locations on fish environmental DNA metabarcoding in dam reservoirs

Environmental DNA (eDNA) analysis has seen rapid development in the last decade, as a novel biodiversity monitoring method. Previous studies have evaluated optimal strategies, at several experimental steps of eDNA metabarcoding, for the simultaneous detection of fish species. However, optimal sampling strategies, especially the season and the location of water sampling, have not been evaluated thoroughly. To identify optimal sampling seasons and locations, we performed sampling monthly or at two-monthly intervals throughout the year in three dam reservoirs. Water samples were collected from 15 and 9 locations in the Miharu and Okawa dam reservoirs in Fukushima Prefecture, respectively, and 5 locations in the Sugo dam reservoir in Hyogo Prefecture, Japan. One liter of water was filtered with glass-fiber filters and eDNA was extracted. By performing MiFish metabarcoding, we successfully detected a total of 21, 24, and 22 fish species in Miharu, Okawa, and Sugo reservoirs, respectively. From these results, the eDNA metabarcoding method had a similar level of performance compared to conventional long-term data. Furthermore, it was found to be effective in evaluating entire fish communities. The number of species detected by eDNA survey peaked in May in Miharu and Okawa reservoirs, and in March and June in Sugo reservoir, which corresponds with the breeding seasons of many of fish species inhabiting the reservoirs. In addition, the number of detected species was significantly higher in shore, compared to offshore samples in the Miharu reservoir, and a similar tendency was found in the other two reservoirs. Based on these results, we can conclude that the efficiency of species detection by eDNA metabarcoding could be maximized by collecting water from shore locations during the breeding seasons of the inhabiting fish. These results will contribute in the determination of sampling seasons and locations for fish fauna survey via eDNA metabarcoding, in the future.

opencc-zeroSep 2020View details →

Data from: Warm temperatures during cold season can negatively affect adult survival in an alpine bird

Climate seasonality is a predominant constraint on the lifecycles of species in alpine and polar biomes. Assessing the response of these species to climate change thus requires taking into account seasonal constraints on populations. However interactions between seasonality, weather fluctuations, and population parameters remain poorly explored as they require long-term studies with high sampling frequency. This study investigated the influence of environmental covariates on the demography of a corvid species, the alpine chough Pyrrhocorax graculus, in the highly seasonal environment of the Mont Blanc region. In two steps, we estimated: 1) the seasonal survival of categories of individuals based on their age, sex, etc., 2) the effect of environmental covariates on seasonal survival. We hypothesized that the cold season – and more specifically, the end of the cold season (spring) – would be a critical period for individuals, and we expected that weather and individual covariates would influence survival variation during critical periods. We found that while spring was a critical season for adult female survival, it was not for males. This is likely because females are dominated by males at feeding sites during snowy seasons (winter and spring), and additionally must invest energy in egg production. When conditions were not favourable, which seemed to happen when the cold season was warmer than usual, females probably reached their physiological limits. Surprisingly, adult survival was higher at the beginning of the cold season than in summer, which may result from adaptation to harsh weather in alpine and polar vertebrates. This hypothesis could be confirmed by testing it with larger sets of populations. This first seasonal analysis of individual survival over the full life cycle in a sedentary alpine bird shows that including seasonality in demographic investigations is crucial to better understand the potential impacts of climate change on cold ecosystems.