Find research datasets worth reusing

opencc-by-4.0Jan 2021View details →

FIGURE 7. Age-specific discriminant analysis using all morphometric parameters for all sites. 7A in Taxon-specific variability of leaf traits in three long-ranging fossil-species of the Paleogene and Neogene: Responses to climate?

FIGURE 7. Age-specific discriminant analysis using all morphometric parameters for all sites. 7A: Eocene. 7B: Oligocene. Triangles: Platanus neptuni. Squares: Eotrigonobalanus furcinervis. Circles: Daphnogene cinnamomifolia.

opencc-by-4.0Jan 2021View details →

FIGURE 8 in Taxon-specific variability of leaf traits in three long-ranging fossil-species of the Paleogene and Neogene: Responses to climate?

FIGURE 8. Circularity plotted against LWR. Blue circles: Platanus neptuni. Red squares: Eotrigonobalanus furcinervis. Yellow diamonds: Daphnogene cinnamomifolia. Black line: Relationship between circularity and length-towidth ratio of an ellipse. Please note that this relationship was calculated by using an approximate equation for the perimeter of an ellipse, which causes the slight deflection of the curve for high circularity values. As approximation, the following equation for the ellipse perimeter (EP) was used: EP = π* [2 * (a2 + b2)1/2].

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Dengue incidence and climatic variables in Cali from 2015 to 2021

In this work we studied the relationship between dengue incidence in Cali and the climatic variables that are known to have an impact on the mosquito and were available (precipitation, relative humidity, minimum, mean, and maximum temperature). Since the natural processes of the mosquito imply that any changes on climatic variables need some time to be visible on the dengue incidence, a lagged correlation analysis was done in order to choose the predictor variables of count regression models. A Principal Component Analysis was done to reduce dimensionality and study the correlation among the climatic variables. Finally, aiming to predict the monthly dengue incidence, three different regression models were constructed and compared using de Akaike information criterion. The best model was the negative binomial regression model, and the predictor variables were mean temperature with a 3-month lag and mean temperature with a 5-month lag as well as their interaction. The other variables were not significant on the models. And interesting conclusion was that according to the coefficients of the regression model, a 1°C increase in the monthly mean temperature will reflect as a 45% increase in dengue incidence after 3 months. The rises to a 64% increase after 5 months.

opencc-zeroMay 2024View details →

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Variable species establishment in response to microhabitat indicates different likelihoods of climate-driven range shifts

Climate change is causing geographic range shifts globally, and understanding the factors that influence species' range expansions is crucial for predicting future biodiversity changes. A common, yet untested, assumption in forecasting approaches is that species will shift beyond current range edges into new habitats as they become macroclimatically suitable, even though microhabitat variability could have overriding effects on local population dynamics. We aim to better understand the role of microhabitat in range shifts in plants through its impacts on establishment by Q1) examining microhabitat variability along large macroclimatic (i.e., elevational) gradients, Q2) testing which of these microhabitat variables explain plant recruitment and seedling survival, and Q3) predicting microhabitat suitability beyond species range limits. We transplanted seeds of 25 common tree, shrub, forb, and graminoid species across and beyond their current elevational ranges in the Washington Cascade Range, USA, along a large elevational gradient spanning a broad range of macroclimates. Over five years, we recorded recruitment, survival, and microhabitat (i.e., high resolution soil, air, and light) characteristics rarely measured in biogeographic studies. We asked whether microhabitat variables correlate with elevation, which variables drive species establishment, and whether microhabitat variables important for establishment are already suitable beyond leading range limits. We found that only 30% of microhabitat parameters covaried with elevation. We further observed extremely low recruitment and moderate seedling survival, and these were generally only weakly explained by microhabitat. Moreover, species and life stages responded in contrasting ways to soil biota, soil moisture, temperature, and snow duration. Microhabitat suitability predictions suggest that distribution shifts are likely to be species-specific, as different species have different suitability and availability of microhabitat beyond their present ranges, thus calling into question low-resolution macroclimatic projections that will miss such complexities. We encourage further research on species responses to microhabitat and including microhabitat in range shift forecasts.

opencc-zeroDec 2023View details →

opencc-by-4.0Jun 2024View details →

TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study. in Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats

TA B L E 1 Summary of model fit, based on the area under the curve (AUC) of the receiver operating characteristic (ROC) for training data, and the most important bioclimatic variables in past, present, and future (2070) Maxent models of 13 bat species included in this study.

Figure 2 in Climate variability of extreme air temperature events in the Eastern Black Sea

Figure 2. Changes in the mean monthly air temperature anomalies at the surface (relative to seasonal variability) smoothed by annual (orange) and eight-year (violet) gliding averaging in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E). Their linear trend is shown by black line and the accumulated sum of anomalies after removing the linear trend – by green line. Average values of anomalies for warm and cold half-year are marked by red and blue dots respectively.

Figure 1 in Climate variability of extreme air temperature events in the Eastern Black Sea

Figure 1. Changes in mean monthly air temperature at the surface (red) and their linear trend (blue) in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E).

Figure 4 in Climate variability of extreme air temperature events in the Eastern Black Sea

Figure 4. The annual changes in the mean amplitude (upper part), the number (middle part) and the mean duration (bottom part) of extreme events with positive (red lines) and negative (blue lines) air temperature anomalies in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E), exceeding two standard deviations, and their linear trends.

Figure 3 in Climate variability of extreme air temperature events in the Eastern Black Sea

Figure 3. The annual changes in the mean amplitude (upper part), the number (middle part) and the mean duration (bottom part) of extreme events with positive (red lines) and negative (blue lines) air temperature anomalies in the eastern part of the Black Sea (42° - 45°N, 37° - 42°E), exceeding one standard deviation, and their linear trends.

opencc-by-4.0Oct 2018View details →

Raw data sets from Jones et al. 2018 QSR publication: A multi-proxy approach to understanding complex responses of saltlake catchments to climate variability and human pressure: A Late Quaternary case study from south-eastern, Spain

Attached are the raw data sets containing the pollen data, DXR, Grain size and C14 ages from the recent publication: Jones et al. 2018 QSR publication: A multi-proxy approach to understanding complex responses of saltlake catchments to climate variability and human pressure: A Late Quaternary case study from south-eastern, Spain. Note that these data sets do contain hiatuses and a major age-reversal due to erosian which have likely been caused by increased seasonal wetness at the onset of the Holocene. A full explanation is provided in our 2018 publication. If you do wish to use the data, it is essential that you read the publication inorder to interpret the results correctly. We also require that when using this data that you correctly cite it (Bibliographic reference and the doi number of the data set). There were some problems uploading the XRF (geochemical) data sets, so I haven't included these yet, but hopefully will do eventually.  Below I have also included the abstract from our publication, which provides an overview of the purpose of our work and a brief summary of the main findings. Abstract of Jones et al. 2018: The article focuses on a former salt lake in the upper Vinalopo Valley in south-eastern Spain. The study spans the Late Pleistocene through to the Late Holocene, although with particular focus on the period between 11 ka cal BP and 3000 ka cal BP (which spans the Mesolithic and part of the Bronze Age). High resolution multi-proxy analysis (including pollen, non pollen palynomorphs, grain size, X-ray fluorescence, and X-ray diffraction) was undertaken on the lake sediments. The results show strong sensitivity to both long term and small changes in the evaporation/precipitation ratio, affecting the surrounding vegetation composition, lake-biota and sediment geochemistry. To summarise the key findings the main general trends identified include: 1) Hyper-saline conditions and low lake levels at the end of the Late Glacial 2) Increasing wetness and temperatures which witnessed an expansion of mesophilic woodland taxa, lake infilling and the establishment of a more perennial lake system at the onset of the Holocene 3) An increase in solar insolation after 9 ka cal BP which saw the re-establishment of pine forests 4) A continued trend towards increasing dryness (climatic optimum) at 7 ka cal BP but with continued freshwater input 5) An increase in sclerophyllous open woody vegetation (anthropogenic?), and increasing wetness (climatic?) is represented in the lake record between 5.9 and 3 ka cal BP 6) The Holocene was also punctuated by several aridity pulses, the most prominent corresponding to the 8.2 ka cal BP event. These events, despite a paucity of well dated archaeological sites in the surrounding area, likely altered the carrying capacity of this area both regionally and locally, particularly during the Mesolithic-Neolithic transition, in terms of fresh water supply for human/animal consumption, wild plant food reserves and suitable land for crop growth.

Fig. 1 in Lice community structure infesting Trinomys iheringi (Thomas, 1911) - Ocurrence, sex bias and climatic variables on tropical island

Fig. 1. Location of capture of Trinomys iheringi in Dois Rios Village, Ilha Grande, Rio de Janeiro State, Brazil, between April 2013, and December 2015.

Fig. 2 in Lice community structure infesting Trinomys iheringi (Thomas, 1911) - Ocurrence, sex bias and climatic variables on tropical island

Fig. 2. Distribution of Gyropus (m.) martini stages on Trinomys iheringi rodents. Host sex (F = female, M = male) and capture months (Aug = August, Dec = December, Feb = February, Jul = July, Nov = November) in Ilha Grande State Park, RJ, Brazil. The numbers along the x axis represent the number of lice life stages: male/female/nymph 1/nymph 2/nymph 3.

Fig. 4 in Lice community structure infesting Trinomys iheringi (Thomas, 1911) - Ocurrence, sex bias and climatic variables on tropical island

Fig. 4. Probability of lice occurrence on Trinomys iheringi as a function of humidity and sex (A), and humidity and age class (B) in Ilha Grande State Park, RJ, Brazil. The letters in the upper part of the graph represent the presence of lice on rodents, and the letters in the lower part of the graph indicate the absence of lice on rodents.

Fig. 3 in Lice community structure infesting Trinomys iheringi (Thomas, 1911) - Ocurrence, sex bias and climatic variables on tropical island

Fig. 3. Relationship between the natural logarithm of body mass and the natural logarithm of body length for Trinomys iheringi individuals infected and uninfected by lice in Ilha Grande State Park, RJ, Brazil. Open circles and the continuous line refer to uninfected individuals, while solid circles and the dashed line refer to infected individuals.

opencc-by-4.0Jul 2021View details →

Hourly estimates of climate variables for Greece, 2017-2018

Raster of hourly estimates of climate variables for Greece, 2017-2018. The estimates, which form the ERA5 Reanalysis data, are based on vast amounts of historical observations. From <a href="https://www.ecmwf.int/">ECMWF</a> through the Copernicus Climate Change Service. Prepared by <a href="https://www.athenarc.gr/">Athena Research Center</a> for use in the <a href="https://www.i4sea.eu/">i4SEA project</a>. The data was downloaded from <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">ERA5 hourly data on single levels from 1979 to present</a> on May 16, 2019. It covers the years 2017-2018 and a rectangular region encompassing Greece. The climate variables contained are: <ul> <li>10m u-component of wind (10u)</li> <li>10m v-component of wind (10v)</li> <li>2m dewpoint temperature (2d)</li> <li>2m temperature (2t)</li> <li>Mean sea level pressure (msl)</li> <li>Mean wave direction (mwd)</li> <li>Mean wave period (mwp)</li> <li>Sea surface temperature (sst)</li> <li>Significant height of combined wind waves and swell (swh)</li> <li>Surface pressure (sp)</li> <li>Total precipitation (tp)</li> </ul> Generated using Copernicus Climate Change Service information 2019. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

opencc-by-4.0Aug 2021View details →

KGClim historical: A 1-km global dataset of historical (1979-2013) Köppen-Geiger climate classification and bioclimatic variables

We presented a new dataset of 1-km Köppen-Geiger climate classification maps and 12 bioclimatic variables for the historical periods (1979-2008, 1980-2009, 1981-2010, 1982-2011, 1983-2012, 1984-2013).

opencc-by-4.0Feb 2023View details →

Data for 'Thermal regimes of groundwater- and lake-fed headwater streams differ in their response to climate variability'

This dataset contains seasonal and annual mean spot stream temperatures for the six groundwater-fed and seven lake-fed streams at the Turkey Lakes Watershed. We have also included seasonal and annual scale hydroclimatic variables (air temperature, solar radiation, discharge, precipitation, ice on/off dates, and April 1st SWE). The Turkey Lakes Watershed is approximately 65 km northwest of Sault Ste. Marie, Ontario, Canada.  Manual spot stream temperature measurements were made by field technicians visiting the catchment outlets as part of a routine water quality monitoring program at the TLW. The stream temperature data record extends from 1983 through 2018. The stream temperature record for stream 013 is 1986-2018. Hydroclimatic data is also 1983-2018, with the exception of lake ice data which ended in 2015. See the methods section of the associated publication for more details.

opencc-by-4.0Jun 2023View details →

Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables (Data)

Accompanying data for the Depsky and Pons (2023) PLoS ONE publication - Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables. This repository contains tables of the raw 2018 Guatemalan national census values at the individual, household, and residence levels, as well as its migration-specific data table. Municipality-average climate values from ERA5-Land are provided as well, in addition to a shapefile of the municipal boundaries. All standardized outcome and predictor variables used for each of the five models are provided as separate tables as well.