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opencc-zeroNov 2023View details →

Interests, beliefs, experience, and perceptions shape tolerance towards impacts of recovering predators

<ol> <li>The modification of landscapes is increasing the interface between humans and wildlife, while conflicts concerning predator impacts on human activities persist. Some previously persecuted but now protected predator species are experiencing recovery and range expansion.</li> <li>Tolerance is considered essential for achieving coexistence between humans and wildlife; however, its conceptualisation remains unresolved. Little is known about tolerance in the context of recovering predators, particularly which drivers are relevant to all or specific species and human interests.</li> <li>Using an online questionnaire survey shared with members of organisations with interests in rural land-based activities, we collected data on interests and beliefs, and attitudes, perceptions, experience, and management preferences for six recovering vertebrate predators in the UK (n=819). We created a species tolerance score representing the management choices of the respondents in different conflict scenarios, which differed in the degree of impact on the predator population.</li> <li>Our species tolerance score was characterized by a complex combination of the interests and beliefs of the respondents about wildlife management, perceptions and experience of that species (perceived benefits, population trend, positive and negative experience, indirect negative experience) and negative experience of other recovering predators. </li> <li>We found a tolerance gradient between interest groups with notable overlap between groups with primary interests in wildlife conservation, shooting, farming, and fishing. Although higher perceived benefits consistently corresponded to higher tolerance, having a negative experience of the species dampened the effect of perceived benefits on tolerance. When both negative personal and indirect experiences were reported, tolerance was dramatically reduced. The classification of species from least to most tolerated was consistent between interest groups. </li> <li>The application of our species tolerance score as the normative dimension (i.e., acceptability) in Brenner and Metcalf's (2020) Social Tolerance of Wildlife Framework highlights that tolerance (negative attitude-high acceptability) is potentially rare and more positive attitudes must be achieved before acceptance of the impacts of species can increase. </li> <li>Our findings highlight that considering only primary interests may hinder debates concerning recovering predators. Strategies to reduce negative experiences or change how they are perceived could significantly increase tolerance in combination with increasing positive experiences.</li> </ol>

opencc-by-4.0Nov 2022View details →

Population impact of fine particulate matter on tuberculosis risk in China: A causal inference

Supplementary to "Population impact of fine particulate matter on tuberculosis risk in China: A causal inference"

opencc-by-4.0Nov 2023View details →

Application of artificial neural network to forecast indoor air temperature in a building with artificial ventilation: impact of early stopping.

Indoor air temperature prediction can facilitate energy-saving actions without compromising the indoor thermal comfort of occupants. The aim of this study was to analyse the performance of various artificial neural networks with a view to proposing an optimal approach for predicting the indoor temperature of a tertiary building with artificial ventilation. The MLP, CNN, LSTM models and the CNN-LSTM combination (long short-term memory network) were used and coupled with the optimisation algorithms (Adam, SGD) and the independent hyper-parameters early stopping and dropout. The parameters used are outdoor ambient temperature, outdoor relative humidity, indoor relative humidity, wet bulb temperature, black globe temperature and mean radiant temperature. The data is collected in an artificially ventilated building in Yaoundé, Cameroon. A numerical code was developed in Python to run the simulations. In order to study the impact of the parameters on the prediction, two scenarios were distinguished in this work: (1) all the parameters are input to the network, (2) only the parameters whose absolute value of the correlation coefficient was greater than or equal to 0.5 were used. The impact of early stopping is assessed by distinguishing two case studies: the first without early stopping, the second with early stopping. The results showed that without early stopping, the MLP, CNN, LSTM and CNN-LSTM networks are adequate for predicting the temperature with the second scenario, mainly with both the SGD and Adam algorithms, and CNN-LSTM is the most appropriate model because the MSE and MAE values obtained in this case were closer to 0. With early stopping, the learning time is reduced and the learning curves are improved; the models optimised better with the SGD algorithm in general, but the best neural network model was obtained with the Adam algorithm and the LSTM network for the performances MSE=0.0005, MAE=0.0130 with the second scenario.Keywords: prediction, indoor temperature, artificial neural network, early stopping, artificially ventilated building.

opencc-zeroNov 2023View details →

Data from: Quantifying the impacts of management and herbicide resistance on regional plant population dynamics in the face of missing data

A key challenge in the management of populations is to quantify the impact of interven-tions in the face of environmental and phenotypic variability. However, accurate estima-tion of the effects of management and environment, in large-scale ecological research is often limited by the expense of data collection, the inherent trade-off between quality and quantity, and missing data. In this paper we develop a novel modelling framework, and demographically informed imputation scheme, to comprehensively account for the uncertainty generated by miss-ing population, management, and herbicide resistance data. Using this framework and a large dataset (178 sites over 3 years) on the densities of a destructive arable weed (Alo-pecurus myosuroides) we investigate the effects of environment, management, and evolved herbicide resistance, on weed population dynamics. In this study we quantify the marginal effects of a suite of common management prac-tices, including cropping, cultivation, and herbicide pressure, and evolved herbicide re-sistance, on weed population dynamics. Using this framework, we provide the first empirically backed demonstration that herbi-cide resistance is a key driver of population dynamics in arable weeds at regional scales. Whilst cultivation type had minimal impact on weed density, crop rotation, and earlier cultivation and drill dates consistently reduced infestation severity. Synthesis and applications: As we demonstrate that high herbicide resistance levels can produce extremely severe weed infestations, monitoring of herbicide resistance is a pri-ority for famers across western Europe. Furthermore, developing non chemical control methods is essential to control current weed populations, and prevent further resistance evolution. We recommend that planning interventions that center on crop rotation and incorporate spring sewing and cultivation to provide the best reductions in weed densi-ties. More generally, by directly accounting for missing data our framework permits the analysis of management practices with data that would otherwise be severely compro-mised.

opencc-by-4.0Nov 2023View details →

3D and multimodal X-ray microscopy reveals the impact of voids in CIGS solar cells

Data repository for the article "3D and multimodal X-ray microscopy reveals the impact of voids in CIGS solar cells"  DOI: 10.1002/advs.202301873

opencc-by-4.0Nov 2023View details →

Authigenic carbonate burial within the Late Devonian Western Canada Sedimentary Basin and its impact on the global carbon cycle

The complete dataset for the research project entitled Authigenic carbonate burial within the Late Devonian Western Canada Sedimentary Basin and its impact on the global carbon cycle. Within this zip file includes an excel file compiling a list of rock samples and their corresponding stable carbon and oxygen isotope compositions as well as their inorganic carbon content. Rock samples are grouped according to formation name, depositional environment and stratigraphic height. Along with the excel data compilation are two supplementary figures meant to accompany the publication of this research.  Figure S1 illustrates coulometry-measured inorganic carbon content of shale samples plotted with respect to their respective IRMS beam area. Figure S2 illustrates a rolling window analysis of the covariability between the d13C and d18O composition of each sample grouped according to their respective core and field sections. A window size of 20 samples was used.

Dataset for "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling

This dataset allows the user to reproduce figures from the journal article "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling.

Interacting impacts of hydrological changes and air temperature warming on lake temperatures highlight the potential for adaptive management: Model output

This archive includes the output from the General Ocean Turbulence Model for a series of simulations that used differing model drivers (inflow discharge, Q, and air temperature, T).  The Experiment_output.zip contains text files generated from the GOTM workflow containing modelled water temperatures and the Mod_z.txt are the corresponding depths for these temperatures. The file name corresponds to the change made to the driving data from baseline (unchanged conditions), a combination of air temperature increase and flow percentage change e.g. Mod_temp_T_2_Q_1.5 refers to an air temperature increase of 2 degrees Celsius and a flow increase of 50% and a Mod_temp_T_3.5_Q_0.7 refers to an air temperature increase of 3.5 degrees Celsius and a flow decrease of 30%.

Supporting data for assessing impacts of satellite GPS transmitters on survival, nesting propensity, and nest success of greater sage-grouse

Telemetry technology and data are commonly used to study behavior and demography of wildlife. Satellite-based, global positioning system (GPS) telemetry allows researchers to remotely collect a high volume of fine-resolution animal location data but may also come with hidden costs. For example, recent studies suggested GPS transmitters attached via backpacks may reduce survival of greater sage-grouse (Centrocercus urophasianus) relative to very high frequency (VHF) telemetry transmitters attached via collars. While some evidence suggests GPS backpacks can reduce survival, no studies examined their effects on sage-grouse breeding behavior and success. We compared survival, breeding behavior, and nest success for sage-grouse hens marked with either VHF collars or GPS backpack transmitters in central Idaho, USA. GPS backpacks reduced spring-summer survival relative to VHF collars, yet GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation relative to VHF collars. Daily nest survival varied annually and with timing of nest initiation and nest age, but marginal effects of transmitter type were statistically insignificant, and interactions between transmitter type and study year were inconsistent. These results demonstrate the effect of GPS backpacks on sage-grouse survival but also suggest GPS backpacks do not appear to affect components of fecundity.

Data and code for: Does increasing temperature accentuate disease impacts on fisheries species? A meta-analysis

Rapid warming could drastically alter host-parasite relationships, which is especially important for fisheries crucial to human nutrition and economic livelihoods; yet we lack a synthetic understanding of how warming influences parasite-induced mortality in these systems. We conducted a meta-analysis using 301 effect sizes from 60 empirical papers on harvested aquatic species and determined the relationship between parasite-induced host mortality and temperature and how this relationship was altered by host, parasite and study design traits. Overall, temperature increased parasite-induced host mortality; however, the magnitude and sometimes direction of this relationship varied. Hosts from the order Salmoniformes experienced a greater increase in parasite-induced mortality with temperature than average. Opportunistic parasites were correlated with a greater increase in host mortality with temperature than average, while bacterial parasite-induced mortality was lower than average as temperature increased. Thus, parasites will generally increase host mortality as the environment warms; however, this effect will vary among systems.

Centennial deforestation impacts on soil phosphorus cycling in the Amazon rainforest

Deforestation of tropical rainforests is a major land use change that alters terrestrial biogeochemical cycling at local to global scales. Deforestation and subsequent reforestation are likely to impact soil phosphorus (P) cycling, which in P-limited ecosystems such as in the Amazon basin has implications for long-term land use change and productivity. We used a 100-year observational chronosequence of primary forest conversion to pasture, as well as a 13-year-old secondary forest, to test land use change and duration effects on soil P dynamics in the Amazon basin. By combining sequential extraction and P K-edge X-ray absorption near edge structure (XANES) spectroscopy with soil phosphatase assays, we assessed pools and process rates of P cycling in surface soils. Deforestation caused increases in total P (135-398 mg kg-1), total organic P (Po) (19-168 mg kg-1), and total inorganic P (Pi) (30-113 mg kg-1) fractions in surface soils with pasture age, with concomitant increases in Pi fractions corroborated by sequential fractionation and XANES spectroscopy. Soil non-labile Po (10-148 mg kg-1) increased disproportionately compared to labile Po (from 4-5 to 7-13 mg kg-1). Soil phosphomonoesterase and phosphodiesterase binding affinity (Km) decreased while the specificity constant (Ka) increased by 83-159% in 39–100y pastures. Soil P pools and process rates reverted to magnitudes similar to primary forests within 13 years of pasture abandonment, though the relatively short but representative pre-abandonment pasture duration of our secondary forest may not enable significant deforestation effects on soil P cycling, highlighting the need to consider both pasture duration and reforestation age in evaluations of Amazon land use legacies. Although the space-for-time substitution design can entail variation in the initial soil P pools due to atmospheric P deposition, soil properties, and/or primary forest growth, the trend of P pools and process rates with pasture age still provides valuable insights.

Identifying climate impacts from different stratospheric aerosol injection strategies in UKESM1

Data to plot figures in Identifying climate impacts from different stratospheric aerosol injection strategies in UKESM1 - Wells et al., 2023

Replication data and code for "The Spatiotemporal Pattern of Surface Ozone and Its Impact on Agricultural Productivity in China"

This dataset contains code and data to replicate the results for "The Spatiotemporal Pattern of Surface Ozone and Its Impact on Agricultural Productivity in China" by Xiaoguang Chen, Jing Gao, Luoye Chen, Madhu Khanna, Binlei Gong, and Maximilian Auffhammer.

Dataset from "Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy"

The dataset presented below is described in the paper "Impact of rain-on-snow events on snowpack structure and runoff under a boreal canopy" by Bouchard et al. (submitted in December 2023) in the journal The Cryosphere.The original dataset includes sub-canopy snow monitoring data collected at the Montmorency Forest site (MF; 47.29°N, 71.17°W, elev. » 850 m above mean sea level (AMSL)) from 2018 to 2023 and at the Bernard River Valley site (BRV; 50.91°N; 63.37°W, elev. » 250 m. AMSL) from 2019 to 2023. MF is a balsam fir-white birch stand on a 12° northeast-facing slope. BRV is a valley surrounded by plateaus 200 m higher. The dataset covers the period from October 15 to June 15 of each year. In the monitoring dataset you can find the hourly time step:<ul><li>Snow height (cm) – all years at both sites</li><li>Soil-snow interface temperature (°C) – 2020 to 2023 at both sites</li><li>Snow temperature every 15 cm from the ground surface (°C) – 2020 to 2023 at both sites</li><li>Snow surface temperature (°C) – 2018-19 and from 2020 to 2023 at MF site</li><li>Air temperature (°C) – 2020 to 2023 at both sites</li></ul>The dataset also includes a total of 48 sub-canopy snow pit observations taken at the MF (42 snow pits) and BRV (6 snow pits) sites during the study period. Each snow pit contains the vertical profile of snow stratigraphy (grain type) and snow density. The snow pit height corresponds to the upper limit of the top snow layer in the stratigraphic profile. For density measurements, the height value corresponds to the center of the 3 cm thick box cutter. Grain type codes for the snowpack stratigraphy correspond to the International Classification for Seasonal Snow (Fierz et al., 2009):<ul><li>PP: precipitation particles</li><li>DF: decomposed and fragmented precipitation particles</li><li>RG: rounded grains</li><li>FC: faceted crystals</li><li>FCxr: rounding faceted particles</li><li>DH: depth hoar</li><li>MFpc: melt forms – rounded polycrystals</li><li>MF: melt forms – clustered rounded grains</li><li>MFcr: melt forms – melt-freeze crusts</li><li>IF: ice formations</li></ul>Finally, the dataset includes all observed rain-on-snow (ROS) events at both sites from November to March, covering the period 2018-2023 at the MF site and the period 2019-2023 at the BRV site. In the ROS dataset, we present the start and end dates, as well as the duration, rainfall amount, and mean air temperature of each event.

Data for "Impact of Arctic stratospheric polar vortex on the Mediterranean precipitation" by Zhang et al., submitted to JC, 2023.

A detailed description of variables and model setup can be found in "Description of variables and model setup.txt"

Global Regionalized Characterization Factors for Phosphorus and Nitrogen Impacts on Freshwater Fish Biodiversity

Overview and guidance for using the data in "CFs_freshwater_eutrophication" related to the article "Global Regionalized Characterization Factors for Phosphorus and Nitrogen Impacts on Freshwater Fish Biodiversity"   See the "readme_CFs_freshwater_eutrophication.pdf" file to find the details of the enclosed data.   Units <ul> <li>Phosphorus from direct emissions to freshwater or diffuse sources on the soil: PDF·year/kgP</li> <li>Nitrogen from direct emissions to freshwater or diffuse sources on the soil: PDF·year/kgN</li> <li>Erosion: PDF·year/(m2·year)</li> </ul> Please excuse any typos in the units in the xlsx files.

Test results from quasi-static impact tests over SMC materials reinforced with glass fibre (ramdom and textile)

Test results from quasi-static impact tests over SMC materials with structural properties conceived for automotive applications, reinforced with glass fibre (samples with ramdom distribution of fibres and samples reinforced with GF textile)

Strategic Environmental Messaging: Identifying the Most Impactful Communication Characteristics Through Cluster Analysis

Datasets for study 1 & 2 for the manuscript Strategic Environmental Messaging: Identifying the Most Impactful Communication Characteristics Through Cluster Analysis

Data For "Impact of dust and temperature on primary productivity in Late Miocene oceans"

Impact of dust and temperature on primary productivity in Late Miocene oceans   This dataset contains marine biogeochemical outputs (NetCDF files) from modeling experiments with realistic late Miocene paleogeography, different CO2 levels and dust concentrations. The simulations focus on the evolution of primary productivity in response to aridification and global cooling. The simulations were carried out using the IPSL-CM5A2 general circulation model (Sepulchre et al. 2020 - IPSL-CM5A2 - an Earth system model designed for multimillennial climate simulations, GMD) and the PISCES-v2 biogeochemistry model (Aumont et al. 2015). It includes four simulations: Mio300Dust (300 ppm, dust concentration equal to pre-industrial level), Mio420Dust2 (420 ppm, dust concentration equal to pre-industrial level divided by 2), Mio420Dust10 (420 ppm, dust concentration equal to pre-industrial level divided by 10) and Mio420NoDust (420 ppm, dust concentration equal to pre-industrial level divided by 1000). The data are monthly averages over the last 100 years of the simulations.   Contact: quentin.pillot@gmail.com   Experiments , see Pillot et al. (2024), Methods ans supplementary Informations for details.   INTPP : Vertically integrated primary production by phyto (mol/m2/s) EPC100 : Export of carbon particles at 100 m (mol/m2/s) LNlight : Light limitation term in Nanophyto (between 0 and 1) LNnut : Nutrient limitation term in Nanophyto (between 0 and 1) PPPHY : Primary production of nanophyto (mol/m3/s) PPPHY2 : Primary production of diatoms (mol/m3/s) Ndep : Nitrogen deposition from dust (mol/m2/s) Pdep : Phosphorus deposition from dust (mol/m2/s) Sidep : Silice deposition from dust (mol/m2/s) Irondep : Iron deposition from dust (mol/m2/s)   Keywords: Late Miocene, marine primary productivity, aridification, dust, CO2, cooling, oceans, modelling, IPSL-CM5A2, PISCES-v2

Season-specific impacts of climate change on canopy-forming seaweed communities

Understory assemblages associated with canopy-forming species such as trees, kelps, and rockweeds should respond strongly to climate stressors due to strong interaction strengths. Climate change can directly and indirectly modify these assemblages, particularly during more stressful seasons and climate scenarios. However, fully understanding the seasonal impacts of different climate conditions on canopy-reliant assemblages is difficult due to a continued emphasis on studying single species responses to a single future climate scenario during a single season. To examine these more complex interactions, we used mesocosm experiments to expose intertidal assemblages associated with the canopy-forming golden rockweed, Silvetia compressa, to elevated temperature and pCO2 conditions reflecting two projected greenhouse emission scenarios [RCP 2.6 (low) & RCP 4.5 (moderate)]. Assemblages were grown in the presence and absence of Silvetia, and in two seasons. Relative to ambient conditions, predicted climate scenarios generally suppressed Silvetia biomass and photosynthetic efficiency. However, these effects varied seasonally - both future scenarios reduced Silvetia biomass in summer, but only the moderate scenario did so in winter. These reductions shifted the assemblage, with more extreme shifts occurring in summer. Contrarily, future scenarios did not shift assemblages within Silvetia Absent treatments, suggesting that climate primarily affected assemblages indirectly through changes in Silvetia. Mesocosm experiments were coupled with a field Silvetia-removal experiment to simulate the effects of climate-mediated Silvetia loss on natural assemblages. Consistent with the mesocosm experiment, Silvetia loss resulted in season-specific assemblage shifts, with weaker effects observed in winter. Together, our study supports the hypotheses that climate-mediated changes to canopy-forming species can indirectly affect the associated assemblage, and that these effects vary seasonally. Such seasonality is important to consider as it may provide periods of recovery when conditions are less stressful, especially if we can reduce the severity of future climate scenarios.