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opencc-zeroNov 2021View details →

Temporal biodiversity change following disturbance varies along an environmental gradient

Aim The diversity and composition of natural communities are rapidly changing due to anthropogenic disturbances. Magnitude of this compositional reorganization varies across the globe, but reasons behind the variation remain largely unknown. Disturbances induce temporal turnover by stimulating species colonizations, causing local extinctions, altering dominance structure, or all of these. We test which of these processes drive temporal community changes, and whether they are constrained by natural environmental gradients. Moreover, we assess to what degree identity shifts translate to changes in dominance structure. Location Finland Time period Observations 1985-2006, disturbance history >140 years. Major taxa studied Vascular plants. Methods We investigated temporal turnover of boreal forest understory in response to disturbance, here forest management, along a soil fertility gradient. We disentangle the roles of species gains, losses and abundance changes in driving temporal turnover in response to and after disturbance by comparing turnover rates in different forest age categories along fertility gradient. We quantify temporal turnover richness-based complement of Jaccard's similarity index and proportional-abundance based dissimilarity index. We also test whether disturbance history or fertility influence the relationship between identity shifts and dominance structure. Results We found that the impact of disturbance on temporal turnover depends on soil fertility. The greatest turnover occurred in most fertile forests immediately after disturbance. There, species gains and losses strongly altered dominance structure leading to high turnover, whereas undisturbed old forests and nutrient-poor habitats were characterized by stable dominant species even when the majority of species shifted their identity. Main conclusions Our results suggest that human impacts on temporal biodiversity change vary along environmental gradients. In boreal forests, the fertile habitats have higher probability than nutrient-poor sites to change their composition in response to anthropogenic disturbances. Resource availability and disturbance history may thus influence consequences of temporal turnover for ecosystem functioning.

opencc-by-4.0Oct 2021View details →

Event-based hyperspectral EELS: towards nanosecond temporal resolution

Here we present the two data sets presented in the work <a href="https://arxiv.org/abs/2110.01706">Event-based hyperspectral EELS: towards nanosecond temporal resolution</a>. Data was processed using Rust. In ASI Cheetah Timepix3, we have two different kinds of events: electron and TDC events (little-endian). Data chunk package is a 8-byte data that begins with "TPX3". Electron hit is a 8-byte packet that contains "0xb" in 60-63 bits. TDC data packet is a 8-byte packet that contains "0x6" in 60-63 bits. 56-59 bits identify if it is comes from TDC Line 1 or 2 and also identifies if it is a falling or a rising edge.

opencc-by-4.0Oct 2021View details →

Replication data for: Spatial and temporal origins of the La Perouse low oxygen pool: A combined Lagrangian statistical approach

This dataset contains: a) NEP36 daily Model (NEMO) Output from 20130228 till 20131005 in NetCDF format, b) Moving Vessel Profiler (MVP) Survey data gathered onboard the R/V Falkor during August 2013 in ASCII .mat files, c) Files required to initialize and run Lagrangian Particle tracking model ARIANE i.e. one mesh_mask file in netCDF format and one text file containing initial positions based on the Eulerian grid of the sliced NEP36 model d) the output files from running the particle tracking model ARIANE in NetCDF format

opencc-zeroOct 2021View details →

Temporal patterns of visitation of birds and mammals at mineral licks in the Peruvian Amazon

Mineral licks are key ecological resources for many species of birds and mammals in Amazonia, providing essential dietary nutrients and clays, yet little is known about which species visit and their behaviors at the mineral licks. Studying visitation and behavior at mineral licks can provide insight into the lives of otherwise secretive and elusive species. We assessed which species visited mineral licks, when they visited, and whether visits and the probability of recording groups at mineral licks were seasonal or related to the lunar cycle. We camera trapped at 52 mineral licks in the northeastern Peruvian Amazon and detected 20 mammal and 13 bird species over 6,255 camera nights. Generalized linear models assessed visitation patterns and records of groups in association with seasonality and the lunar cycle. We report nocturnal curassows (Nothocrax urumutum) visiting mineral licks for the first time. We found seasonal trends in visitation for the black agouti (Dasyprocta fuliginosa), red howler monkey (Alouatta seniculus), blue-throated piping guan (Pipile cumanensis), red brocket deer (Mazama americana), collared peccary (Pecari tajacu) and tapir (Tapirus terrestris). Lunar trends in visitation occurred for the paca (Cuniculus paca), Brazilian porcupine (Coendou prehensilis) and red brocket deer. The probability of recording groups (>1 individual) at mineral licks was seasonal and related to lunar brightness for tapir. Overall, our results provide important context for how elusive species of birds and mammals interact with these key ecological resources on a landscape scale. The ecological importance of mineral licks for these species can provide context to seasonal changes in species occupancy and movement.

opencc-by-4.0Jul 2024View details →

Spatio-temporal dynamics of attacks around deaths of wolves: A statistical assessment of lethal control efficiency in France

<h1>Description</h1> This repository contains the supplementary materials (Supplementary_information.pdf, Supplementary_figures.pdf, Supplementary_tables.pdf) of the manuscript: "Spatio-temporal dynamics of attacks around deaths of wolves: A statistical assessment of lethal control efficiency in France". This repository also provides the R codes and datasets necessary to run the analyses described in the manuscript.  <h1>Datasets</h1> We provide the spatially anonymized R datasets to respect confidentiality. Therefore, the preliminary preparation of the data is not provided in the public codes. These datasets, all geolocated and necessary to the analyses, are: <ul> <li>Attack_sf.RData: 19,302 analyzed wolf attacks on sheep     - ID: unique ID of the attack     - DATE: date of the attack     - PASTURE: the related pasture ID from "Pasture_sf" where the attack is located     - STATUS: column resulting from the preparation and the attribution of attacks to pastures (part 2.2.4 of the manuscript); not shown here to respect confidentiality  </li> <li>Pasture_sf.RData: 4987 analyzed pastures grazed by sheep       - ID: unique ID of the pasture     - CODE: Official code in the pastoral census     - FLOCK_SIZE: maximum annual number of sheep grazing in the pasture     - USED_MONTHS: months for which the pasture is grazed by sheep  </li> <li>Removal_sf.RData:  232 analyzed single or multiple wolf removals      - ID: unique ID of the removal     - OVERLAP: are they single removal ("single" in the manuscript => "NO" here), or not ("multiple" in the manuscrit, here "SIMULTANEOUS" for removals occurring during the exact same operation or "NON-SIMULTANEOUS" if not).      - DATE_MIN: date of the single removal or date of the first removal of a group     - DATE_MAX: date of the single removal or date of the last removal of a group     - CLASS: administrative type of the removal according to definitions from 2.1 part of the manuscript     - SEX: sex of the removed wolves if known     - AGE: class age of the removed wolves if known     - BREEDER: breeding status of the removed female wolves, "Yes" for female breeder, "No" for female non-breeder. Males are "No" by default, when necropsied; dead individuals with NA were not found.      - SEASON: season of the removal, as defined in part 2.3.4 of the manuscript     - MASSIF: mountain range attributed to the removal, as defined in part 2.3.4 of the manuscript  </li> <li>Mountain_range_buff_sf.RData: one row for each mountain range, corresponding to the buffered mountain ranges where removal control events could be sampled, as defined in part 2.3.3 of the manuscript   </li> <li>Area_to_exclude_sf.RData: one row for each mountain range, corresponding to the area too close from other mountain ranges, terrestrial and maritime limits, where removal control events could not be sampled, as defined in part 2.3.3 of the manuscript </li> <li>Overlapping_removal_sf.RData corresponds to the spatial dataset necessary to run the supplementary figures about overlapping removals (S9)  </li> </ul> You can also find the object called Subset_lt.RData, which gives the ID of removals for each dataset (single/multiple removals) or subsets of single removals.   The other RData resulted from the analysis. How to read their names:   <ul> <li>First part:        - Buffer: they link the attacks to removals or of control events.       - Kernel: they give the results of the kernel density estimation (z), according to the spatial (y) and temporal (x) coordinates, for each dataset.   - Int: they give, for each distance and time, the total amount of attack intensities before (INT_BEF) and after (INT_AFT) the combined locations and days of removals or control events. 1 unit of distance = 50 meters, 1 unit of time = 1 day.   - Trend: they give, for each distance and time, the trends in % of the attack intensities when comparing before and after, with their uncertainties and significance. Files with spatshift are designed for figures about spatial shift (unnested scales), contrary to files without spatshift (nested scales).  </li> <li>Middle parts: (noted with an X after)       - obs: results from removals     - jack: results from jackknife samples of the removals    - ctl: results related to control sets     - cor: results corrected for livestock presence   - raw: results uncorrected for livestock presence   - sim: results for simulated attacks according to livestock presence  </li> </ul> Lengths of lists or sublists correspond to:   - 20 elements: the two main datasets (single/multiple) and the 18 subsets of single removals.  - 100 elements: the 100 control sets.     - 1000 elements: the 1000 simulations of attacks (for the livestock presence correction).    - Other lengths and jack within the name: the jackknife samples.       <h1>Structure of the repository</h1> <h2>Code 1: file Buffer.R      </h2> We keep only removals within geographic zones for the analysis (Removal_analyzed_sf), and sample their control events (100 simulations = control sets, Removal_ctl_sf_lt). We start by delimiting the spatio-temporal buffer for each row of the removal and control datasets.        - We identify the attacks from Attack_sf.RData within each buffer, thanks to the function Buffer_fn, giving the data frames Buffer_X_df (one row per attack)       - We select the pastures from Pasture_sf.RData within each buffer, thanks to the function Buffer_pasture_fn, giving the data frames Buffer_X_sf (one row per removal or control event)   We calculate the spatial correction:       - We spatially slice each buffer into 200 rings with the function Ring_fn, giving the data frame Ring_sf (one row per ring)       - We add the total pastoral area of the ring of the attack ("SPATIAL_WEIGHT") with the function Spatial_correction_fn, for each attack of each buffer, within Buffer_X_df    We calculate the pastoral correction:       - We create the pastoral matrix for each removal or control event with the function Pastoral_matrix_fn, giving a matrix of 200 rows (one for each ring) and 180 columns (one for each day, 90 days before the removal date and 90 day after the removal date), with the total pastoral area in use by sheep for each corresponding cell of the matrix (one element per removal, Pastoral_X_mx_lt.RData)       - We simulate, for each removal or control event, the random distribution of the attacks from Buffer_X_df.RData according to Pastoral_X_mx_lt.RData with the function Buffer_sim_fn. The process is done 1000 times (one element per simulation, Buffer_X_sim_lt.RData).    <h2>Code 2: file Kernel.R where we estimate the attack intensities  </h2> We classified the removals into 2 main datasets and 18 subsets, according to part 2.3.4 of the manuscript (Subset_lt.RData) (one element per set). We compute the jackknife samples for each dataset or subset (Removal_id_jack_lt).   We perform the kernel estimations with the function Kernel_fn (Kernel_X_lt).   We sum the intensities of attacks before and after the removals or control events, with the function Intensity_fn, giving Int_X_df_lt.RData.    <h2>Code 3: file Trend.R where we calculate the trends of attack intensities after removals </h2>  We focus on the nested trends first:       - We calculate them (Trend_X_df) with function Trend_fn      - We set the result significance test by observing the overlapping of confidence intervals of removals and control sets (Trend_X_comparison_df)   We focus on the spatial shifts (trends for each specific distance):     - We calculate them (Trend_X_spatshift_df) with function Trend_fn       - We set the result significance test by observing the overlapping of confidence intervals of removals and control sets (Trend_X_comparison_spatshift_df)   <h2>- Code 4: file Functions.R where can be found all custom functions called in the other analysis codes   </h2> <h2>- Code 5: file Figures.R produces part of the figures from the manuscript</h2> Detailed comments are included in each code. <h1>Support</h1> If you have any question or request, do not hesitate to contact us at: oksana.grente@gmail.com <h1>Authors and acknowledgment</h1> Grente Oksana (CEFE, CNRS), Opitz Thomas (INRAE), Duchamp Christophe (OFB), Drouet-Hoguet Nolwenn (OFB), Chamaillé-Jammes Simon (CEFE, CNRS) and Gimenez Olivier (CEFE, CNRS).   <h1>License</h1> GNU GENERAL PUBLIC LICENSE 3.0

opencc-zeroOct 2022View details →

Temporal structure of two call types produced by competing male cicadas

We investigated the behavior of Meimuna oparifera, which utilize two types of calls at close range. The calls were recorded multiple times with different pairs of cicadas. This data includes the type, onset and end of each call. Utilizing this data, you can quantify how M. opalifera responded to the calls of another male by calculating a phase difference.

opencc-zeroNov 2022View details →

Divergent response and adaptation of specific leaf area to environmental change at different spatio-temporal scales jointly improve plant survival

Specific leaf area (SLA) is one of the most important plant functional traits. It integrates multiple functions and reflects strategies of plants to obtain resources. How plants employ different strategies (e.g., through SLA) to respond to dynamic environmental conditions remains poorly understood.This study aimed to explore the spatial variation in SLA and divergent adaptation of plants by changing SLA through the lens of biogeographic patterns, evolutionary history, and short-term responses. SLA data for 5424 plant species from 76 natural communities in China were systematically measured and integrated with meta-analysis of field experiments (i.e., global warming, drought, and nitrogen addition). The mean value of SLA across all species was 21.8 m2 kg–1, ranging from 0.9 to 110.2 m2 kg–1. SLA differed among different ecosystems, temperature zones, vegetation types, and functional groups. Phylogeny had a weak effect on SLA, but plant species evolved toward higher SLA. Furthermore, plants responded nonlinearly to environmental change by changing SLA. Unexpectedly, radiation was one of the main factors determining the spatial variation in SLA on a large scale. Conversely, short-term manipulative experiments showed that SLA increased with increased resource availability and tended to stabilize with treatment duration. However, different species exhibited varying response patterns. Overall, long-term adaptation of plants to environmental gradients and its short-term response to resource pulses through variation in SLA jointly improve plant adaptability to a changing environment. Overall SLA-environment relationships should be emphasized as a multidimensional strategy for elucidating environmental change in future research.

opencc-zeroNov 2022View details →

Fine-scale temporal dynamics of flower visitors sheds light on the pollination strategy of a dioecious palm in the Ecuadorian Andes

Background: Dioecious plants generally display sexual dimorphism in male and female floral traits, potentially attracting slightly different pollinator communities. The sharing of common floral visitors between male and female flowers and their timing of visits to both sexes is of critical importance to ensure plant's reproductive success. Palm inflorescences are visited by abundant and diverse insect communities, yet the temporal patterns of insect visits on both sexes remain poorly known. Results: We report 59 morphospecies in the arthropod community, dominated by three beetle families: Staphylinidae, Nitidulidae and Curculionidae. Male inflorescences were more abundantly visited than female, but visitors of the later were taxonomically more diverse. Among the 16 pollinator candidates identified, 9 visited both inflorescence sexes synchronously at dusk /night whereas the others did so asynchronously during the day. Conclusion: Our study provides new insights into the pollination mechanism of P. aequatorialis. We found evidence of differential pollinator attraction between floral sexes, which may be explained by the sexual dimorphism of both flowers. Synchronicity in dusk/night visits of both inflorescence sexes suggests a sexual synchronization of the signal used to attract pollinators.

opencc-zeroNov 2022View details →

Contrasting intra-annual population dynamics of two codominant species are consistent across spatial and temporal scales

1. Despite asymmetric competition and a wide array of functional similarities, two ecologically important C4 perennial grasses, Andropogon gerardii and Sorghastrum nutans, frequently codominate areas of the mesic tallgrass prairie of the US Great Plains. A subtle difference in their vegetative reproduction strategies may play a role in preventing exclusion of S. nutans, the presumed weaker competitor in this region. 2. While A. gerardii vegetative tiller densities peak in the early growing season and decline thereafter (determinate recruitment), those of S. nutans may continue to increase throughout the growing season (indeterminate recruitment), providing a potential avenue for recovery from more intensive early season competition. However, until now these patterns have only been informally observed in the field. 3. We examined the year-to-year consistency of growing season vegetative tiller dynamics (measured as seasonal change in tiller densities) of each grass species from at an intact tallgrass prairie in Kansas - a site within the core of both species' distributions - over a period of 8 years. Then, to investigate environmental effects on these dynamics, we examined whether they differ across a Kansas landscape varying in topography, fire management regimes and the abundances of the study species. Finally, we expanded the investigation of environmental effects on growing season tiller dynamics by observing them at the periphery of the species' distributions in central Colorado, where climatic conditions are dryer and the study species' abundances are reduced. 4. Synthesis: We found that the tiller densities of A. gerardii decline within seasons with striking consistency regardless of spatio-temporal scale or environmental factors (topography and fire regimes). In contrast, we found the seasonal dynamics of S. nutans tiller densities were dependent on environmental factors, with seasonal tiller density increases occurring only within the Kansas populations but not consistently between years. These observations lay the groundwork for establishing differences in tiller recruitment determinacy as a potentially important yet underappreciated mechanism for promoting coexistence and codominance among perennial plant species.

Data from: Temporal change in floral availability leads to periods of resource limitation and affects diet specificity in a generalist pollinator

Generalist species are core components of ecological networks and crucial for the maintenance of biodiversity. Generalised species and networks are expected to be more resilient, therefore understanding the dynamics of specialisation and generalisation in ecological networks is a key focus in a time of rapid global climate change. Whilst diet generalisation is frequently studied, our understanding of how it changes over time is limited. We explore temporal variation in diet specificity in the honeybee (Apis mellifera), using pollen DNA metabarcoding of honey samples, through the foraging season, over two years. We find that overall, honeybees are generalists that visit a wide range of plants, but there is temporal variation in the degree of specialisation. Temporal specialisation of honeybee colonies corresponds to periods of resource limitation, identified as a lack of honey stores. Honeybees experience a lack of preferred resources in June when switching from flowering trees in spring to shrubs and herbs in summer. Investigating temporal patterns in specialisation can identify periods of resource limitation that may lead to species and network vulnerability. Diet specificity must therefore be explored at different temporal scales in order to fully understand species and network stability in the face of ecological change.

Tracing pathways from high-resolution tractography, transcription, and temporal dimensions

The neural circuits supporting human cognition are topics of enduring interest. The lack of tools available to map circuits has precluded our ability to trace the evolution of the human connectome. We harnessed high-resolution connectomic, anatomic, and transcriptomic data to develop enhanced tools to test for modifications in developmental programs across species. We found corresponding ages across species and transcriptionally define neurons with stereotypical projections in humans and macaques. We used these data to test for modifications in frontal cortex circuit. Frontal cortex circuitry development is extended in primates, which is concomitant with an expansion in cortico-cortical pathways compared with mice in adulthood. These parameters varied little across humans and macaques. We identify a collection of conserved features in frontal cortex circuits in studied primates. We demonstrate that the integration of transcriptional and connectomic data across temporal dimensions is a robust approach to trace the evolution of connections in primates. This dataset contains scripts as well as diffusion MR scans of mouse brains.

opencc-by-4.0Dec 2022View details →

Data in support of "Antarctic Bottom Water sensitivity to spatio-temporal variations in Antarctic meltwater fluxes"

This data contains the unprocessed output from the five equilibrium  simulations used in the paper "Antarctic Bottom Water sensitivity to spatio-temporal variations in Antarctic meltwater fluxes".  Simulations were run using the ocean and sea-ice components of CESM1, and the atmosphere was data-driven, and based on ERA5 reanalysis from 1958 until 1980. All data is in netcdf, and includes the description of flag values, and units. The five simulations differ in the freshwater flux scheme as described below: Simulation UNIF - files: ga1.f09_g16.308 Forced with freshwater fluxes from the Antarctic Ice Sheet (AIS), uniformly distributed around the Antarctic coast. Total freshwater flux from AIS: 2075 Gt/yr Simulation BM - files: ga1.f09_g16.208 Forced with asymmetric zonal freshwater fluxes from the AIS. Total freshwater flux from AIS: 2075 Gt/yr Simulation VARI - files: ga1.f09_g16.108 Forced with asymmetric zonal and meridional freshwater fluxes from the AIS. Total freshwater flux from AIS: 2075 Gt/yr Simulation CV - files: ga1.f09_g16.408 Forced with asymmetric meridional freshwater fluxes from the AIS, to mimic iceberg melting. Total freshwater flux from AIS: 934 Gt/yr Simulation VARI120% - files: ga1.f09_g16.x18 Same as VARI, but the total freshwater fluxes were increased by 20%. Total freshwater flux from AIS: 2490 Gt/yr     [30S 90S] , [180W 180E]   Variables: Ocean Temperature [Celius], Salinity [PSU], Sea ice Fraction [fraction], Salt flux from sea ice [kg/m2/s], and ocean overturning [SV] For more information, check:<a href="https://doi.org/10.1002/essoar.10512610.1">https://doi.org/10.1002/essoar.10512610.1</a>

Data from: Two for the price of one: eDNA metabarcoding reveals temporal and spatial variability of mussel and fish co-distributions in Michigan riverine systems

Freshwater mussels (family Unionidae) are among the world's most endangered taxa, with almost 75% of North American taxa classified as a species of concern, threatened, or endangered. Despite the critical importance of comprehensive distributional data for the conservation of unionids and fishes, these data are often lacking because of the labor and resources associated with traditional survey methods. During their larval stage, unionid mussels use various fish species as obligate hosts, making native fish species vital to unionid persistence and an understanding of host distribution similarly important. Here, we utilized an eDNA metabarcoding approach to evaluate patterns of co-distribution of unionid mussels and fishes along ~362 km of the densely sampled Grand River network as well as the outlets of 19 tributaries along the eastern shore of Lake Michigan, USA. We detected a total of 21 mussel and 40 fish taxa, with distinctive composition of both mussel and fish assemblages across tributaries and differences in fish taxa between sampling periods. Notably, we detected more mussel taxa within the Grand River watershed than at the outlets of all 20 rivers combined. Within the Grand River network, two fish taxa (Pylodictus olivaris and Cyprinella) were found more frequently in areas of high mussel diversity, and three fish taxa more frequently in areas of low mussel diversity (Umbra, Leuciscidae, and Etheostoma). There was little difference between eDNA detections of mussels from samples collected in June versus August, but we detected significantly more fish taxa in August compared to June. Taken together, our findings demonstrate the value of eDNA metabarcoding for evaluating co-distribution of ecologically connected taxa. The use of eDNA as a tool for determining distributions of mussels and their obligate hosts may facilitate conservation efforts for these imperiled taxa.

Propagating spatio-temporal activity patterns across macaque motor cortex carry kinematic information

Propagating spatio-temporal neural patterns are widely evident across sensory, motor and association cortical areas. However, it remains unclear whether any characteristics of neural propagation carry information about specific behavioral details. Here, we provide the first evidence for a link between the direction of cortical propagation and specific behavioral features of an upcoming movement on a trial-by-trial basis. We recorded local field potentials (LFPs) from multi-electrode arrays implanted in the primary motor cortex of two rhesus macaque monkeys while they performed a 2-D reach task. Propagating patterns were extracted from the information-rich high-gamma band (200–400Hz) envelopes in the LFP amplitude. We found that the exact direction of propagating patterns varied systematically according to initial movement direction, enabling kinematic predictions. Furthermore, characteristics of these propagation patterns provided additional predictive capability beyond the LFP amplitude themselves, which suggests the value of including mesoscopic spatio-temporal characteristics in refining brain-machine interfaces.

opencc-by-4.0Dec 2022View details →

Optimization Framework for Temporal Interference Current Tibial Nerve Stimulation in Tibial Nerves based on In-Silico Studies

Online Resource 1: All MR-based 3D models and cross-sections. n = 29.   Online Resource 2: Comparison of changes in electrode pairs according to anatomical differences (independent sample t-test for Online Resource 2, *p<0.0001) When Electrode opt TI was applied, the model in which the combination of electrodes was changed relative to Parallel opt TI was referred to as the Change group, and the model that was unaltered was called the Non-change group. In the case of the Change group, PR values increased in Electrode opt compared with those in the Parallel opt group. When comparing the ratio of nerve depth to the total length of the model section, we confirmed the Change group exhibited a smaller ratio. Since the sample size of each group was different, the difference of average in the PR value of each group was evaluated using an independent sample t-test. Purple dots present raw data. Mean and standard deviation of the changes are shown in black.

Data for "From pandemic to endemic: Spatial-temporal patterns of influenza-like-illness incidence in a Swiss canton, 1918-1924"

Datasets underlying the analysis of the paper: "From pandemic to endemic: Spatial-temporal patterns of influenza incidence in a Swiss canton, 1918-1924" <ul> <li>Cofactors_1918.xlsx : Ecological cofactors for each bernese municipility</li> <li>Data_Influenza_Bern.xlsx: Influenza data (1920-1924)</li> <li>Data_Spanishflu.xlsx: "Spanish flu" data (1918-1919)</li> <li>Data_Population.xlsx: Population for each municipality</li> <li>Tb_death.xlsx : Number of tuberculosis death</li> <li>Fabrik_Statistik_1929.xlsx : Information about the factories</li> </ul>

opencc-zeroJan 2023View details →

Data from: Plant attributes interact with fungal pathogens and nitrogen addition to drive soil enzymatic activities and their temporal variation

Nitrogen enrichment can alter soil communities and their functioning directly, via changes in nutrient availability and stoichiometry, or indirectly, by changing plant communities or the abundance of consumers. However, most studies have only focused on one of these potential drivers and we know little about the relative importance of the different mechanisms (changes in nutrient availability, in plant diversity or functional composition, or in consumer abundance) by which nitrogen enrichment affects soil functioning. In addition, soil functions could vary dramatically between seasons, however, they are typically measured only once during the peak growing season. We therefore know little about the drivers of intra-annual stability in soil functioning. In this study, we measured activities of β-glucosidase and acid phosphatase, two extracellular enzymes that indicate soil functioning. We did so in a large grassland experiment which tested the effects, and relative importance, of nitrogen enrichment, plant functional composition and diversity, and foliar pathogen presence (controlled by fungicide) on soil functioning. We measured the activity of the two enzymes across seasons and years to assess the stability and temporal dynamics of soil functioning. Overall β-glucosidase activity was slightly increased by nitrogen enrichment over time but did not respond to the other experimental treatments. Conversely, plant functional diversity, and interactions between plant attributes and fungicide application, were important drivers of mean acid phosphatase activity. The temporal stability of both soil enzymes was differently affected by two facets of plant diversity: species richness increased temporal stability and functional diversity decreased it; however, these effects were dampened when nitrogen and fungicide were added. Synthesis: The fungicide effects on soil enzyme activities suggest that foliar pathogens can also affect belowground processes and the interacting effect of fungicide and plant diversity suggests that these plant enemies can modulate the relationship between plant diversity and ecosystem functioning. The contrasting effects of our treatments on the mean versus stability of soil enzyme activities clearly show the need to consider temporal dynamics in belowground processes, to better understand the responses of soil microbes to environmental changes such as nutrient enrichment.

National High-Resolution Cropland Classification of Japan with Agricultural Census Information and Multi-temporal Multi-modality datasets

Multi-modality datasets offer advantages for processing frameworks with complementary information, particularly for large-scale cropland mapping. Extensive training datasets are required to train machine learning algorithms, which can be challenging to obtain. To alleviate the limitations, we extract the training samples from the agricultural census information. We focus on Japan and demonstrate how agricultural census data in 2015 can map different crop types for the entire country. Due to the lack of Sentinel-2 datasets in 2015, this study utilized Sentinel-1 and Landsat-8 collected across Japan and combined observations into composites for different prefecture periods (monthly, bimonthly, seasonal). Recent deep learning techniques have been investigated the performance of the samples from agricultural census information. Finally, we obtain nine crop types on a countrywide scale (around 31 million parcels) and compare our results to those obtained from agricultural census testing samples as well as those obtained from recent land cover products in Japan. The generated map accurately represents the distribution of crop types across Japan and achieves an overall accuracy of 87% for nine classes in 47 prefectures.

Raw GBIF data used in the article "Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles"

This table contains the raw (unfiltered) species occurrence data for Dianthus sylvestris complied from GBIF. A filtered subset of this data was combined with other data sources to define the input for the species distribution models used in the article "Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles".

Temporal iCLIP captures co-transcriptional RNA-protein interactions

Minimum datasets required to perform analysis using code from github.