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opencc-by-4.0Nov 2020View details →

Database for "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China"

This file contains the dataset accompanying the manuscript '2020EA001232-TR' submitted to the ESS journal (https://earthandspacescience-submit.agu.org). Title: "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China" China Merged Precipitation Analysis data (CMPA, hourly, with the resolution of , as validation data) for China Mainland is available at website http://data.cma.cn. Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrieval data (IMERG, half-hourly, with the resolution of , as the observed data) is available at https://pmm.nasa.gov/data-access/downloads/gpm. The Shuttle Radar Topography Mission data (SRTM, with a 90-m spatial resolution) could be accessed at http://srtm.csi.cgiar.org.

Fig. 10 in Patterns of spatio-temporal distribution as criteria for the separation of planktic foraminiferal species across the Danian-Selandian transition in Spain

Fig. 10. Lower/higher (L/H) latitude taxa ratio and quantitative stratigraphic distribution of planktic foraminiferal genera across the Danian–Selandian transition at Caravaca. Asterisks indicate climate warming events identified here.

Fig. 9 in Patterns of spatio-temporal distribution as criteria for the separation of planktic foraminiferal species across the Danian-Selandian transition in Spain

Fig. 9. Cluster analyses based on Morisita's index for relative abundance data of species from Caravaca in the Acarinina uncinata Zone (4a) and in the Morozovella cf. albeari Zone (4b); l1 = Simpson's diversity index in sample j; l2 = Simpson's diversity index in sample k; xij = percentage of species i in sample j; xik = percentage of species i in sample k.

Fig. 2 in Patterns of spatio-temporal distribution as criteria for the separation of planktic foraminiferal species across the Danian-Selandian transition in Spain

Fig. 2. Comparison of some planktic foraminiferal zonations proposed for the D–S transition in low and middle latitudes. Correlation with the chronostratigraphic and magnetostratigraphic scales based on data from the Zumaia stratotype. (*) Probable biostratigraphic position of the base of the Igorina pusilla Zone by Toumarkine and Luterbacher (1985), and Canudo and Molina (1992), based on data from Zumaia. (**) Biostratigraphic position of the P3a/P3b boundary by Berggren and Pearson (2005), assuming that their species concept of I. albeari includes Morozovella crosswicksensis by Blow (1979) and Arenillas and Molina (1997) and/or M. cf. albeari by Arenillas et al. (2008). FOD, first occurrence data; L/H, lower/higher latitude, LOD, last occurence data.

Fig. 3 in Patterns of spatio-temporal distribution as criteria for the separation of planktic foraminiferal species across the Danian-Selandian transition in Spain

Fig. 3. Quantitative stratigraphic distribution of planktic foraminiferal species across the Danian–Selandian transition at Caravaca. The shown stratigraphic interval does not include the lower part of the A. uncinata Zone, where Globoconusa species were found (see Arenillas and Molina 1997).

opencc-by-4.0Jul 2020View details →

The influence of human disturbances on the spatio-temporal habitat selection patterns of roe deer near Trento (Italy)

This is the dataset used for the MSc. thesis of Matthijs Hinkamp for the master Earth Sciences (Environmental Management track) at the University of Amsterdam. In this thesis the Individual Movement Sequence Analysis Method (IM-SAM) was applied to analyse the influence of human disturbances on the sequential habitat use of roe deer in northern Italy. While it is known that in this area the roe deer populations are affected by anthropogenic pressures, the actual spatial and temporal implications of such pressures are unknown. The input for IM-SAM consisted of habitat sequences, which were obtained through tracking data from the Fondazione Edmund Mach, land use and land cover maps and temporal information. Based on exploratory dissimilarity trees for the real behavioural sequences, several simulation profiles were established, each with a different habitat use pattern. The results show that most roe deer prefer isolated forest areas, but alternating patterns are definitely present. Several co variables were assessed: the influence of the hunting season, increased pressure during weekends, differences between protected and unprotected areas and changes in the average NDVI. It seems that roe deer are affected by the hunting pressure in September. This month shows an increase in the prevalence of alternating profiles, which indicates that roe deer tend to change their habitat use during periods of the day when hunting takes place. It cannot be concluded that habitat use patterns are altered during the weekends and the differences between sequences in protected and unprotected areas seem to be relatively small. However, some results indicate that alternating habitat use is a strategy for some roe deer in protected areas. When looking at the NDVI values, it becomes clear that the average NDVI is higher overall for the alternating profiles, but this just underlines the general conclusions drawn about the habitat use strategies in September.

opencc-by-4.0Nov 2024View details →

Dataset on Spatial Analysis and Clustering of Deforestation in the Amazon Biome: Spatio-Temporal Patterns and Priority Areas

The dataset was developed with the aim of facilitating the development of a methodology to identify and evaluate deforestation patterns and trends in the Amazon. This innovative method combines deforestation alerts from the Real-Time Deforestation Detection System (DETER) with detailed information on various land categories, including environmental protection areas, settlements, rural properties, undesignated public forests, indigenous lands, and conservation units. The integration of this robust data allowed for the precise identification of areas at risk of deforestation, significantly strengthening monitoring and control activities aimed at combating deforestation in the Amazon region.   Spatial resolution The data are available with a spatial resolution of 25 x 25 km (625 km²) and cover the Amazon biome.   Temporal resolution  Period of observed data: 2017 and 2021   Coordinate reference system  Geographic Coordinate System with Datum SIRGAS 2000 (EPSG:5880)   Data format Data is provided as Shapefile.   Dataset usage  It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset.   Publication & further information For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com).

opencc-zeroAug 2022View details →

Predicting spatio-temporal population patterns of Borrelia burgdorferi, the Lyme disease pathogen

The causative bacterium of Lyme disease, Borrelia burgdorferi, expanded from an undetected human pathogen into the etiologic agent of the most common vector-borne disease in the United States over the last several decades. Systematic field collections of the tick vector reveal increases in the geographic range and population size of B. burgdorferi that coincided with increases in human Lyme disease incidence across New York State. Here we investigate the impact of environmental features on the population dynamics of B. burgdorferi. Analytical models developed using field collections of nearly 19,000 nymphal Ixodes scapularis and spatially- and temporally-explicit environmental features accurately explained the variation of B. burgdorferi population sizes across space and time. Importantly, the model identified environmental features that can be used to predict the biogeographical patterns of B. burgdorferi-infected ticks into future years and in previously unsampled areas. Forecasting the distribution and abundance of a pathogen at fine geographic scales offers a powerful strategy to mitigate a serious public health threat.

opencc-zeroOct 2022View details →

Spatio-temporal variation in deep soil water use patterns of overstory and understory layers in subtropical plantations predict community assembly

1. Deep soil water utilization allows plants to cope with drought stress. However, little is known about the roles of the understory layers in driving spatio-temporal variations of deep soil water in forests and how the patterns of deep soil water use among life forms contribute to community assembly processes. 2. We assessed the spatio-temporal patterns and determinants of deep water utilization of tree, shrub and herb layers in subtropical coniferous plantations and investigated associations between deep water use parameters and dominance and richness of understory vegetation. 3. We found that the understory layer had a higher reliance on deep soil water in the dry season, a larger seasonal plasticity of deep soil water uptake, but lower spatial variability in deep soil water utilization than the tree layer. We showed that greater reliance of the tree layer on deep soil water was associated with decreased shrub layer diversity, whereas greater reliance of the shrub layer on deep water was associated with increased herb layer diversity. 4. Synthesis. Our results highlight the roles of understory layers in driving the temporal dynamics of deep soil water in forests and improve our understanding of how deep soil water use patterns amongst life forms shape community assembly in forests.

opencc-by-4.0May 2018View details →

Data from: Individual Movement - Sequence Analysis Method (IM-SAM): characterising spatio-temporal patterns of animal trajectories across scales and landscapes

Dataset included in Zenodo supports the analyses performed in "Individual Movement - Sequence Analysis Methods (IM-SAM) characterising spatio-temporal patterns of animal trajectories across scales and landscapes." The dataset includes one RDS file, that can be easily loaded into R using the readRDS function. The RDS file consists out of a list including two objects per animal: <ul> <li>Object 1 contains a data frame with the real and simulated sequences for an animal. e.g., ls[[1]][[1]] </li> <li>Object 2 contains the home range in raster format of an animal. e.g., ls[[1]][[2]]</li> </ul> The data frames in object 1 contain real habitat use sequences and corresponding simulated habitat use sequences generated in the home range of the specific individual (900 simulated sequences: 6 habitat selection rules x 3 selection coefficients x 50 repetitions). Open and closed habitats are respectively encoded by 0 and 1. The first 96 columns of each row in a data frame represent a 16-day habitat use sequence, with a fixed 4-hour relocation interval (0, 4, 8, 12, 16 and 20h). Column names are named as follows: Day_1_0h, Day_1_4h,..., Day_16_20h. In the next columns we provide the selection coefficients (columns 97-99), the habitat selection rules (or pattern, columns 100-102) and the number of missing values (mvs, columns, 103-104) for each of the real and simulated sequences. Note that simulated sequences have no missing values (i.e. values are always 0.00) and for real sequences there is no selection coefficient or habitat selection rule (i.e. values are always xxx). Rownames of simulated sequences are composed out of the habitat selection rule (c, o, a24, a33, a42 and u), the selection coefficient (5, 10, 50) and the replicate (1 to 50), separated by dashes. For example, the first simulated sequence in the first data frame (ls[[1]][[1]][1,]) is described as a24_10_1. The rownames of real sequences instead are composed out of the individuals' identifier, the biweekly period (1 to 23) and the year. For example, the first real sequence in the first data frame (ls[[1]][[1]][901,]) is described as 1_5_2006.

Fig. 1 in Patterns of spatio-temporal distribution as criteria for the separation of planktic foraminiferal species across the Danian-Selandian transition in Spain

Fig. 1. Geographical location of the Caravaca and Zumaia sections (Spain).

opencc-zeroDec 2022View details →

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-zeroOct 2023View details →

Analysing spatio-temporal patterns of non-native fish in a biodiversity hotspot across decades

Aim: Analysing the spatio-temporal patterns and dynamics of non-native species is essential to understanding the mechanisms underlying successful invasions and developing effective management strategies. Yet, such analyses generally neglect the influence of receiving ecosystem types and non-native species sources (i.e. alien species, non-natives originating outside the concerned region; translocated species, nonnatives introduced to locations outside their historical range within the concerned region). Location: Yunnan, China. Methods: We analysed long-term (1950–2022) spatio-temporal patterns and potential underlying dynamics of non-native fishes in a biodiversity hotspot (Yunnan, China), paying special attention to waterbody types receiving non-native species and comparing alien and translocated species. We did this through compiling a highly comprehensive occurrence dataset of native and non-native fishes. Results: We recorded 783 native species and 94 non-native species (49 alien species and 45 translocated species), which mainly belonged to the order Cypriniformes (52 species) and were introduced via purposes for advancing aquaculture. Most frequently encountered non-native species were either intentionally introduced aquaculture species or small-bodied fish unintentionally introduced via aquaculture activities. The richness and spatial ranges of non-native fishes increased consistently since the 1950s and demonstrated a pronounced change after the 2000s, with densely populated areas and the middle to lower reaches of large rivers being more profoundly affected. The number of records of translocated species exceeded the number of records of alien species after the 2000s. Lakes and reservoirs are hotspots for both alien and translocated species introductions, and watersheds with large areas in Yunnan (e.g. the Jinsha-Yangtze and Lancang-Mekong basins) contained more non-native fish. Main Conclusions: Our study highlights the need to consider invasion sensitivities of receiving ecosystems and pay special attention to intra-regional species translocations when developing prevention and management strategies against invasions of alien species, particularly in important biodiversity hotspots around the world.