Find research datasets worth reusing

opencc-by-4.0Oct 2024View details →

Data underlying the assessment of biodiversity and diverse values for nature in University of Helsinki campuses / Aineisto luonnon monimuotoisuutta ja moninaisia arvoja Helsingin yliopiston kampuksilla käsittelevän selvitystyön taustalla

These records contain the spatial and nonspatial datasets underlying the assessment of biodiversity and diverse values for nature in the four campuses of University of Helsinki, namely the Kumpula, Meilahti, Viikki, and City center campuses in Helsinki. The assessment was a part of the University of Helsinki Sustainability and responsibility plan 2022-2024. For further information on the types and contents of the data, see the pdf "README.pdf" and the assessment report.

opencc-by-4.0Aug 2024View details →

Mobilising marine biodiversity data: a new malacological dataset of Italian records (Mollusca)

The location and palaeoceanographic history of the Mediterranean Sea make it a biodiversity hotspot, prompting extensive studies in this region. However, despite the marine biodiversity of this area is apparently widely studied, a large amount of distributional data for Mediterranean taxa is still unpublished or scattered in various sources and formats, causing severe limitations to their potential reuse. This emerges as a particularly thorny issue for highly biodiverse and neglected taxa, such as invertebrates. The mobilisation of these frozen data through a process of standardisation and georeferencing could potentially support biodiversity research and conservation. The aim of this work is to provide a standardised pipeline to integrate these dispersed data, focusing on the Italian waters of the Mediterranean Sea and using molluscs as target taxa. Data were gathered from two main sources: published literature and Natural History Collections. The harmonisation process involved three key steps: 1) terminology and structure standardisation, 2) taxonomy updating and 3) georeferencing. Our efforts yielded over 44000 standardised records of mollusc species from Italian seawaters. These records encompassed primary biodiversity data from newly digitised specimens owned by 11 different institutions and private collectors, as well as secondary biodiversity data extracted from 311 published studies.

opencc-by-4.0Jan 2022View details →

Data from: The extreme rainfall gradient of the Cape Horn Biosphere Reserve and its impact on forest bird richness. Biodiversity and Conservation

Description of dataset This dataset contains information about forest bird species richness and climatic variables in 61 sample sites of the Cape Horn Biosphere Reserve. This dataset was analysed in : Quilodrán CS, Sandvig EM, Aguirre F, Rivero de Aguilar J, Barroso O, Vásquez RA, and R Rozzi. 2022. Effects of the extreme rainfall gradient in the Cape Horn Biosphere Reserve on forest bird richness. Biodiversity and Conservation.    Acknowledgments  This study was funded by grants for Technological Centers of Excellence with Basal Financing of the National Agency for Research and Development (ANID-Chile), granted to the Cape Horn International Center (CHIC- FB210018) and the Institute of Ecology and Biodiversity (IEB-AFB170008). CSQ acknowledges support from the Swiss National Science Foundation (N°P5R5PB_203169).

opencc-by-4.0Jan 2022View details →

Training data for the "Biodiversity data exploration" Galaxy-E tutorial

Dataset sample from Reef life survey initiative https://reeflifesurvey.com/ to serve as a training set for "Biodiversity data exploration" tutorial for Galaxy and notably Galaxy for ecology initiative

opencc-by-4.0Feb 2022View details →

State of biodiversity documentation in the Philippines: Metadata gaps, taxonomic biases, and spatial biases in the DNA barcode data of animal and plant taxa in the context of species occurrence data

These files can be categorized into three groups: (1) raw datasets obtained from public databases (i.e., GBIF, BOLD, and GenBank), (2) manually edited files needed for parsing and analysis, and (3) supplementary files for spatial analysis. All are used in the examination of gaps and biases present in Philippine biodiversity data, which can direct research on the taxa and spatial regions that need more sampling.

opencc-by-4.0Apr 2022View details →

Data from: Riparian reforestation on the landscape scale – Navigating trade-offs among agricultural production, ecosystem functioning and biodiversity

Short description This repository contains the relevant data and code used for the analyses of the scientific publication: "Riparian reforestation on the landscape scale – Navigating trade-offs among agricultural production, ecosystem functioning and biodiversity", published in the Journal of Applied Ecology. For further details please see the original article and its supplementary materials.   Organization of the data The repository contains two main folders:    1. Target indicators & spatial analysis ‘target indicators.csv’: Measured variables that have been quantified at the CROSSLINK field sampling campaign in the Zwalm catchment (EPT taxa richness, diatoms functional evenness, cotton-strip assay). ‘bio-suitability segments.csv’: Biophysical suitability for food production of the arable land for each riparian segment of the Zwalm. ‘spatial analysis.xlsx’: Results of the Zwalm spatial analyses addressing land-use and physiographic properties of the (1) local riparian corridors; (2) full riparian corridors within in the upstream catchments and (3) total upstream catchment areas for each sampling site. ‘Summary model development Zwalm.pptx’: Additional information on the models that have been used in the CoMOLA optimization framework.    2. CoMOLA input & parameterisation The files in this folder can be used for the parameterisation of the Python tool CoMOLA (Strauch et al., 2019). Source for CoMOLA, including user manual: https://github.com/michstrauch/CoMOLA ‘config.ini’: Basic configuration file of CoMOLA (needs to be adjusted to local settings) ‘input’ folder: Includes the CoMOLA input files that have been used in our study. See CoMOLA manual for more details on each file. ‘models’ folder: Includes the Python code of the models that are used for the calculation of all target indicators within the optimization framework (‘Zwalm_4_Models_v1_utf8.py’). The sub-folders ‘GIS_temp_files’ and ‘Input’ contain all files that are needed and have been used to run the Python code.

Fig. 3 in Analysis of biodiversity data suggests that mammal species are hidden in predictable places

Fig. 3. Consensus results of species delimitation analyses. Phylogenetic distribution of hidden diversity estimated from strict consensus of delimitation results (SI Appendix, Table S1). Each silhouette represents a mammalian order with its shadow reflecting the ratio of predicted species to recognized species. Striped silhouettes represent orders with conflicting delimitation results that were not included in the predictive analysis. Phylogeny was adapted from ref. 31.

Fig. 4 in Analysis of biodiversity data suggests that mammal species are hidden in predictable places

Fig. 4. Important predictors of hidden species in mammals. (A) From Top to Bottom, the 50 most important predictive variables (judged by MDA), for the consensus random forest classification model. In both plots, variables are color coded by life history, geographic, climatic, taxonomic, and environmental. (B) Boxplots representing values of the top predictive variables for species included in the consensus model. Values from species identified as hidden are shown at the Bottom of each plot (labeled "H"), and values from species not identified as hidden are shown Above (labeled "NH"). Outliers are excluded from boxplots.

Fig. 1 in Analysis of biodiversity data suggests that mammal species are hidden in predictable places

Fig. 1. Predictive modeling workflow. The framework proposed for identifying named mammal species that are likely to contain hidden diversity utilizes barcoding gene sequences and machine learning models built from environmental, geographic, climatic, taxonomic, and life history variables.

Fig. 2 in Analysis of biodiversity data suggests that mammal species are hidden in predictable places

Fig. 2. Scope of the dataset. Genetic sequences for ∼70% of currently recognized mammalian species were obtained. All mammalian orders are represented, with 23 orders containing sequences from both COI and cytb and 4 having only sequences from cytb. (A) Circle plots reflect species representation for the COI and cytb genes in each order. Dark bars represent the species present in the dataset and light bars represent species for which no genetic data are available. (B) Blue bars represent the proportion of the sequence database represented by each order, and gray bars represent the proportion of recognized species in each order. (C) A total of 3,205,630 geographic occurrence records were obtained for species present in the genetic database.

opencc-by-4.0Aug 2022View details →

Data: Biodiversity Risks and Safeguards of China's Hydropower Financing in BRI Countries

Data used in: Narain D, Teo HC, Lechner AM, Watson JEM, Maron M. 2021. Biodiversity risks and safeguards of China’s hydropower financing in BRI countries. (In press with One Earth)

opencc-zeroSep 2022View details →

Source code and data from: Foraging personalities modify effects of habitat fragmentation on biodiversity

Habitat loss undeniably poses a substantial threat to biodiversity, but whether fragmentation per se drives the loss of species is still widely debated. While negative consequences from fragmentation are often anticipated, many empirical studies report positive effects. However, the intrinsic mechanisms governing species' persistence in fragmented landscapes are not yet understood. In this study, we investigated consistent personality-dependent differences in foraging behavior among individuals as a possible mechanism underlying the discrepancy of reported fragmentation effects. We devised a mechanistic individual-based model simulating the home range behavior of a competitive small mammal community based on the availability of a shared resource. Thereby, an individual's risk-taking behavior dictates its foraging decisions at risky habitat edges, an inherent property of fragmentation per se. Our simulations show that differences in risk-taking while foraging are potentially a further mechanism contributing to reconciling the fragmentation debate. The first scenario considering risk-seeking communities showed a neutral response towards fragmentation, while the second scenario featuring risk-avoiding communities confirmed the negative effects of fragmentation. Notably, the third scenario, simulating behaviorally diverse communities including risk-avoiding and risk-seeking individuals, demonstrated a positive influence of fragmentation on biodiversity. Intraspecific differences in behavior could also enhance the temporal species coexistence (coviability) of communities threatened by an ongoing habitat loss. Our study highlights the importance of recognizing the behavioral composition of populations and communities for estimating fragmentation effects, because differences in risk-taking can influence the coping abilities of animal communities in light of fragmentation.

opencc-by-4.0Sep 2022View details →

Biodiversity data collected by volunteers from NaturTjek 2015-2020

This .csv file contains all observation made by volunteers between 2015 and 2020 as part of the Danish large-scale citizen science project: "NaturTjek" or "Biodiversitet Nu". Each line represents an observation made by a volunteer profile and contains information on the species, the time, the location and (anonymized) informaiton on the recorder (i.e. and ID number). Columns containing 1) the username, 2) the last name and 3) the birth year of the volunteers have been removed. In addition to the information collected as part of the original species observation, the file also contains information on selected geo-spatial attributed connected to the spatial location of the observation and associated post-collection.

opencc-zeroSep 2022View details →

Data from: Habitat quality influences pollinator pathogen prevalence through both habitat–disease and biodiversity–disease pathways

The dilution effect hypothesis posits that increasing biodiversity reduces infectious disease transmission. Here, we propose that habitat quality might modulate this negative biodiversity–disease relationship. Habitat may influence pathogen prevalence directly by affecting host traits like nutrition and immune response (we coined this as the 'habitat–disease relationship') or indirectly by changing host biodiversity (biodiversity–disease relationship). We used a path model to test the relative strength of links between habitat, biodiversity, and pathogen prevalence in a pollinator–virus system. High-quality habitat metrics were directly associated with viral prevalence, providing evidence for a habitat–disease relationship. However, the strength and direction of specific habitat effects on viral prevalence varied based on the characteristics of the habitat, host, and pathogen. In general, more natural area and richness of landcover types were directly associated with increased viral prevalence, while greater floral density was associated with reduced viral prevalence. More natural habitat was also indirectly associated with reduced prevalence of two key viruses (black queen cell virus and deformed wing virus) via increased pollinator species richness, providing evidence for a habitat-mediated dilution effect on viral prevalence. Biodiversity–disease relationships varied across viruses, as prevalence of sacbrood virus was not associated with any habitat quality or pollinator community metrics. Across all viruses and hosts, habitat–disease and biodiversity–disease paths had effects of similar magnitude on viral prevalence. Therefore, habitat quality is a key driver of variation in pathogen prevalence among communities via both direct habitat–disease and indirect biodiversity–disease pathways, though the specific patterns varied among different viruses and host species. Critically, habitat–disease relationships could either contribute to or obscure dilution effects in natural systems depending on the relative strength and direction of the habitat–disease and biodiversity–disease pathways in that host–pathogen system. Therefore, habitat may be an important driver in the complex interactions between hosts and pathogens.

opencc-zeroOct 2022View details →

Data from: Biodiversity patterns diverge along geographic temperature gradients

Models applying space-for-time substitution, including those projecting ecological responses to climate change, generally assume an elevational and latitudinal equivalence that is rarely tested. However, a mismatch may lead to different capacities for providing climatic refuge to dispersing species. We compiled community data on zooplankton, ectothermic animals that form the consumer basis of most aquatic food webs, from over 1,200 mountain lakes and ponds across western North America to assess biodiversity along geographic temperature gradients spanning nearly 3,750 metres of elevation and 30 degrees latitude. Species richness, phylogenetic relationships, and functional diversity all showed contrasting responses across gradients, with richness metrics plateauing at low elevations but exhibiting intermediate latitudinal maxima. The nonmonotonic/hump-shaped diversity trends with latitude emerged from geographic interactions, including weaker latitudinal relationships at higher elevations (i.e. in alpine lakes) linked to different underlying drivers. Here, divergent patterns of phylogenetic and functional trait dispersion indicate shifting roles of environmental filters and limiting similarity in the assembly of communities with increasing elevation and latitude. We further tested whether gradients showed common responses to warmer temperatures and found that mean annual (but not seasonal) temperatures predicted elevational richness patterns but failed to capture consistent trends with latitude, meaning that predictions of how climate change will influence diversity also differ between gradients. Contrasting responses to elevation- and latitude-driven warming suggest different limits on climatic refugia and likely greater barriers to northward range expansion.

opencc-by-4.0Jun 2021View details →

Data used in the paper: Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot

This repository contains phylogenetic and functional trait data, raster files, and tables with sampling information and references used in the article "Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot" by Silva, J.L.A., Souza, A., and Vitória, A.P. Journal of Vegetation Science, <a href="https://doi.org/10.1111/jvs.13049">https://doi.org/10.1111/jvs.13049</a> . Description of files: (1) "Species-level_Trait_Data_Silva_et_al._2021.csv": This file contains species-specific mean trait values and the plant growth form of the 2,122 studied species, whenever available. Trait values were compiled from public sources such as original papers, master and doctoral dissertations, and global trait databases. (2) "Phylogenetic_Tree_Silva_et_al._2021.txt": This file contains the phylogenetic tree of the 2,122 studied species. (3) "CWM_Trait_Maps.zip": This file contains seven rasters of spatially contiguous surfaces produced by Ordinary Kriging Interpolation using Community-Weighted Means (CWM) of each functional trait. (4) "References-abundance-data.csv": This file contains sampling details and the references used to compile species abundance data for each studied site. (5) "References-trait-data.csv": This file contains sampling details and the references used to compile functional trait data.

opencc-zeroMay 2024View details →

Data from: Ecosystem functioning during biodiversity loss and recovery

Anthropogenic biodiversity loss can impair ecosystem functioning. Human activities are often managed with the aim of reversing biodiversity loss and its associated functional impacts. However, it is currently unknown whether biodiversity–ecosystem function (BEF) relationships observed during biodiversity recovery are the same as those observed during biodiversity loss. This will depend on how species extirpation and recolonisation sequences compare and how different species influence ecosystem functioning. Using data from a marine benthic invertebrate community, we modelled how bioturbation potential – a proxy for benthic ecosystem functioning – changes along biodiversity loss and recovery sequences governed by species' sensitivity to physical disturbance and recolonisation capability, respectively. BEF relationships for biodiversity loss and recovery were largely the same despite species extirpation and recolonisation sequences being different. This held true irrespective of whether populations were assumed to exhibit compensatory responses as species were removed or added. These findings suggest that the functional consequences of local biodiversity loss can be reversed by alleviating its drivers, as different species present at comparable levels of species richness during biodiversity loss and recovery phases have similar functional effects. Empirically verifying and determining the generality of our model-based results are potential next steps for future research.

opencc-by-4.0May 2024View details →

Benešov dataset - spectral and biodiversity data

The dataset containing spectral and biodiversity data used in the study presented in "“Flower power”: How flowering affects spectral diversity metrics and their relationship with plant diversity" by Perrone et al. (2024).

opencc-zeroJun 2024View details →

Data from: Individual energetics scale up to community coexistence: Movement, metabolism and biodiversity dynamics in fragmented landscapes

Unraveling the intricate mechanisms that govern community coexistence remains a daunting challenge, particularly amidst ongoing environmental change. To understand the response of individual animals to environmental change, physiology and individual metabolism are often studied. However, this perspective is currently largely lacking in community ecology. We argue that the integration of individual metabolism into community theory can offer new insights into coexistence. We present the first individual-based metabolic community model for a terrestrial mammal community to simulate energy dynamics and home range behavior in different environments. Using this model, we investigate how ecologically similar species coexist and maintain their energy balance under food competition. Only if individuals of different species are able to balance their incoming and outgoing energy over the long-term will they be able to coexist. After thoroughly testing and validating the model against real-world patterns such as of home range dynamics and field metabolic rates, we applied it as a case study to scenarios of habitat fragmentation - a widely discussed topic in biodiversity research. First, comparing single-species simulations with community simulations, we find that the effect of habitat fragmentation on populations is strongly context-dependent. While populations of species living alone in the landscape were mostly positively affected by fragmentation, the diversity of a community of species was highest under medium fragmentation scenarios. Under medium fragmentation, energy balance and reproductive investment were also most similar among species. We therefore suggest that similarity in energy balance among species promotes coexistence. We argue that energetics should be part of community ecology theory, as the relative energetic status and reproductive investment can reveal why and under what environmental conditions coexistence is likely to occur. As a result, landscapes can potentially be protected and designed to maximize coexistence. The metabolic community model presented here can be a promising tool to investigate other scenarios of environmental change or other species communities to further disentangle global change effects and preserve biodiversity.