In this database, we present plant-animal interactions in the lowland forest community of Doñana National Park during the fruiting season. Our focus primarily lies on plant-frugivore interactions but we also report data on animals that visits fruiting plants. We used DNA-based molecular analysis on faecal samples and regurgitated seeds from fleshy-fruited plant species to identify the frugivore species involved in each dispersal event and other animal species visiting plants. Sampling was conducted over the fruiting seasons from 2018 to 2022. We used seed traps and transects that were stratified across several forest and scrubland communities. Our dataset contains 13,835 pairwise interaction records derived from 8,783 collected samples. Of these records, 6,358 correspond to frugivorous interactions, while 7,477 correspond to animals visiting plants. The dataset encompasses 19 plant species, 39 bird species (with 30 of them being frugivores), 7 mammal species (with 6 of them being frugivores), 2 reptile species, 2 amphibia species, and 1 insect species. Each interaction is recorded as an event, defined by the encounter of species at a specific location and time. The interactions are further described in terms of the partners involved, allowing for multiple occurrences within the same event.
These data can be used to assess frugivory and seed dispersal networks, explore frugivore contributions to seed rain in different microhabitats, or frugivores’ preference for fruit/seed sizes. They provide occurrence data for animals (mainly birds) associated with specific plant species, enabling the study of animal dynamics and behavior. Moreover, they support big-data approaches for generating species interaction models and macro-ecological analyses. This dataset greatly enhances our understanding of animal-plant interactions, particularly in the context of frugivory.
Los datos en este recurso de evento de muestreo han sido publicados como Archivo Darwin Core(DwC-A), el cual es un formato estándar para compartir datos de biodiversidad como un conjunto de una o más tablas de datos. La tabla de datos del core contiene 8.783 registros.
también existen 2 tablas de datos de extensiones. Un registro en una extensión provee información adicional sobre un registro en el core. El número de registros en cada tabla de datos de la extensión se ilustra a continuación.
Este IPT archiva los datos y, por lo tanto, sirve como repositorio de datos. Los datos y los metadatos del recurso están disponibles para su descarga en la sección descargas. La tabla versiones enumera otras versiones del recurso que se han puesto a disposición del público y permite seguir los cambios realizados en el recurso a lo largo del tiempo.
La siguiente tabla muestra sólo las versiones publicadas del recurso que son de acceso público.
Los usuarios deben citar este trabajo de la siguiente manera:
Moracho E, Jordano P, Calvo G, Homet P, Villalva P, Quintero E, Isla J, Arroyo J M (2023). Plant-animal frugivore interactions and beyond in Doñana's fruiting season: Insights from DNA barcoding. Version 1.2. No organization. Metadata dataset. https://ipt-demo.gbif.es/resource?r=barcoding_frugi_donana&v=1.2
Los usuarios deben respetar los siguientes derechos de uso:
El publicador y propietario de los derechos de este trabajo es Estación Biológica de Doñana (CSIC). Esta obra está bajo una licencia Creative Commons de Atribución/Reconocimiento-NoComercial (CC-BY-NC 4.0).
Este recurso ha sido registrado en GBIF con el siguiente UUID: 87033e79-02a7-487d-9515-9e4f07ca695f. Estación Biológica de Doñana (CSIC) publica este recurso y está registrado en GBIF como un publicador de datos avalado por GBIF Spain.
Samplingevent; Occurrence; endozoochory; molecular analysis; plant–animal interactions; seed dispersal; ecological networks; protected areas; biodiversity
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Our study area primarily encompasses the Doñana National Park, which spans parts of the provinces of Huelva, Sevilla, and Cádiz.
|Coordenadas límite||Latitud Mínima Longitud Mínima [-90, -180], Latitud Máxima Longitud Máxima [90, 180]|
Datos del proyecto
The project SUMHAL aims at implementing a strategy for biodiversity conservation in the western Mediterranean hotspot by setting a technologically efficient and scientifically robust system. The project combines fieldwork and virtual research environments for the recording, storing, analysis, and dissemination of the conservation status and threats of biodiversity in Andalusia (Southern Spain). The main objective of WP5 is to characterize and quantify the interactome of biodiversity in protected areas within the RN2000, by examining the size and diversity of ecological functions integrated within complex networks of ecological interactions among species. The thematic elements of eLabs-BioINTERACT encompasses different forms of ecological interaction: including predator-prey, herbivory, pollination, seed dispersal, parasitism, plant-plant facilitation, mycorrhizae-plants, among others. Current online interaction databases are limited and there are no standards for ecological interaction data, which is crucial for the digitization, sharing and aggregation of interaction data on a large scale. SUMHAL’s WP5 aims to produce useful information for the conservation of biodiversity and biotic interactions by mobilizing information from both field data recording and bibliographic compilation, structured in standardized formats for free access.
|Título||Sustainability for Mediterranean Hotspots in Andalusia integrating LifeWatch ERIC (SUMHAL). Work package 5 (WP5): eLabs-BioINTERACT: ecological interactions as Biodiversity and ecosystem service components|
|Fuentes de Financiación||This study was funded by MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020].|
|Descripción del área de estudio||The proposed geographical framework for action is Andalusia, with a focus on the Doñana National Park (END), while also including areas within the RN2000. This framework will serve as a foundation for mobilizing information on biotic interactions in broader geographic areas, including Spanish, European, and global levels.|
|Descripción del diseño||The specific aims of the work package are: Task 1. Updating and development of databases on ecological interactions by means of bibliographic compilation and field-based studies. Task 2. Development of a cluster of eLabs platforms to inventory, document and analyze the biodiversity of ecological interactions in protected natural spaces. Task 3. Development of public platforms for database use, integrated with citizen science activities and school training for recording ecological interaction among species.|
Métodos de muestreo
Our sampling design aimed to capture the diverse range of frugivory interactions in the Doñana National Park. To achieve this goal, we covered the main Mediterranean plant communities hosting the diversity of fleshy-fruit species in the area, including (i) Juniperus-dominated forests coexisting with Mediterranean scrub and scattered pines; (ii) sclerophyllous scrubland dominated by Pistacia lentiscus, coexisting with a total of 28 fleshy-fruited plant species; (iii) sparse mixed scrubland with a wide amount of fleshy-fruited plant species, occasionally dominated by Arbutus unedo, Olea europaea or Myrtus communis, (iv) humid scrub located in depressions, dominated by Rubus ulmifolius. We used DNA-barcoding techniques of faecal samples and regurgitated seeds to estimate the intensity of interactions between frugivores and plants, as well as between fruiting plants and animals in general. Our sampling approach involved placing seed traps beneath the crowns of various plant species, which served as potential fruit sources or bird perching spots. To protect the seed traps from seed predation, we covered them with a 1 cm mesh. The sampled area beneath each focal plant varied, typically corresponding to one tray area. However, for larger plants, we installed two trays to ensure maximum coverage. We occasionally collected scats within a delimited rectangular soil surface adjacent to the tray or along open transects to increase the sampled surface area. Overall, we sampled a total of 308 sites, including 105 sites under juniper individuals, 80 sites under Pistacia individuals, and 123 sites under a variety of fleshy and non-fleshy fruiting individuals (including up to 11 plant species).
|Área de Estudio||We conducted our study in the Doñana National Park between 2018 and 2022, covering different plant communities in the area. Sampling was carried out along the fruiting season, which typically spans from September to May, although the exact timing varied among plant species. Each plant community was sampled during one or two consecutive fruiting seasons to ensure comprehensive coverage of frugivorous animal-plant interactions.|
|Control de Calidad||The dataset includes quality measures regarding the lab procedure and animal identification: (i) the percentage of similarity between sequences, from the focal sample and from the reference database, and (ii) the sequence length. In the Juniperus-dominated forest, successful identification was defined as sequences with a similarity of >98% and a minimum length of 100 bp. In the Lentiscus-dominated scrubland, we only considered samples over 150 bp length and over 90% of identity similarity. Most samples scored over 99% similarity (mean length = 288 bp, mean similarity = 99.31%). For the subset of samples with similarity in between 90%-99% (n = 228), the second species identified had to be further than 2% similarity distance, or absent in the geographical range area, as an additional quality requisite. In mixed scrubland, the main criteria to assign a sample to an animal species was the second species identified had to exhibit a similarity distance greater than 2% from the first species. The dataset includes genetic sequence information for each animal sample, ensuring result reproducibility. Furthermore, for certain focal plants, interaction accumulation curves (IAC) were estimated to assess the completeness of DNA-barcoding sampling (Colwell & Coddington 1994, Jordano 2016), as described in Quintero et al. 2023 Suppl. Mat. B.3.|
Descripción de la metodología paso a paso:
- The seed traps were scanned every ten to fifteen days, and all samples present in the trays were collected, regardless of whether they contained seeds or not. A total of 2.993 samples were collected from the Juniper forest, 3.029 samples from the Pistacia-dominated scrubland, and 2.761 samples from the mixed scrublands. When abundant samples were found in the trays and appeared identical (such as multiple regurgitated seeds below a perch), a subset of samples was collected for barcoding. The remaining seed count was then assigned to the same species identified in the collected subset. These imputed samples account for approximately 8% of the total samples collected in the Pistacia-dominated scrubland. The number of samples collected varied among focal plants. We initially analyzed all available samples per plant site, excluding those with significantly degraded material, up to a maximum of 40 samples. However, in the Pistacia-dominated scrubland, certain plants yielded more than 40 samples (reaching up to 200 samples in some cases). To ensure comprehensive sampling, we gradually increased the number of DNA-barcoded samples until the sampling completeness curves reached saturation. This rigorous approach ensured a robust characterization of the frugivore-plant assemblage in Doñana. Plant species of seeds from faces or regurgitations were identified through direct observation by at least one trained and qualified person. Lab procedure: The identification of disperser species was based on the mitochondrial DNA region (COI: cytochrome c oxidase subunit I). For birds, we used a fragment of 464-bp for samples from Pistacia-dominated scrubland, 272-bp for samples from Juniperus and mixed fleshy fruit plant species, and 758- or 175-bp for mammals. DNA extraction was performed using the GuSCN/ silica protocol and PCR amplification followed the protocol described by González-Varo et al. (2014) with minor modifications (Quintero et al. 2023 Suppl. Mat. B.1). All bird samples were amplified by PCR using the primer pair COI-fsdF /COI-fsdR for samples from Pistacia-dominated scrubland and the primer pair COI-fsd-degF/ COI-fsdR for the remaining samples (González-Varo et al. 2017). Mammal samples were amplified following the protocols and primers of Alcaide et al. and additionally Schaffer et al. 2017 (only primer pair In1f/In1r) for samples from mixed scrubland. The resulting sequences (i.e., barcodes) were revised and edited using 4Peaks software (http://nucleobytes. com/4peaks/). The identified species was then determined by comparing the sequences against the "BARCODE OF LIFE DATA" (BOLD) and Nucleotide Basic Local Alignment Search Tool (BLAST from NCBI) reference databases. For the bird samples that did not amplify, we amplified the 272-bp fragment from the 464-bp COI DNA region using the primers COI-fsd-degF and COI-fsdR and the nested PCR protocol described in González-Varo et al. (2017).
- González‐Varo, J. P., Arroyo, J. M., & Jordano, P. (2014). Who dispersed the seeds? The use of DNA barcoding in frugivory and seed dispersal studies. Methods in Ecology and Evolution, 5(8), 806-814. (doi:10.1111/2041-210X.12212) González-Varo JP, Carvalho CS, Arroyo JM, Jordano P. 2017 Unravelling seed dispersal through fragmented landscapes: Frugivore species operate unevenly as mobile links. Mol. Ecol. 26, 4309–4321. (doi:10.1111/mec.14181) Colwell, R. K., & Coddington, J. A. (1994). Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 345(1311), 101-118. Jordano, P. (2016). Sampling networks of ecological interactions. Functional ecology, 30(12), 1883-1893 Alcaide M, Rico C, Ruiz S, Soriguer R, Muñoz J, Figuerola J. 2009 Disentangling vector-borne transmission networks: A universal DNA barcoding method to identify vertebrate hosts from arthropod bloodmeals. PLoS One 4, 1–6. (doi:10.1371/journal.pone.0007092) Schäffer S, Zachos FE, Koblmüller S (2017) Opening the treasure chest: A DNA- barcoding primer set for most higher taxa of Central European birds and mammals from museum collections. PLoS ONE 12(3): e0174449. https://doi.org/10.1371/journal.pone.0174449 Quintero, E., Rodríguez- Sánchez, F. & Jordano, P. (2023) Reciprocity and interaction effectiveness in generalised mutualisms among free-living species. Ecology Letters, 26, 132–146. Available from: https://doi.org/10.1111/ ele.14141
This database comprises records of pairwise animal-plant interactions at specific locations and times. The core of the database are the interactions that are described by different attributes in the Event file. These attributes include information sources, interaction location, sampling design details and other relevant information. The Occurrences file provides information about the partners engaged in the interaction. This includes details about their taxonomy and behavior observed during the interaction. The MeasurementsOfFacts file contains measurements of the sampling effort regarding to area and time. List of variables and their descriptions: “Events" data: > eventID: A unique identifier for each interaction event in the dataset. It is created by combining the institution, the funding project, the sampling site ID and the lab code. > bibliographicCitation: A bibliographic reference for the scientific report from which the data was extracted. > eventDate: The date when the sampled was collected. It represents when the interaction occurred. > country: The country where the interaction was observed. > stateProvince: The administrative region where the interaction occurred, represented as a combination of region and province (e.g., Andalucía:Sevilla). > municipality: The municipality where the interaction occurred. > locationRemarks: A descriptive name of the location in the Natura 2000 Network > locality: The name of the specific site (e.g., village or town) where the interaction occurred. > decimalLatitude: The latitude of the site where the interaction occurred, expressed in decimal degrees using the unprojected WGS84 coordinate system and georeferenced in Google Earth. > decimalLongitude: The longitude of the site where the interaction occurred, expressed in decimal degrees using the unprojected WGS84 coordinate system and georeferenced in Google Earth. > minimumElevationInMeters: The altitude of the site in meters. A unique altitude range for the Doñana area is provided for all the samples. > geodeticDatum: The geodetic datum used to define the geographical coordinates of the site. > sampleSizeUnit: The smallest unit of measurement used to quantify the interaction sampling. > sampleSizeValue: The number of sample size units on which the interaction intensity is based. > samplingProtocol: The method used to sample biotic interactions in the study. > basisOfRecord: The basis of interaction sampling, which indicates how the data were collected. It includes "MaterialSample" for interaction events inferred from physical samples (e.g., a fecal sample, a stomach, etc), "HumanObservation" for interaction data directly observed in the field by people, and "MachineObservation" for data collected automatically by machines. > dynamicProperties: A list of general descriptors that provide additional information about the study, including: - Study focus: This indicates which taxa the study is focused on and can be categorized as phytocentric, zoocentric, combined, or other; - Sampling site: Information on the sampling site (e.g. plant species in which the trays were placed) > resourceRelationship: Type of interaction or process being studied. > institutionCode: The acronym of the institution having custody of the dataset. 2. “Occurrences” data: > eventID: A unique identifier for each interaction event in the dataset. > kingdom, phylum, class, order, family, genus, scientificName: The taxonomic classification of the observed taxa, following the GBIF taxonomic backbone. > taxonRemarks: The role played by the taxon during the Event. It includes "focalPlant", which refers to the plant species where the sampling site is located; “animalSp, which refers to the animal species interacting with a focal plant and/or dispersing a fleshy fruit plant species; “plantSp”, which refers to the plant species consumed and being dispersed by the animal. > taxonID: An identifier for the set of taxon information provided by the GBIF backbone taxonomy > behaviour: The action performed by each partner during the interaction. It includes behaviours related to plants, such as "plant dispersed by frugivore”, "plant visited by animal”; and related to animals, such as "frugivore dispersing seeds”, "animal perching”, "animal visiting plant" (when analysis are not enough to disentangle the behaviour). > occurrenceRemarks: A list of quality information related to the laboratory procedure for assigning animal taxa to DNA samples, including: - ; Percentage of similarity between the reference and the sampled sequence; - Sequence length > recordedBy: Person responsible for field sampling and laboratory procedure. > associatedSequences: Genetic sequence information associated with animal material samples. 3. “MeasurementsOfFacts” data: > eventID: A unique identifier for each interaction event in the dataset. > measurementType: A measurement of the sampling effort for sampling biotic interactions at a locality and time, including: - Sampling area: The area covered by the sampling effort (expressed as the value and its units); - Sampling time: The duration of the sampling effort (expressed as the value and its units). > measurementUnit: The units of measurement used to quantify the sampling effort. > measurementValue: The numeric value of the sampling effort.
|Propósito||This dataset is highly valuable for scientific research focused on understanding the complex dynamics of natural plant regeneration, particularly in relation to frugivory and seed dispersal processes. It provides occurrence data for animals (mainly birds) associated with specific plant species, enabling investigations into animal dynamics and behavioral patterns. The dataset offers significant opportunities for advancing big-data approaches, such as generating species interaction models and macro-ecological analyses, which provide insights into the underlying ecological processes that govern species coexistence and ecosystem functioning. In combination with other approaches, this dataset greatly enhances our understanding of animal-plant interactions, particularly within the context of frugivory.|