DOI: 10.5061/dryad.g1jwstr3h
title: Human-induced downsizing of animal communities weakens trait matching between tropical plants and frugivores

description: Defaunation of large-bodied animals threatens essential ecosystem
 functions, such as seed dispersal. However, the impact of this
 ‘downsizing’ of animal communities on plant-frugivore trait matching—the
 alignment of frugivory-related plant traits (e.g., fruit size) with
 frugivore traits (e.g., body mass)—remains poorly understood at
 macroecological scales. Here, we investigate how human disturbance and
 environmental conditions influence trait matching in plant-frugivore
 networks across the tropics. We compiled data on fruit size and several
 other frugivory-related plant traits, frugivore body mass, and diet
 information for 1,927 plant and 1,120 animal species and integrated these
 with 12,708 interaction records across 102 networks. The datasets provided
 include: Plant-frugivore interaction data (Dataset S1), the plant
 trait data (Dataset S2), the frugivore trait data (Dataset S3),
 and the network data (incl. environmental and human impact data; Dataset
 S4). Data sources are provided in the datasets, and each dataset contains
 a README sheet with additional information. Data is openly available for
 reuse.
description: # Human-induced downsizing of animal communities weakens trait matching
 between tropical plants and frugivores Dataset DOI:
 [10.5061/dryad.g1jwstr3h](10.5061/dryad.g1jwstr3h) ## Description of the
 data and file structure Four datasets are provided, including different
 columns with information. ### Files and variables #### File:
 Dataset_S1_Network_Plant_Frugivore_Complete.xlsx
 **Description:** **Plant-frugivore network data: Dataset S1.**  We sourced
 the plant-frugivore interaction data from a comprehensive global dataset
 compiled by Fricke and Svenning (2020). This dataset consists of 410 local
 interaction networks, each constructed based on direct observations of
 animals interacting with fruits or seeds or from seeds retrieved from
 captured animals. These networks are bipartite, representing interactions
 between animal and plant species. While some networks recorded interaction
 frequencies, we used them in a binary format (presence or absence) due to
 inconsistencies in how frequencies were recorded across the dataset. This
 study focused on a subset of networks from tropical regions, defined
 geographically as the area between the Tropic of Cancer and the Tropic of
 Capricorn. This focus was chosen due to the key role of frugivorous
 vertebrates in seed dispersal within tropical ecosystems. The initial
 subset contained 251 spatially and temporally distinct tropical
 interaction networks (see Dataset S1). To account for repeated sampling at
 the same location over time, we aggregated unique plant-frugivore
 interactions from networks with the same coordinates into single composite
 networks, resulting in a final dataset of 181 geographically distinct
 networks (*n* = 145 non-composite networks; *n* = 36 composite networks
 formed by merging 2–11 original networks, mean ± SD: 2.94 ± 1.67). Prior
 to data analysis, the nomenclature of animal and plant species was updated
 to reflect taxonomic revisions made since the compilation of the original
 dataset. Animal species names were standardised following HBW and BirdLife
 International for birds, the International Union for Conservation of
 Nature (IUCN 2022) for mammals, and Oskyrko *et al.* (2024) for reptiles.
 Plant species names were standardised using the World Checklist of
 Vascular Plants (WCVP). ##### Variables | Column Name | Description  |
 Data Type | Units  | | :----------------------------- |
 :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------- | :----------------------- | | animal.accepted.species | Accepted species name according to HBW and BirdLife International (2021) for birds, the International Union for Conservation of Nature (IUCN 2022) for mammals, and Oskyrko et al. (2024) for reptiles | Text | - | | WCVP\_plant\_species\_name | Accepted species name according to the World Checklist of Vascular Plants (WCVP)  | Text | - | | net.id | Unique identifier assigned to each ecological network (see Fricke and Svenning, 2020) | Text | - | | study.id | Unique identifier assigned to each ecological network study (see Fricke and Svenning, 2020) | Text | - | | latitude | 
 
 | Continuous | Decimal degrees (°) | | longitude | 
 
 | Continuous | Decimal degrees (°) | | locality | Name of the locality
 where the network was sampled | Text | - | | country | Name of the country
 where the network was sampled | Text | - | | year | Year in which the
 network was sampled | Continuous | - | | Dispersal\_unit\_smaller\_Axis |
 Measure of 'fruit size'. Measurement of the smallest axis of the
 dispersal unit, recorded as either fruit length or width for indehiscent
 fruits, or seed length or width for dehiscent fruits | Continuous | mm | |
 BodyMass\_g | 
 
 | Continuous | g | | Beak\_volume | 
 
 | Continuous | mm3 | | Gape\_Size | 
 
 | Continuous | mm | | Frugivory\_level | Indicates the percentage of the
 diet that is made up of fruit | Continuous | - | | Diet\_Certainty |
 Specifies whether dietary information was inferred at the species, genus,
 or family level (see Wilman et al. 2014 for details) | Categorical | ABC,
 A,  B,  C,  D1, D2  | #### File: Dataset_S2_Fruit_and_Seed_Traits.xlsx
 **Description:** **Plant functional trait data: Dataset S2** We compiled
 data on frugivory-related plant traits, including fruit and seed
 dimensions (length and width), fruit type (e.g., berry, drupe, capsule;
 see Dataset S1), dehiscence (presence or absence), and seed fleshy
 appendages (presence or absence) for all 2,406 plant species that were
 present in the 181 ecological networks (see supplementary methods in Text
 S1 for details). Trait data were complete for 94.4% of the species (*n* =
 2,272) and were primarily sourced from floras and monographs (79%),
 supplemented by scientific articles (19%) and photographs (2%) (see
 Dataset S2 for data and sources). Plant trait data were preferred under
 the accepted species name; however, when unavailable, they were retrieved
 from taxonomical homotypic synonyms following the WCVP. Methods for
 measuring fruit size vary considerably across studies. Some approaches
 consider fruit length or width, while others use a composite measure that
 sums fruit length and width. Both approaches present limitations: fruit
 length or width may not always correspond to the fruit’s longest or
 shortest axis, and combining length and width into a single metric may
 fail to capture the constraints frugivores face during consumption. To
 address these inconsistencies, we defined fruit size as the smallest
 reported axis of the dispersal unit (either fruit or seed), as this
 dimension is most likely to represent the key constraint for frugivores
 during ingestion. For indehiscent fruits, frugivores generally interact
 with the entire fruit, as the fleshy pericarp remains intact. In contrast,
 for dehiscent fruits, frugivores often interact with the seeds rather than
 the usually dry pericarp, especially when fleshy structures such as arils,
 sarcotestae, or elaiosomes are present. Accordingly, for the trait
 matching analyses, we selected the smallest axis of the dispersal unit,
 whether it was fruit length or width for indehiscent fruits or seed length
 or width for dehiscent fruits. Throughout the study, we refer to this
 measurement as ‘fruit size’. ##### Variables **Dataset S2: Plant trait
 data, fruit and seed traits** | Column Name | Description  | Data Type |
 Units  | | :---------------------------- |
 :----------------------------------------------------------------------------------------------------------------------- | :---------- | :---------------------------------------------------------------- | | Network\_plant\_species\_name | Name under which the species appears in the original interaction networks | Text | - | | WCVP\_match\_status | Indicates whether the name under which the species appears in the original interaction networks is accepted or a synonym | Text | - | | WCVP\_plant\_species\_name | Accepted species name according to the World Checklist of Vascular Plants (WCVP)  | Text | - | | Researcher | Researcher who collected and finalised trait data | Text | - | | Mean\_Fruit\_length | 
 
 | Continuous | mm | | Min\_Fruit\_length | 
 
 | Continuous | mm | | Max\_Fruit\_length | 
 
 | Continuous | mm | | Mean\_Fruit\_width | 
 
 | Continuous | mm | | Min\_Fruit\_width | 
 
 | Continuous | mm | | Max\_Fruit\_width | 
 
 | Continuous | mm | | Mean\_Seed\_length | 
 
 | Continuous | mm | | Min\_Seed\_length | 
 
 | Continuous | mm | | Max\_Seed\_length | 
 
 | Continuous | mm | | Mean\_Seed\_width | 
 
 | Continuous | mm | | Min\_Seed\_width | 
 
 | Continuous | mm | | Max\_Seed\_width | 
 
 | Continuous | mm | | Fruit\_Type | Describes the morphological type of
 the fruit (e.g., berry, drupe, capsule) | Text | - | | Fruit\_Dehiscence |
 Indicates whether the fruit splits open (dehiscent) or remains closed
 (indehiscent) at maturity | Binary | Dehiscent, Indehiscent | |
 Seed\_Fleshy\_Appendage | Indicates whether the seed has a fleshy aril,
 sarcotesta, elaiosome or any other fleshy structure | Binary | Yes, No | |
 Retrieved\_from | Identifies the website or database from which the trait
 data was obtained | Text | - | | URL | Provides the link to the website or
 database page containing the species’ trait data | Text | - | |
 Source\_Continuous | Cites the backbone references used to score
 continuous trait data | Text | - | | Source\_Quality | Indicates the type
 (quality) of the backbone reference for the continuous trait data |
 Categorical | Flora, Monograph, Scientific Article, Photograph, Report,
 Website | | Source\_Categorical | Cites the backbone references used to
 score fruit type, dehiscence, and seed fleshy appendage | Text | - | |
 Notes | Contains any additional remarks or notable details about the trait
 data | Text | - | | Based\_on\_GenusAverage | Indicates whether the fruit
 or seed trait data was inferred using genus-level averages | Binary | Yes,
 No | #### File: Dataset_S3_Frugivore_Traits.xlsx
 **Description:** **Frugivore functional trait data: Dataset S3** We
 compiled data on frugivory-related animal traits, including body mass,
 degree of frugivory (percentage of the diet composed of fruit), beak
 dimensions, and gape size for all 1,226 animal species that were present
 in the 181 ecological networks. Trait data were complete for 98.9% of the
 species (*n* = 1,213) and were primarily sourced from established
 databases: AVONET, COMBINE, EltonTraits, ReptTraits (see Dataset S3 for
 data and sources). Animal trait data were preferred under the accepted
 species name; however, when unavailable, they were retrieved from
 taxonomic synonyms, following HBW and BirdLife International for birds and
 Soria *et al.* (2021) for mammals. In cases of discrepancies between
 accepted names and synonyms, the mean trait values were used. Dietary
 information was available for 1,102 species, with species-specific data
 for 93.7% of them; for the remaining 6.3%, diet was inferred at the genus
 or family level (see Wilman *et al.* 2014 for details). We selected body
 mass as the primary trait because it provides a comparable metric across
 birds, mammals and reptiles. While bird-specific traits such as beak
 volume and gape size are often used in trait matching studies, body mass
 was chosen for its broader applicability across taxa. This decision was
 supported by the strong correlations observed between body mass and beak
 volume (*r* = 0.81) and gape size (*r* = 0.85) in birds. The final dataset
 was predominantly composed of birds (75.8%), followed by mammals (23.3%)
 and reptiles (0.8%). ##### Variables **Dataset S3: Animal trait data,
 frugivore traits** | Column Name | Description  | Data Type | Units  | |
 :---------------------- |
 :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------- | :----------------------- | | All\_Network\_Names | Name under which the species appears in the original interaction networks | Text | - | | animal.class | 
 
 | Text | - | | animal.accepted.species | Accepted species name according
 to HBW and BirdLife International (2021) for birds, the International
 Union for Conservation of Nature (IUCN 2022) for mammals, and Oskyrko et
 al. (2024) for reptiles | Text | - | | BodyMass\_g | 
 
 | Continuous | g | | Beak\_volume | 
 
 | Continuous | mm^3^ | | Gape\_Size | 
 
 | Continuous | mm | | Frugivory\_level | Indicates the percentage of the
 diet that is made up of fruit | Continuous | - | | Granivory\_level |
 Indicates the percentage of the diet that is made up of seed | Continuous
 | - | | Diet\_Certainty | Specifies whether dietary information was
 inferred at the species, genus, or family level (see Wilman et al. 2014
 for details) | Categorical | ABC, A,  B,  C,  D1, D2  | |
 Body\_Mass\_Sources | Identifies the data sources used for body mass |
 Text | - | | Beak\_Volume\_Sources | Identifies the data source used for
 beak volume | Text | - | | Gape\_Size\_Sources | Identifies the data
 source used for gape size | Text | - | | Diet\_Sources | Identifies the
 data sources used for the percentage of the diet that is made up of fruit
 | Text | - | | Notes | Contains any additional remarks or notable details
 about the trait data | Text | - | #### File:
 Dataset_S4_Network_TraitMatch_Env_v2.xlsx **Description:**  **Human
 disturbance and environmental data: Dataset S4** Human disturbance and
 environmental data were assembled and extracted for each plant-frugivore
 network at spatial resolutions of 1 km and 5 km using ArcGIS Pro 3.3.
 Human disturbance data were derived from the Global Human Modification
 (gHM) dataset (Kennedy *et al.* 2020), which provides an integrated (i.e.,
 cumulative) measure of human alteration of terrestrial landscapes at 1 km
 resolution. This continuous metric (ranging from 0 to 1) represents the
 proportion of land modified by human activities and integrates 13
 indicators of disturbance, including human population density, built-up
 areas, cropland, livestock, major roads, minor roads, two-track roads,
 railroads, mining, oil wells, wind turbines, powerlines, and night-time
 lights, based on spatially explicit global datasets with a median
 reference year of 2016 (Kennedy *et al.* 2020). Environmental data were
 sourced from CHELSA V2.1, which provided annual temperature (°C),
 precipitation (mm), and NPP (g C/m²) at a 1 km resolution, averaged over
 the period 1981–2010. Although precipitation and NPP showed a strong
 correlation (*r* = 0.71), this remained below the commonly accepted
 multicollinearity threshold of *r* = 0.80. Consequently, both variables
 were retained, as their influence on frugivory may act through distinct
 ecological mechanisms. Additionally, AET (mm) was extracted as the annual
 average across the period 1982–2019 at a 1 km resolution. All
 network-level data is provided in Dataset S4. ##### Variables **Dataset
 S4: Environmental and human impact data per network** | Column Name |
 Description  | Data Type | Units  | | :------------------------------- |
 :------------------------------------------------------------------------------------------------------------------------------------------- | :--------- | :--------------------------------- | | net.id | Unique identifier assigned to each ecological network (see Fricke and Svenning, 2020) | Text | - | | weighted\_z | Trait matching between plant fruit size and frugivore body mass, calculated from all unique species interactions in plant-frugivore networks | Continuous | Weighted z-transformed Pearson’s r | | latitude | 
 
 | Continuous | Decimal degrees (°) | | longitude | 
 
 | Continuous | Decimal degrees (°) | | year | Year in which the network
 was sampled | Continuous | - | | sampling\_method | The sampling method
 used to record interactions between plants and frugivores | Text | - | |
 biogeographical\_realm | The biogeographic realm where the network is
 located | Text | - | | animal\_richness | Total number of distinct animal
 species present in the network | Continuous | - | | plant\_richness |
 Total number of distinct plant species present in the network | Continuous
 | - | | interaction\_count | Total number of unique recorded interactions
 between plants and frugivores in the network | Continuous | - | |
 avg\_frugivory\_per\_site | Average degree of frugivory across all
 plant-frugivore interactions | Continuous | - | | fruit\_size\_range |
 Range (max-min) of the log-transformed fruit sizes within the network |
 Continuous | - | | body\_mass\_range | Range (max-min) of the
 log-transformed frugivore body masses within the network | Continuous | -
 | | mean\_annual\_precipitation | Mean annual precipitation at 1 km
 resolution, averaged over 1981–2010 | Continuous | mm | |
 mean\_annual\_temperature | Mean annual temperature at 1 km resolution,
 averaged over 1981–2010 | Continuous | °C | | net\_primary\_productivity |
 Mean annual net primary productivity at 1 km resolution, averaged over
 1981–2010 | Continuous | g C/m² | | mean\_annual\_evapotranspiration |
 Mean annual actual evapotranspiration at 1 km resolution, averaged over
 1982–2019 | Continuous | mm | | ghm | Index of Global Human Modification
 (gHM) intensity (Kennedy et al. 2020) | Continuous | - | # Code/software
 Analytical workflow to reproduce main results from Structural Equation
 Models and Figure 3 are provided in the following files, including the R
 script and the R data to be loaded into R. *
 Analytical_workflow_Guerra_et_al._Ecol_Let.R *
 Data_Analytical_workflow_Guerra_et_al._Ecol_Let.RData ## Access
 information Other publicly accessible locations of the data: * In the
 supporting information of the article. Data was derived from the following
 sources: * Fricke, E.C. & Svenning, J.-C. (2020). Accelerating
 homogenization of the global plant–frugivore meta-network. *Nature*, 585,
 74–78. * Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H.,
 Soria-Auza, R.W., *et al.* (2017). Climatologies at high resolution for
 the earth’s land surface areas. *Sci Data*, 4, 170122. * Kennedy, C.M.,
 Oakleaf, J.R., Theobald, D.M., Baruch-Mordo, S. & Kiesecker, J.
 (2020). Global Human Modification of Terrestrial Systems. * Oskyrko, O.,
 Mi, C., Meiri, S. & Du, W. (2024). ReptTraits: a comprehensive dataset
 of ecological traits in reptiles. *Sci Data*, 11, 243. * Soria, C.D.,
 Pacifici, M., Di Marco, M., Stephen, S.M. & Rondinini, C. (2021).
 COMBINE: a coalesced mammal database of intrinsic and extrinsic traits.
 *Ecology*, 102, e03344. * Wilman, H., Belmaker, J., Simpson, J., de la
 Rosa, C., Rivadeneira, M.M. & Jetz, W. (2014). EltonTraits 1.0:
 Species-level foraging attributes of the world’s birds and mammals.
 *Ecology*, 95, 2027–2027.