Local functional traits question global trait data: insights from mammal communities in a fragmented Atlantic Forest landscape

Local functional traits question global trait data: insights from mammal communities in a fragmented Atlantic Forest landscape | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Oikos This is a preprint and has not been peer reviewed. Data may be preliminary. 23 June 2025 V1 Latest version Share on Local functional traits question global trait data: insights from mammal communities in a fragmented Atlantic Forest landscape Authors : Maria Regiolli Godoi 0009-0001-1226-288X [email protected] , F.Z. Farneda 0000-0001-6765-2861 , Alan Pereira , Marcos Akira-Umeno , Fernanda Marques , and Marcos Lima 0000-0002-5901-0911 Authors Info & Affiliations https://doi.org/10.22541/au.175067495.56857433/v1 422 views 317 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Accurate functional trait data are critical for assessing ecosystem services and processes in fragmented landscapes. We evaluated whether the global EltonTraits 1.0 database adequately represents the functional structure of mammal communities in forest fragments and restoration sites in a highly fragmented Atlantic Forest landscape. We compared the local data on the frequency of occurrence of 30 mammal species (recorded via camera traps) and their locally compiled trait values (from 118 studies) with those from the global trait database. We focused on three key traits (diet, foraging stratum, and activity cycle), and tested the associations between local and global trait sets using species-level functional uniqueness (¯K_i), community-weighted means (CWM), functional diversity (Rao’s Q), and community-level functional uniqueness (U). Compared to global trait datasets, we found: (i) 85% of species in fragments and 77% in restoration forests showed higher ¯K_i with local traits; (ii) CWM values differed significantly between local and global datasets, particularly for crepuscular activity, scansorial/ground-aquatic foraging, and several dietary components, with local data capturing a broader range of ecological strategies across habitats; (iii) global data underestimated Rao’s Q and U in both habitats, suggesting trait convergence in global datasets masking local-scale variation. These gaps arise because the EltonTraits 1.0 database likely aggregates many trait values from pristine ecosystems, inflating niche space, while local communities face multiple effects of environmental filtering. Additionally, species with wide geographic distributions may exhibit greater intraspecific trait variation, which is often averaged in global datasets, potentially contributing to mismatches. Our findings indicate that depending on global data can risk underestimating the roles of specialized species in fragmented ecosystems, emphasizing the necessity for conservation strategies adapted to local-scale data in tropical landscapes. Our results also highlight the importance of integrating local trait information into functional ecology metrics to avoid biased assessments of community structure. Introduction In recent decades, biodiversity has gained prominence as a central focus of ecological research, with studies such as the Millennium Ecosystem Assessment (2005) and Cardinale et al . (2012) systematizing its critical role in sustaining ecosystem processes and services. At the core of this understanding are functional traits, that is, morphological, physiological, or behavioral characteristics that determine a species’ performance in terms of survival and reproduction, as well as its ecological effects (Violle et al . 2007). These traits mediate species responses to environmental change and shape their contributions to ecosystem functions, from nutrient cycling to pollination (Cadotte et al . 2011). To organize these trait values across scales, the rise of open-access biodiversity databases has revolutionized macroecological research by allowing extensive analyses of functional traits and species distributions (e.g., Jeliazkov et al . 2020). The development of data papers has improved transparency and reproducibility in trait-based ecology, providing detailed metadata and methodological reporting (e.g., Chase et al . 2019). While these resources are crucial for cross-scale spatial comparisons, their effectiveness depends on the representativeness of the underlying data, which may be biased towards well-studied taxa or protected ecosystems (Hughes et al . 2021). Local-scale studies, especially in human-modified landscapes, complement these efforts by capturing trait variations influenced by recent environmental filters (Cox et al . 2021, Devarajan et al . 2025). It is also important to distinguish data papers that focus on time series and local assemblages (e.g., BioTIME – Dornelas et al. 2025) from those that compile species-level mean trait values across broad spatial scales, such as EltonTraits (Wilman et al. 2014). It is this latter category of species-level aggregated trait databases that forms the core of our investigation, in which we assess the applicability of broad-scale trait data to address ecological questions at local scales. In tropical regions like the Atlantic Forest, recent environmental filters associated with anthropogenic landscapes are expected to influence ecological functions and ecosystem processes. More than 80% of the Atlantic Forest original vegetation has been cleared (Ribeiro et al . 2009) and 97% of its fragments are smaller than 50 ha (Vancine et al . 2024). Consequently, isolated patches will be influenced by environmental filters that favor species with traits adapted to human-modified ecosystems (Bogoni et al . 2018, Magioli et al . 2021). However, functional trait data are often derived from global databases such as EltonTraits 1.0 (Wilman et al . 2014), which may overlook local adaptations emerging in rapidly changing landscapes due to their coarse spatial resolution. Although these databases provide an invaluable baseline for macroecological studies, they may be inadequate for analysis focused on local scale or highly fragmented landscapes. Globally, large mammals face disproportionate extinction risks due to their expansive home ranges, slow reproduction, and sensitivity to fragmentation and habitat loss (Ripple et al . 2017, Ceballos et al . 2020). Large mammals have important ecological roles in ecosystems (Larcher et al . 2019), they help regulate food webs (through top-down and bottom-up processes) as predators and primary consumers (Pringle et al . 2023). Frugivores and herbivores can regulate nutrient cycling (Villar et al . 2021), affecting key ecological services such as carbon storage (Schmitz et al . 2018). Additionally, some mammals species act as ecosystem engineers due to their ability to structurally modify habitats (Larcher et al . 2019, Rodrigues et al . 2020). For example, Neotropical species like peccaries and armadillos overturn soil while foraging, reducing soil compaction, creating wallows, and bringing deeper soil and nutrients to the surface (Rodrigues et al . 2020, Villar et al . 2021). However, these behaviors and ecological functions depend on access to large areas of pristine habitats, a growing challenge as human activities fragment landscapes and shrink species’ ranges (Dirzo et al . 2014, Ripple et al . 2017), leading to a reduction in the ecological functions they provide (Magioli et al . 2021). Furthermore, the relationship between traits and ecosystem roles can vary substantially between broad-scale datasets and region-specific populations (Shelomi and Zeuss 2017, Fan et al . 2019). This mismatch raises a pivotal question: To what extent can global trait databases effectively represent the local functional structure of mammal communities in highly fragmented tropical landscapes? In this study, we address this question by comparing functional traits from a global dataset with a locally compiled dataset based on species occurrence frequencies in forest fragments and restoration sites within the Atlantic Forest, a biodiversity hotspot where fragmentation threatens endemic mammal species (Bogoni et al . 2018, Ribeiro et al . 2009). By quantifying species-level functional uniqueness (\({\overline{K}}_{i}\)), community-weighted mean trait values (CWM), and functional diversity metrics (Rao’s Q and community-level functional uniqueness U ) separately for forest fragments and restoration sites, we aim to identify how reliance on global trait data disproportionately skews conservation priorities in fragmented landscapes. We hypothesize that in restoration sites and forest fragments, where multiple ecological filters are operating, traits shaped by local ecological pressures (e.g., diet plasticity) will show greater divergence between global and local trait datasets. Furthermore, circadian activity patterns may also show greater divergence, reflecting behavioral adjustments to anthropogenic disturbances (Gálvez et al. 2021, Prado et al. 2021). Conversely, evolutionarily conserved traits, such as foraging habits, are expected to remain more consistent across datasets in both habitats. By quantifying mismatches between local and global trait patterns, our findings highlight the need to harmonize fine-scale data with global repositories to inform habitat-specific management strategies in hyper-diverse tropical ecosystems undergoing simultaneous forest degradation and recovery. math_shortcuts Material and Methods math_shortcuts Study area The study was carried out in nine ecological restoration sites consisting of early-stage secondary forest (~13 years of regrowth) and seven forest fragments in the Semideciduous Atlantic Forest of northern Paraná and southwestern São Paulo, Brazil (Fig. 1; Table S1; see Marques and Anjos 2023). This region is characterized by high levels of forest fragmentation, with a landscape dominated primarily by industrial-scale monocultures of soybean, corn, and sugarcane (Soares and Medri 2002). The climate is humid subtropical mesothermal (Cfa; Peel et al . 2007), with a mean annual temperature of 21°C and average annual rainfall of 1,450 mm. Restoration forest areas were established between 2002 and 2005 through controlled, human-assisted regeneration using native early-successional and secondary arboreal species. These sites, along with adjacent forest remnants, are now integrated into a long-term ecological monitoring initiative under the “Atlantic Forest of Northern Paraná Long-Term Ecological Research Network (PELD-MANP)”. Fig. 1. Study area and sampling design for medium- and large-sized mammal surveys. South American continent highlighting Brazil and Paraná and São Paulo states (yellow), and detailed map of the study region showing seven forest fragments (F1–F7), nine ecological restoration sites (RF1–RF9), and surrounding land cover types. All sampling sites are embedded within the Semideciduous Seasonal Atlantic Forest. Mammal field surveys Sampling was conducted between September 2015 and June 2017. In each forest fragment and reforestation site, sampling points were established 100 meters apart along either a 500-meter transect (6 points) or a 1,000-meter transect (12 points), depending on the area and shape of each site (see Supplementary Material Table S1). Each site was treated as a single sampling unit (Table S1) to ensure sufficient sampling effort while avoiding pseudoreplication. Two recording methods were applied alternately across the sampling points, meaning that each point employed only one method: (i) footprint tracking using sand plots or (ii) visual detection using camera traps. Each large mammal species (≥1 kg) was recorded only once within a 24-hour period at each sampling unit (see Marques and Anjos, 2023 for more information). Species occurrence frequencies were calculated and are provided as Supplementary Material (Table S2). Mammal functional traits We focused on three functional traits (diet, foraging stratum, and activity cycle) due to their importance in Neotropical mammal ecology, particularly their roles in ecosystem functioning (e.g., seed dispersal, predation dynamics) and responses to forest fragmentation (Mello et al . 2011). To synthesize local functional trait data for our study area, we conducted a systematic review (Lortie 2014) using comprehensive searches in SCIELO and Google Scholar (accessed June 2021). Searches combined scientific mammal species names with keywords such as “diet”, “ecology”, “Atlantic Forest”, and “Brazil”, with no date restrictions. After screening titles, abstracts, and full texts, 118 peer-reviewed studies were retained for analysis (see Supplementary Material, Appendix 1). For global comparisons, we used the EltonTraits 1.0 database (Wilman et al . 2014), which contains functional trait data for 5,400 mammal species. Local trait data were standardized to match EltonTraits protocols, that is, diet percentages were averaged across studies, while categorical traits (foraging stratum, activity cycle) were converted to binary variables (1 = present, 0 = absent; Table 1). Table 1. Functional traits of mammal species evaluated in forest fragments and restoration forests across the Atlantic Forest for the local and global datasets. Diet Proportional consumption of ten food resources: invertebrates, birds and mammals, reptiles and amphibians, fish, all vertebrates, scavengers, fruits, nectar and pollen, seeds, other vegetable elements Percentage (0-100%) Foraging stratum Primary vertical habitat use: arboreal, scansorial, ground/aquatic Presence/Absence Activity cycle Temporal activity: crepuscular, diurnal, nocturnal Presence/Absence math_shortcuts For species-level trait values, see Supplementary Material Table S3 (global dataset) and Table S4 (local dataset). Data analysis To ensure comparability between the local and global trait datasets, continuous functional trait values (diet components) were standardized to z-scores (mean = 0, standard deviation = 1) using the ”scale” function (R package FD; Laliberté and Legendre 2010). For species-level functional uniqueness (\({\overline{K}}_{i}\)) and functional indices (Rao’s Q and community-level functional uniqueness U ), we calculated Gower distances to accommodate mixed data types (quantitative diet percentages and categorical activity/foraging traits). Distances were derived using the ”gawdis” function (R package Gawdis; de Bello et al . 2021), with settings ”w.type = optimized” and ”opti.maxiter = 300” to balance trait contributions. Species-level functional uniqueness (\({\overline{K}}_{i}\)) was calculated to quantify how distinct each species’ trait combination is relative to other species in the community, considering both datasets. The \({\overline{K}}_{i}\) was computed with frequency occurrence data using the “uniqueness” function (Ricotta et al . 2016). Community-weighted mean trait values (CWM) were computed to evaluate shifts in trait composition between datasets (Lavorel et al . 2008). The ”functcomp” function (R package FD; Laliberté and Legendre 2010) was used to calculate CWM, weighted by species frequency occurrence data. Pairwise comparisons of each trait based on local vs. global datasets were tested with paired permutation tests (9999 randomizations; Broman 2022). To quantify functional α diversity, we applied Rao’s quadratic diversity index ( Q ), which accounts for trait-based variance among species pairs. Taxonomic α diversity was assessed using the Simpson index ( D ), a metric that treats all species as maximally dissimilar (Botta-Dukát 2005). Notably, Q represents a functional extension of D , as both indices share mathematical foundations, they incorporate species frequency occurrence data and pairwise dissimilarities. We further derived community-level functional uniqueness ( U ) by calculating the ratio Q/D (Ricotta et al . 2016). Statistical comparisons of these indices ( Q , D , and U ) between local vs. global datasets were conducted separately for forest fragments and restoration forest using paired permutational tests with 9,999 randomizations. The calculations of D , Q and U were also performed with the “uniqueness” function provided by Ricotta et al . (2016). All analyses were conducted in R version 4.3.2 (R Core Team 2023). Results Despite equal species richness (n = 26) in forest fragments and restoration sites, species-level functional uniqueness (\({\overline{K}}_{i}\)) differed markedly between habitats and trait datasets. Local trait data displayed higher \({\overline{K}}_{i}\)compared to global trait data for 85% of species (22/26) in fragments and 77% (20/26) in restoration sites (Fig. 2). These trends persisted at the community level: mean \({\overline{K}}_{i}\) was significantly higher locally (fragments: 0.323 ± 0.049; restoration: 0.297 ± 0.044) than globally (fragments: 0.273 ± 0.032; restoration: 0.257 ± 0.029). Variation occurred among species and habitats. For example, Mazama americana (forest fragments), Nasua nasua (restoration sites), and Procyon cancrivorus (both habitats) showed minimal divergence between local and global trait datasets. In contrast, Herpailurus yagouaroundi (forest fragments), Leopardus wiedii (both habitats), and Tamandua tetradactyla (both habitats) exhibited pronounced local-global differences (Fig. 2). Fig. 2. Ranking of functional uniqueness \({\overline{K}}_{i}\)for 30 mammal species in the Atlantic Forest, comparing local (green circles) and global (orange; EltonTraits 1.0) trait datasets. Species were sampled in forest fragments (n = 26) and restoration sites (n = 26), with 22 species shared between habitats. Greater horizontal distance between paired circles indicates stronger divergence in\({\overline{K}}_{i}\) values between local and global trait data. Community-weighted mean (CWM) trait values differed significantly ( P < 0.05) between local and global (EltonTraits 1.0) datasets, with variation further influenced by habitat (Fig. 3). In forest fragments, significant divergence occurred in crepuscular activity, scansorial/ground-aquatic foraging stratum, and dietary categories (granivory, nectarivory, frugivory, scavenging, and consumption of mammals/birds and all vertebrates). Restoration sites also exhibited broad divergence, spanning all major dietary categories (granivory, nectarivory, scavenging, and consumption of fish, invertebrates, and reptiles/amphibians), as well as scansorial/ground-aquatic foraging strategies, and crepuscular activity (Fig. 3). Notably, five of the nine significant traits from both forest fragments and restoration sites were more prevalent in the local dataset than in the global dataset. Fig. 3. Divergence in functional trait composition between local (green) and global (orange; EltonTraits 1.0) datasets for mammal communities in Atlantic Forest fragments and restoration sites. Community-weighted mean (CWM) values are shown for diet, foraging stratum, and temporal activity. Traits with significant differences (paired permutation tests; P < 0.05) are marked with asterisks (*) and bold labels. Boxplots depict medians (horizontal lines), interquartile ranges (colored bars), and data ranges (vertical lines). Data include a total of 30 species, with 26 sampled per habitat (22 shared). Both habitats exhibited similar levels of taxonomic diversity, as indicated by Simpson’s index ( D ; forest fragments = 0.85; restoration sites = 0.81; Fig. 4). Functional diversity, measured by Rao’s quadratic entropy ( Q ), was significantly higher for the local trait dataset than for the global dataset (EltonTraits 1.0) in both forest fragments and restoration sites (paired permutation tests; P < 0.05). Similarly, community-level functional uniqueness ( U ) was significantly greater for the local trait dataset than for the global dataset in both habitats ( P < 0.05; Fig. 4). Fig. 4. Differences in functional diversity (Rao’s quadratic entropy, Q ) and functional uniqueness ( U ) between local (green) and global (orange; EltonTraits 1.0) trait datasets in Atlantic Forest fragments and restoration sites. U was derived from Simpson’s index ( D ) using U = D/Q . Significant differences (paired permutation tests; P < 0.05) are marked with asterisks (*). Boxplot: medians (horizontal lines), interquartile ranges (color bars), and data ranges (vertical lines). Discussion Our findings reveal complementary strengths and limitations of local and global functional trait datasets, with critical implications for understanding biodiversity in fragmented ecosystems. While both datasets captured core trait patterns, we found context-dependent divergences. Traits shaped by local ecological pressures (diet) and evolutionarily conserved traits (activity cycles, foraging strata) varied significantly between the scales. Even traits typically assumed to be phylogenetically constrained showed contextual plasticity under extreme forest fragmentation. Species-level functional uniqueness showed similar patterns of divergence, with forest fragments and restoration sites presenting higher \({\overline{K}}_{i}\) when local functional trait dataset was used. This suggests that when \({\overline{K}}_{i}\) is calculated using locally measured traits (i.e., traits quantified from species within or near each study site), functional diversity exceeds estimates derived from the global trait databases. A similar pattern emerged for community-weighted means (CWM), with most traits showing higher values when local rather than global functional trait data were used in both habitats. This trend was also evident in Rao’s Q and community-level functional uniqueness U , despite communities exhibiting similar taxonomic diversity (Simpson’s D ). Together, these findings suggest that uniqueness, composition, and diversity all increase in a functional context when analyses rely on locally observed traits rather than on traits aggregated across broader spatial scales. Our results demonstrate the value of local trait datasets in improving global generalizations. The higher functional uniqueness observed when using local functional trait data underscores how environmental filtering reshapes mammal communities in fragmented ecosystems. Forest fragmentation and habitat loss can eliminate specialist species, favoring those with traits suited to novel conditions (Bogoni et al . 2018), thereby increasing functional redundancy and reducing the ecological roles of the remaining species (Brandl et al . 2016, Magioli et al . 2021). Species like H. yagouaroundi, Leopardus wiedii and Tamandua tetradactyla showed larger divergence in functional uniqueness, likely reflecting a sharp departure from global averages, particularly in forest fragments, suggesting functional adaptations context-dependent to the environmental in which they occur (Flynn et al . 2008). Conversely, in restoration forests, other filters (e.g., simplified canopies) likely drove niche shifts in taxa like Eira barbara , which may increase scansorial foraging to exploit prey across all forest strata, a behaviour absent from global databases like EltonTraits, where the species is categorized as exclusively “ground”. However, generalists such as D. albiventris , N. nasua , and P. cancrivorus showed consistent trait values across datasets, likely due to their inherent plasticity already captured in EltonTraits’ broad dietary categories. As hypothesized, some diet-related traits exhibited significant differences between datasets, reflecting species’ adaptations to local resource availability. The higher estimated predation on fish, reptiles, and amphibians in restoration forests, likely influenced by their proximity to water bodies in our study area, contrasts with the more pronounced predation on mammals and birds in forest fragments, where the persistence of terrestrial prey and more complex habitat structure may favor these interactions (Magioli et al. 2021). Species like Cerdocyon thous can adapt by increasing scavenging on carrion (e.g., roadkill) and preying on small vertebrates, such as rodents and birds (Facure et al . 2003, Rocha et al . 2008, Santiago et al . 2023). These behaviours are poorly represented in the global dataset, likely because the data were sourced from large areas of pristine forest. Temporal activity cycles and foraging strata also diverged significantly. Although we found no differences in nocturnal or daytime activities between the local and global datasets, crepuscular activity was more frequent in both habitats when CWM was calculated using the local dataset. This result suggests that anthropogenic disturbances are affecting wild species interactions and, hence, their activity patterns (Gálvez et al . 2021, Prado et al . 2021). The lower frequency of crepuscular activity observed in the global dataset may also reflect the fact that most data were collected in protected areas or easily accessible areas (Gallo et al . 2021, Hughes et al . 2021). The higher difference between scansorial and ground/aquatic foraging between local and global dataset, suggests that foraging habits may exhibit plasticity in response to local habitat structure influenced by disturbances and landscape context a pattern echoed globally in the temporal flexibility of mammalian activity, such as crepuscular shifts (Devarajan et al . 2025). Global datasets underestimated functional diversity compared to local values in both habitats, suggesting that local trait expression captures more ecological nuance. This pattern implies that global databases may underrepresent niche space by smoothing over intraspecific variation and habitat-specific adaptations. Locally, fragmented communities showed broader functional diversity and uniqueness, reflecting fine-scale responses to environmental filtering and disturbance. These mismatches highlight opportunities to harmonize scales: while global data provide standardized baselines, local data capture dynamic and context-dependent trait expression The dietary plasticity, as discussed by Gorczynski and Beaudrot (2020), is likely underrepresented in global profiles. This finding aligns with previous research showing that resource availability, predation pressure, and anthropogenic modification influence functional traits in a site-specific way (Bregman et al . 2016, Chiu‐Werner and Jones 2023, Gallo et al . 2021, Magioli et al . 2021; Requena-Mullor et al . 2016). While these patterns may reflect local adaptive strategies, they also point to the fragility of species’ long-term survival in increasingly fragmented landscapes (Cudney‐Valenzuela et al . 2023). Although local functional variation is increasingly recognized as essential for understanding ecosystem functioning (Violle et al . 2012), many ecological studies still rely on global databases due to challenges in fieldwork, such as time constraints, financial limitations, and safety concerns. However, reliance on global datasets assumes that average trait values can accurately represent local populations, which overlooks critical local variations from a functional perspective. Additionally, although global databases like EltonTraits 1.0 offer unparalleled breadth, their focus on broad applicability may not fully capture local adaptations driven by rapid environmental change. For instance, although global dietary profiles of C. thous emphasize invertebrates (comprising 50% of its diet) and vertebrates (40%), local data indicate a shift primarily toward frugivory (40%) and a more omnivorous diet overall (see Tables S3 and S4), likely driven by vertebrate and invertebrate scarcity in fragmented habitats. Additionally, species with broad geographic distributions often exhibit substantial intraspecific trait variation, which is typically averaged in global databases. This averaging may inflate estimates of functional niche breadth, particularly when local environmental filters limit trait expression. Such discrepancies highlight the need for ”trait databases 2.0” that integrate intraspecific variation and landscape context, bridging scale-dependent gaps in trait-environment relationships. math_shortcuts Conservation implications Our results have implications for conservation in the Atlantic Forest, where > 95% of remnants are < 50 ha (Vancine et al . , 2024). Our results highlight the synergy between local and global data in conservation planning. For example, combining global baselines (e.g., scansorial foraging in Leopardus wiedii ) with local observations (e.g., increased ground activity in small forest fragments) can improve corridor design by accommodating species’ adaptive behaviors. To achieve this, we propose (i) leveraging global databases to identify priority traits, (ii) ground-truthing these traits with local data to detect plasticity, and (iii) expanding community-based monitoring to capture real-time trait shifts. Furthermore, future studies comparing local and global datasets should integrate abundance-weighted metrics to disentangle whether high uniqueness stems from rare specialists or sampling bias. Supporting Information Additional supplementary material can be found online in the Supporting Information section. Data Availability Species occurrence frequency for each sampling site: available as Supporting Information online (Table S2). Species traits data obtained from Elton Traits 1.0 (Wilman et al. 2014): available as Supporting Information online (Table S3). Species traits data obtained from local literature: available as Supporting Information online (Table S4). References Bogoni, J. A., Pires, J. S. R., Graipel, M. E., Peroni, N., Peres, C.A. 2018. Wish you were here: How defaunated is the Atlantic Forest biome of its medium- to large-bodied mammal fauna? – PLoS One 13: 1–23. https://doi.org/10.1371/journal.pone.0204515. Botta-Dukát, Z. 2005. 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Farneda 0000-0001-6765-2861 Universidade Estadual de Londrina View all articles by this author Alan Pereira Universidade Estadual do Parana View all articles by this author Marcos Akira-Umeno Universidade Estadual de Londrina View all articles by this author Fernanda Marques Universidade Estadual de Londrina View all articles by this author Marcos Lima 0000-0002-5901-0911 Universidade Estadual de Londrina View all articles by this author Metrics & Citations Metrics Article Usage 422 views 317 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Maria Regiolli Godoi, F.Z. Farneda, Alan Pereira, et al. Local functional traits question global trait data: insights from mammal communities in a fragmented Atlantic Forest landscape. Authorea . 23 June 2025. DOI: https://doi.org/10.22541/au.175067495.56857433/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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