Quantifying shortfalls in the knowledge on Neotropical Auchenipteridae fishes

Freitas, Tiago Magalhães da Silva; Stropp, Juliana; Calegari, None Bárbara; Calatayud, Joaquín; Marco, Paulo De; Montag, Luciano Fogaça de Assis; Hortal, Joaquín

doi:10.1111/faf.12507

Cited by 24 publications

(9 citation statements)

References 93 publications

(225 reference statements)

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“…Despite this importance, morphological information for 43 ant species is entirely absent, and about 12% of the morphological matrix required data imputation for some trait value. The absence or constraints in available morphological data can affect our knowledge about the evolution, diversity and relationships among traits, and ultimately compromise efficient conservation of species and ecosystems (Hortal et al 2015, Freitas et al 2021).…”

Section: Discussionmentioning

confidence: 99%

A large‐scale assessment of ant diversity across the Brazilian Amazon Basin: integrating geographic, ecological and morphological drivers of sampling bias

et al. 2022

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Tropical ecosystems are often biodiversity hotspots, and invertebrates represent the main underrepresented component of diversity in large-scale analyses. This problem is partly related to the scarcity of data widely available to conduct these studies and the lack of systematic organization of knowledge about invertebrates' distributions in biodiversity hotspots. Here, we introduce and analyze a comprehensive data compilation of Amazonian ant diversity. Using records from 1817 to 2020 from both published and unpublished sources, we describe the diversity and distribution of ant species in the Brazilian Amazon Basin. Further, using high-definition images and data from taxonomic publications, we build a comprehensive database of morphological traits for the ant species that occur in the region. In total, we recorded 1067 nominal species in the Brazilian Amazon Basin, with sampling locations strongly biased by access routes, urban centers, research institutions and major infrastructure projects. Large areas where ant sampling is non-existent represent about 52% of the basin and are concentrated mainly in the northern, southeastern and western Brazilian Amazon. We found that distance to roads is the main driver of ant sampling in the Amazon. Contrary to our expectations, morphological traits had lower predictive power in predicting sampling bias than purely geographic variables. However, when geographic predictors were controlled, habitat stratum and traits contribute to explain the remaining variance. More species were recorded in better-sampled areas, but species richness estimation models suggest that areas in southern Amazonian edge forests are associated with especially high species richness. Our results represent the first traitbased, large-scale study for insects in Amazonian forests and a starting point for macroecological studies focusing on insect diversity in the Amazon Basin.

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Section: Discussionmentioning

confidence: 99%

A large‐scale assessment of ant diversity across the Brazilian Amazon Basin: integrating geographic, ecological and morphological drivers of sampling bias

et al. 2022

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“…It follows that these landscape-sampling gaps compromise our ability to understand how species respond to changes in habitat size. The lack of well-sampled inventories from small and disconnected forest fragments highlights the importance of assessing the quality and coverage of the available biodiversity data before conducting large-scale analyses in macroecology and conservation ( Hortal, Lobo & Jiménez-Valverde, 2007 ; Rocchini et al, 2011 ; see also Stropp et al, 2016 ; Ronquillo et al, 2020 ; Freitas et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Knowledge gaps hamper understanding the relationship between fragmentation and biodiversity loss: the case of Atlantic Forest fruit-feeding butterflies

Sobral‐Souza

Stropp

Santos

et al. 2021

PeerJ

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Background A key challenge for conservation biology in the Neotropics is to understand how deforestation affects biodiversity at various levels of landscape fragmentation. Addressing this challenge requires expanding the coverage of known biodiversity data, which remain to date restricted to a few well-surveyed regions. Here, we assess the sampling coverage and biases in biodiversity data on fruit-feeding butterflies at the Brazilian Atlantic Forest, discussing their effect on our understanding of the relationship between forest fragmentation and biodiversity at a large-scale. We hypothesize that sampling effort is biased towards large and connected fragments, which occur jointly in space at the Atlantic forest. Methods We used a comprehensive dataset of Atlantic Forest fruit-feeding butterfly communities to test for sampling biases towards specific geographical areas, climate conditions and landscape configurations. Results We found a pattern of geographical aggregation of sampling sites, independently of scale, and a strong sampling bias towards large and connected forest fragments, located near cities and roads. Sampling gaps are particularly acute in small and disconnected forest fragments and rare climate conditions. In contrast, currently available data can provide a fair picture of fruit-feeding butterfly communities in large and connected Atlantic Forest remnants. Discussion Biased data hamper the inference of the functional relationship between deforestation and biodiversity at a large-scale, since they are geographically clustered and have sampling gaps in small and disconnected fragments. These data are useful to inform decision-makers regarding conservation efforts to curb biodiversity loss in the Atlantic Forest. Thus, we suggest to expand sampling effort to small and disconnected forest fragments, which would allow more accurate evaluations of the effects of landscape modification.

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“…An example is the intensely sampled area surrounding the capital of the state of Amazonas (lowest coefficients in Figure 2c), where traditional ichthyological research centres are located (e.g. National Institute of Amazonian Research, INPA) (Freitas et al., 2021; Zuanon et al., 2016). These results highlight the importance of research centres as vectors for biodiversity samplings and scientific development (e.g.…”

Section: Discussionmentioning

confidence: 99%

Non‐stationary drivers on fish sampling efforts in Brazilian freshwaters

Almeida

Tessarolo

Nabout

et al. 2021

Diversity and Distributions

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Aim Closing knowledge gaps in species taxonomy and distribution (i.e. Linnean and Wallacean shortfalls, respectively) require spatially distributed high‐quality data. However, studies on terrestrial taxa have shown that occurrence data are biased owing to higher sampling efforts towards areas with greater accessibility, research infrastructure and attractiveness. Here, we tested whether these biasing factors are also important drivers of freshwater fish species research by assessing fishes’ sampling efforts in Brazil, a continental‐sized and megadiverse country. We hypothesized that the influence of biasing factors is scale‐dependent, with differential effects across regions, that is that they present non‐stationarity. Location Brazil. Methods We modelled sampling events of fish (gathered from online databases) as a function of accessibility (population density, distance from access routes and density of access routes), availability of research infrastructure (distance from research centres) and attractiveness of protected areas (distance from protected areas), by using a traditional stationary model (ordinary least square models—OLS) and a model taking into account non‐stationarity (geographically weighted regression—GWR). Results We recorded 43,538 sampling events distributed across Brazil. Freshwater fish samplings were spatially biased with a tendency for major efforts to be concentrated in sites with a higher density of access routes, population and nearness to research centres and protected areas. However, GWR models performed better than the OLS model, revealing the non‐stationarity of the effects of predictors in explaining the number of sampling events. Main conclusions Overcoming Linnean and Wallacean shortfalls for freshwater fish species in megadiverse regions such as Brazil can be aided by financially supporting the sampling efforts in less accessible and less populated sites farther from research centres and well‐studied protected areas. However, the source of biasing has strong scale dependency, so that reducing a specific source of bias is not expected to have the same effectiveness in all areas.

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Quantifying shortfalls in the knowledge on Neotropical Auchenipteridae fishes

Cited by 24 publications

References 93 publications

A large‐scale assessment of ant diversity across the Brazilian Amazon Basin: integrating geographic, ecological and morphological drivers of sampling bias

A large‐scale assessment of ant diversity across the Brazilian Amazon Basin: integrating geographic, ecological and morphological drivers of sampling bias

Knowledge gaps hamper understanding the relationship between fragmentation and biodiversity loss: the case of Atlantic Forest fruit-feeding butterflies

Non‐stationary drivers on fish sampling efforts in Brazilian freshwaters

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