Research Article |
Corresponding author: Rosa Alicia Jiménez ( rajjb315@profesor.usac.edu.gt ) Academic editor: José Monzón Sierra
© 2024 Ana Lucía Interiano, Dulce Herrera, Habibi Orellana Carrera, Nery D. Monroy R., Pavel García, Jorge Erwin López, Rosa Alicia Jiménez.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Interiano AL, Herrera D, Orellana Carrera H, Monroy R. ND, García P, López JE, Jiménez RA (2024) Interaction intensity as determinant of geographic range overlap between ant-following birds and army ants. In: Lipińska M, Lopez-Selva MM, Sierra JM (Eds) Biodiversity research in Central America. Neotropical Biology and Conservation 19(2): 137-156. https://doi.org/10.3897/neotropical.19.e117386
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Biogeography has as a central theme, which is the study of geographic ranges of species that are determined by evolutionary history, abiotic factors, and biotic interactions. Understanding the influence of biotic interactions on geographic ranges is a topic that has been little explored, especially in a way that compares species that vary in intensity of interaction. Here, we assessed interaction intensity as a determinant of geographic range overlap between ant-following birds and army ants in Mexico and Central America. We hypothesized that the intensity of the interaction between army ants and ant-following birds, obligate or facultative, predicts the overlap of geographic ranges of interacting species, as well as the extension of geographic ranges. We generated species distribution models with MAXENT and estimated the percentage of overlap between two species of army ants and 10 species of ant-following birds. Contrary to our predictions, Bayesian regression models found no support for an estimated higher range overlap for obligate ant-following birds and army ants, or wider geographic ranges for facultative ant-following bird species. However, our results suggested trends for higher percentages of range overlap between obligate ant-following birds and army ants, and for geographic ranges of facultative ant-following birds extending to areas without the presence of army ants. Our research encourages further exploration of the biogeography of biotic interactions as part of a quantitative gradient of intensities and not as qualitative categories, integrating spatial and temporal variation in the intensity of interaction.
La biogeografía tiene como tema central el estudio de las áreas de distribución, las cuales están determinadas por la historia evolutiva, los factores abióticos y las interacciones bióticas. Comprender la influencia de las interacciones bióticas en las áreas de distribución es un tema que ha sido poco explorado, especialmente en la comparación de especies que varían en intensidades de interacción. En este estudio evaluamos la intensidad de la interacción como determinante del traslape entre las áreas de distribución de aves seguidoras de hormigas y hormigas soldado en México y América Central. Hipotetizamos que la intensidad de la interacción entre las hormigas soldado y las aves seguidoras de hormigas, obligadas o facultativas, predice el traslape de las áreas de distribución de las especies que interactúan, así como la extensión de las áreas de distribución. Generamos modelos de distribución de especies con MAXENT y estimamos el porcentaje de traslape entre dos especies de hormigas soldado y diez especies de aves seguidoras de hormigas. Contrario a nuestras predicciones, los modelos de regresión Bayesiana no apoyaron un mayor traslape de áreas entre las aves obligadas seguidoras de hormigas y las hormigas soldado o áreas de distribución más amplias para las especies de aves facultativas seguidoras de hormigas. Sin embargo, nuestros resultados sugirieron tendencias; los porcentajes de traslape de áreas de distribución fueron más altos entre las aves obligadas seguidoras de hormigas y las hormigas soldado y las áreas de distribución de las aves facultativas seguidoras de hormigas fueron más amplias, extendiéndose a áreas sin la presencia de hormigas soldado. Nuestra investigación incentiva más exploración de la biogeografía de interacciones bióticas como parte de un gradiente cuantitativo de intensidades en lugar de categorías cualitativas, integrando la variación espacial y temporal en la intensidad de interacción.
Biogeography, biotic interactions, facultative, obligate, parasitism, range overlap
Biogeografía, facultativa, interacciones bióticas, obligada, parasitismo, traslape de área
Understanding the interactions that help determine the geographic ranges of species is a central topic in biogeography (
Biotic interactions are grouped into different categories based on whether the outcome is positive, negative or neutral for the species involved; additionally, species interactions can vary in intensity and be classified, for instance, as obligate or facultative, and as specialist or generalist. Evidence and theoretical expectations suggest that the overlap between geographic ranges of interacting species may predict diverse patterns, which can vary or recur among the different categories of interactions (
Biogeography of biotic interactions. Expected overlap of the geographic ranges of interacting species, considering different kinds of interactions and intensities of the interactions A competition: both competing species have a negative outcome and with high levels of competition exclude each other geographically B predation: one species has a positive outcome (blue) and the other species has a negative outcome (gray) as in the interactions predator/prey, parasite/host, herbivore/plant, Batesian mimic/model C mutualism: both interacting species have a positive outcome and (almost) complete geographic overlap is expected when the interaction is obligate D commensalism: one species has a positive outcome (blue) and the other species is neutral (gray) E higher range overlap is expected between obligate ant-following bird species and army ants than between facultative ant-following bird species and army ants.
Species distribution models (SDMs) are used to predict the potential geographic ranges of the species of interest, mainly based on occurrence data and environmental (abiotic) variables (
The effect of the intensity of interspecific interactions in determining geographic ranges has been barely explored. To date, results show that SDMs are not differently affected by the inclusion of biotic variables in both, dietary generalist and specialist species (
Army ants are mainly tropical species that inhabit forested areas of North America (
Ant-following birds are highly diverse in the Neotropics, encompassing several orders and about 41 families (
Here, we explore the biogeography of the interspecific interactions of parasitism between army ants and obligate and facultative ant-following birds. We contrast SDMs of two species of army ants against SDMs of five species of obligate ant-following birds and five species of facultative ant-following birds. Our hypothesis is that the intensity of the interaction between army ants and ant-following birds (obligate vs. facultative) is reflected in the overlap of geographic ranges between the army ants and the birds. Therefore, we predict that obligate ant-following birds show a higher overlap with the geographic range of army ants than facultative followers (Fig.
Our study region encompassed the northern Neotropics, from Mexico to the Darién Gap at the Panama-Colombia border. The northern limit of our study region corresponds with the Mexican Transition Zone (MTZ), which is located in the overlap between the Neartic and Neotropical regions. The MTZ represents a natural biogeographic barrier for many Neotropical taxa (
To test our hypothesis that the intensity of the interaction is reflected in the overlap of geographic ranges between army ants and ant-following birds, we analyzed the geographic ranges of two species of army ants and ten species of ant-following birds. We selected the two species of army ants that represent most of the army ant swarms in the region, Eciton burchellii and Labidus praedator (
Species of army ants and ant-following birds analyzed. Data points to generate species distribution models were downloaded from the Global Biodiversity Information Facility (GBIF); the number of data points downloaded varied by species, as well as the number of data points included in the models after filtering.
Species | GBIF data points downloaded | GBIF data points included | GBIF hyperlink |
---|---|---|---|
Army ants | |||
Eciton burchellii | 2541 | 202 | https://doi.org/10.15468/dl.svptv7 |
Labidus praedator | 1034 | 273 | https://doi.org/10.15468/dl.ghepdn |
Obligate ant-following birds | |||
Gymnopithys bicolor | 42 | 16 | https://doi.org/10.15468/dl.2js9kq |
Phaenostictus mcleannani | 78 | 38 | https://doi.org/10.15468/dl.xqb8wz |
Dendrocincla anabatina | 567 | 219 | https://doi.org/10.15468/dl.rcrmwc |
Dendrocolaptes sanctithomae | 143 | 86 | https://doi.org/10.15468/dl.cdnvpv |
Eucometis penicillata | 512 | 196 | https://doi.org/10.15468/dl.x38dw9 |
Facultative ant-following birds | |||
Attila spadiceus | 1025 | 536 | https://doi.org/10.15468/dl.ux84ud |
Sittasomus griseicapillus | 1225 | 472 | https://doi.org/10.15468/dl.bsq4g6 |
Ramphocaenus melanurus | 485 | 275 | https://doi.org/10.15468/dl.mm5vzs |
Henicorhina leucosticta | 1319 | 391 | https://doi.org/10.15468/dl.tgrjnw |
Habia fuscicauda | 1947 | 517 | https://doi.org/10.15468/dl.awjz3k |
We used presence data points available in digital public repositories to build species distribution models for each study species. We downloaded data for all species (ants and birds) from the Global Biodiversity Information Facility (GBIF). Specifically, we downloaded data restricted to our study region (Mexico to Panama), that were records of specimens belonging to biological collections, and that included geographic coordinates. To supplement the data points for one of the bird species (Gymnopithys bicolor), we added 20 records from The Macaulay Library (ML). From the ML, we selected records that included photographic evidence of the bird to confirm species identification. All GBIF and ML citations are available in Table
Gymnopithys bicolor geographic records from The Macaulay Library (ML) included in this study for generating the species distribution model.
No. | ML catalog number | No. | ML catalog number |
---|---|---|---|
1 | ML31564301 | 11 | ML555722431 |
2 | ML33712981 | 12 | ML559050011 |
3 | ML47880731 | 13 | ML565958121 |
4 | ML53591581 | 14 | ML566216821 |
5 | ML72199371 | 15 | ML572564301 |
6 | ML108049151 | 16 | ML576572301 |
7 | ML287666611 | 17 | ML580064621 |
8 | ML544000281 | 18 | ML580193821 |
9 | ML551267121 | 19 | ML582128301 |
10 | ML552367261 | 20 | ML583306691 |
We filtered the GBIF presence data points to obtain a final reduced and revised set of points for each species. First, we removed duplicate presence points with the same geographic coordinates. We then visualized the data points on a map to verify that they were all located on continental land and within our study region. Finally, we removed data points that placed the specimen records outside of continental land (i.e., in the ocean). The final number of presence data points for each species analyzed is reported in Table
We built species distribution models (SDMs) to explore the overlap between the geographic ranges of army ants and ant-following birds. We modeled the potential distribution range for each of the two army ant species and the ten ant-following birds in our study region.
We built the SDMs using the maximum entropy algorithm implemented in MAXENT v. 3.4.1 (
We reclassified the SDMs as presence/absence and calculated the overlap between each species of army ants against each species of ant-following bird. Using geographic information system software, we reclassified the presence probability values of the SDMs into presence and absence values (i.e., 1 and 0, respectively). We defined as presence all values above the logistic threshold for the “10 percentile training presence” as indicated in the MAXENT results; any value equal to or less than that threshold was considered as absence. Then, we proceeded to estimate the percentage of overlap between geographic ranges of army ants and ant-following birds. To test our predictions, we were specifically interested in quantifying the geographic range occupied by each species and how much of the geographic range of each species of ant-following bird overlaps with the distribution range of the army ants, both, separately by each one of the two species of army ants and combined as any species of army ants. We expected obligate ant-following birds to show a higher overlap with the geographic range of army-ants than facultative followers, and facultative ant-following birds to have wider geographic ranges than obligate followers.
We assessed how much percentage overlap in the distribution of birds and ants occurs due to the intensity of the interaction (i.e., obligate ant-following birds vs. facultative ant-following birds) using a Bayesian regression model (
P = B0 + XiB1
where P is overlap proportion among bird and ants, Xi is a categorical predictor identifying obligate ant-following bird species. Bo is a predicted parameter of overlap proportion of facultative ant-following bird species, and B1 is a parameter of variation on predicted overlap proportion if bird is an obligate ant-following bird species. Bayesian regression models were fit using Beta distribution, given that data are proportions, in the “brms” package in R (
We also evaluated how much larger areas were estimated in the SDMs due to the intensity of the interaction using a Bayesian robust regression model, given area is a continuous variable (
A = Bf + XiB + ∈
where A is the estimated area (km2), and Xi is a categorical predictor identifying obligate ant-following bird species, as before. Bf is a predicted parameter of estimated area of facultative ant-following bird species, and B is a parameter of variation on predicted estimated area if the bird is an obligate ant-following bird species. ε is t-distributed error of the model. Robust regression models were fit using Student family in the “brms” package in R (
We ran simulations to the posterior distributions on four Markov Chain Monte Carlo (MCMC). MCMC sampling of posteriors was performed in 1000 iterations by chain after 3000 warm-up iterations. We visually checked chain convergence and the scale reduction factor, R-hat < 1.1, for all parameters.
We employed species distribution models (SDMs, AUC values higher than 0.831, Suppl. material
Bayesian regression models show that the intensity of the interaction between army ants and ant-following birds (obligate vs. facultative) is not reflected in the overlap of geographic ranges between the army ants and the birds A obligate ant-following birds do not have higher estimated overlap of geographic ranges than facultative ant-following birds B facultative ant-following birds do not have wider expected geographic ranges than obligate ant-following birds.
Percentage of overlap between army ants and ant-following birds and predicted range size by Species Distribution Models (SDM) in square kilometers.
Species | % of overlap between bird and Eciton burchellii | % of overlap between bird and Labidus praedator | % of overlap among bird and two ants | Predicted area size by SDM (km2) |
---|---|---|---|---|
Obligate ant-following birds | ||||
Gymnopithys bicolor | 84.60 | 57.16 | 88.44 | 2136 |
Phaenostictus mcleannani | 80.86 | 64.04 | 87.12 | 1902 |
Dendrocincla anabatina | 69.17 | 76.71 | 92.28 | 4479 |
Dendrocolaptes sanctithomae | 68.33 | 59.36 | 83.72 | 7524 |
Eucometis penicillata | 73.90 | 79.01 | 96.84 | 2977 |
Facultative ant-following birds | ||||
Attila spadiceus | 53.44 | 48.83 | 67.19 | 9415 |
Sittasomus griseicapillus | 58.90 | 62.81 | 78.22 | 7075 |
Ramphocaenus melanurus | 66.00 | 68.75 | 88.05 | 4150 |
Henicorhina leucosticta | 76.23 | 73.65 | 88.23 | 5940 |
Habia fuscicauda | 63.56 | 60.17 | 80.93 | 6525 |
We noticed a trend of increased overlap between the geographic ranges of army ants and ant-following birds in relation to behavior, obligate ant-following birds showed higher overlap than facultative ant-following birds (Figs
Overlap of species distribution models of two species of army ants (columns; Eciton burchellii, carmine color, and Labidus praedator, caramel color) and five species of obligate ant-following birds (rows, amethyst color). Range overlap between army ants and ant-following birds is shown in lime color, and the percentage of overlap is represented numerically for each ant-bird species pair. Photo credits: G. bicolor (
Overlap of species distribution models of two species of army ants (columns; Eciton burchellii, carmine color, and Labidus praedator, caramel color) and five species of facultative ant-following birds (rows, teal color). Range overlap between army ants and ant-following birds is shown in lime color, and the percentage of overlap is represented numerically for each ant-bird species pair. Photo credits: A. spadiceus (PG), S. griseicapillus (Carlos Echeverría), R. melanurus (NDMR), H. leucosticta (RAJ), H. fuscicauda (NDMR).
Coinciding with our prediction, there was a trend for the geographic ranges of facultative bird species to be more extensive. We observed that facultative ant-following birds extended their distribution to areas where no army ants were predicted (Figs
Both obligate and facultative ant-following behaviors presented three out of five bird species with a higher percentage of overlap with E. burchellii than with L. praedator. The higher percentages of overlap of obligate birds with E. burchellii were 84.60% (G. bicolor), 80.86% (P. mcleannani), and 68.33% (D. sanctithomae); and in the facultative birds the values were 76.23% (H. leucosticta), 66.00% (Ramphocaenus melanurus), and 63.56% (Habia fuscicauda).
Although the geographic ranges of E. burchellii and L. praedator are different, they complemented each other in the study region (Figs
We studied the biogeography of interspecific interactions between army ants and obligate and facultative ant-following birds. We hypothesized that the intensity of the interaction between army ants and ant-following birds would determine the percentage of overlap of the geographic ranges of the interacting species. Contrary to our first prediction, a Bayesian regression model found no support for an estimated higher range overlap between obligate ant-following birds and army ants when compared to facultative followers, which agrees with Eltonian Noise Hypothesis (
Species interactions between army ants and ant-following birds integrate complex networks, both on the number and identity of the species in a given local assemblage and on the environmental factors that limit geographic ranges throughout their extent, which can alter the intensity of the interactions (
The classification of ant-following behavior into two categories, obligate and facultative, eliminates the gradient of the intensity of the interactions, which may have implications in determining the overlap of geographic ranges of ant-following birds and army ants. Our results of the Bayesian analysis of the estimated percentage of overlap of the geographic ranges between ants and birds show a region of intersection between both categories of intensities, challenging the classification commonly used in this field of research and showing that there is no defined threshold between obligate and facultative species (
Bird species are assigned as obligate or facultative based on local scale field studies and with our study, we attempted to transfer that local scale natural history information to the percentage of overlap between geographic ranges at the regional scale. Our findings show no support for an estimated higher range overlap between obligate ant-following birds and army ants when compared to facultative followers. The lack of support for our predictions leads us to propose that Eltonian Noise Hypothesis might partly explain our results (
As mentioned previously, the categorical classification of the intensity of interactions hides the intensity gradient over which interactions can occur, and the local spatial scale at which the intensity of interaction is determined adds up to the difficulty of moving from the local scale to the regional scale. Thus, an alternative explanation for our results is that the categories evaluated (i.e., obligate vs. facultative) do not allow the integration of quantitative values of the intensity of interaction to be able to study the overlap of geographic ranges in a continuous and non-categorical manner, and consider spatial and temporal intraspecific variation. It would be valuable to incorporate, in biogeographic studies, the spatial intraspecific variation that results from different assemblages and environments, since a bird species inhabiting different regions (e.g., Central America vs. Amazonia) can show differential intensity of ant-following behavior. Given these challenges in understanding and categorizing interaction intensities, it is essential to consider the spatial variation in interaction intensity of particular species, for instance Henicorhina leucosticta and Habia fuscicauda, two bird species generally considered as facultative ant-followers. Individuals of H. leucosticta join E. burchellii swarms in Los Tuxtlas, Mexico with a frequency of 57% (
Temporal variation in assemblages should also be incorporated, particularly in bird assemblages that go through an annual cycle with a season of residents-only and a season of resident and migratory species, since some migratory birds (e.g., Geothlypis formosa – Kentucky Warbler, Setophaga citrina – Hooded Warbler) can also join the mixed species flocks of ant-following birds in Guatemala (observations by NDMR) and Mexico (
In summary, our work assesses the intensity of interaction as determinant of geographic range overlap between ant-following birds and army ants. Bayesian regression models found no support for higher range overlap between obligate ant-following birds and army ants, compared to facultative ant-following birds, or for wider geographic ranges in facultative ant-following birds, compared to obligate ant-following birds. However, our analyses show a trend, for both, higher percentages of range overlap between obligate ant-following birds and army ants, and higher geographic ranges of facultative ant-following birds extending to areas with no army ants. Understanding the biogeography of biotic interactions, especially parasitism interactions, requires knowledge of the natural history of the species, integrated here through the comparison of species with obligate ant-following behavior and species with facultative behavior. Our results suggest that the approach to a predictive biogeography of interactions will require that biotic interactions be studied as part of a quantitative gradient of intensities and not as qualitative categories, and that spatial and temporal variation in the intensity of interaction be integrated in models to allow for inferences to be made from the local scale to the regional scale.
Special thanks to Sofia Pozuelos for her valuable contributions in reviewing and filtering data for this paper. We thank Mike Melton and Carlos Echeverría for allowing us to include their photographs in Figs
The authors have declared that no competing interests exist.
No ethical statement was reported.
No funding was reported.
Ana Lucía Interiano: conceptualization, data curation (equal), formal analysis, investigation, methodology (lead), visualization, writing – original draft, writing – review and editing. Dulce Herrera: conceptualization, data curation (equal), formal analysis, investigation, methodology, visualization, writing – original draft, writing – review and editing. Habibi Orellana Carrera: conceptualization, data curation (equal), formal analysis, investigation, methodology, visualization, writing – original draft, writing – review and editing. Nery D. Monroy R.: conceptualization, investigation, visualization, writing – review and editing. Pavel García: formal analysis (lead), methodology, visualization, writing – original draft, writing – review and editing. Jorge Erwin López: conceptualization, supervision, writing – review and editing. Rosa Alicia Jiménez: conceptualization (lead), formal analysis, investigation, methodology, project administration, supervision, validation, visualization, writing – original draft (lead), writing – review and editing.
Ana Lucía Interiano https://orcid.org/0009-0008-2057-9482
Dulce Herrera https://orcid.org/0009-0004-9033-4166
Habibi Orellana Carrera https://orcid.org/0000-0001-8619-2944
Pavel García https://orcid.org/0000-0002-1089-3557
Rosa Alicia Jiménez https://orcid.org/0000-0001-7048-730X
Global Biodiversity Information Facility downloads citations and records from The Macaulay Library are included in the main document. R code available at https://github.com/pavka17/Ant-following-bird-project.
Supplementary information
Data type: docx
Explanation note: table S1. Final sets of bioclimatic variables used to build the Species Distribution Models for each species of army ants and ant-following birds. table S2. Area under the curve (AUC) and threshold values for each species of army ants and ant-following birds.