Skip to main content


Foraging guild structure and niche characteristics of waterbirds in an epicontinental lake in Mexico

Article metrics

  • 3655 Accesses

  • 3 Citations



It was suggested that ecological patterns can be used to infer the nature of ecological processes (i.e., competition) that structure communities. Analysis of patterns of resource partitioning under the classical niche paradigm (competitive niche differentiation in exploiting limited resources) has traditionally been used to understand the structure of communities. On the contrary, neutral theory states that patterns result from neutral processes such as stochasticity and dispersal abilities. Thus, if any ecological process gives rise to a characteristic ecological pattern, the comparative study of patterns with appropriate neutral models may reveal the magnitude of that process. In this study, we analyzed patterns of resource utilization of a waterbird community in Lake Acuitlapilco, an epicontinental lake in central Mexico. In February 2011 to January 2012, we recorded foraging behaviors of waterbird species in two niche dimensions or axes: feeding technique and foraging habitat. The pattern of resource utilization was characterized by niche breath and niche overlap.


Results showed that waterbird species in Lake Acuitlapilco were specialists in resource utilization patterns and therefore were vulnerable to fluctuations in resources, particularly feeding habitat. Niche overlaps were generally largest among species belonging to the same guild. To test competition as an ecological process that plays a role in the community structure, observed niche overlaps were compared with niche overlaps generated with null models of communities in the absence of competition using the RA4 randomization algorithm. Habitat and observed bidimensional overlaps were higher than those of randomly generated communities.


Our study suggested that other processes can be used to predict resource utilization patterns instead of competition alone, as suggested by neutral theory. Future studies analyzing the mechanisms that structure waterbird communities should include the use of null models to support their conclusions.


Bird communities that inhabit aquatic environments usually have a complex structure driven by the large number of variables that influence species interactions (Winemiller and Pianka 1990; Weller 1999; Palmer et al. 2003). Thus far, approaches generally used to understand processes organizing waterbird communities have focused on analyzing patterns of resource partitioning (Schoener 1974; Wiens 1977; Pianka 1980; Winemiller and Pianka 1990; López de Casenave et al. 2008). Research generally concluded that species with similar patterns of resource utilization (i.e., species of the same guild) are susceptible to competitive interactions that affect the community structure.

Patterns of resource utilization (either food or habitat resources) are usually analyzed in the framework of niche theory, i.e., members of the same guild similarly exploit similar resources and may be potential competitors (Root 1967; Albrecht and Gotelli 2001; Palmer et al. 2003). Thus, species of the same guild are susceptible to competitive interactions over shared resources, and in order to coexist, they should show some mechanism to reduce, but not necessarily eliminate, negative competitive interactions (Cody 1974; Simberloff and Dayan 1991).

Most studies searching for patterns of resource utilization evaluated niche breadth and niche overlap. Spatial models of niches were formalized by Hutchinson (1959) who defined niche breadth as the distance through a niche along some particular line in the niche space. In terms of particular resources, niche breadth is the range of resources used by species. Niche overlap refers to the joint use of resources by two or more species (Colwell and Futuyma 1971). Both niche breadth and niche overlap provide indirect ways to explore ecological processes such as competition over shared resources (MacNally 1983).

Schoener (1974) suggested three niche dimensions where species tend to segregate to minimize niche overlap: habitat, food type, and time of habitat occupancy. Thus, characterization of guilds through these dimensions provides information about possible interactions caused by inter- and intraspecific resource partitioning. Studies of waterbird communities have primarily focused on two of the three niche dimensions proposed by Schoener, namely habitat use and food type (Pöysä 1983; Zárate-Ovando et al. 2008; Gatto et al. 2008; López de Casenave et al. 2008), and assume that these two dimensions together suggest resource differentiation (Wiens 1989) and that both dimensions have an effect on the distribution, abundance, and species richness in wetlands (Weller 1999).

Therefore, Robinson and Holmes (1982) proposed an analogy between feeding technique (feeding behavior) and food consumed which was applied in several studies to explain the guild structure and resource partitioning of waterbird communities (Pöysä 1983; Sarrías et al. 1996; Gatto et al. 2008). The advantage of this method is that no dietary study is required for the analysis.

Whether the pattern of resource utilization detected arises from an ecological process, such as competition, is unclear until a comparative study of patterns is carried out to understand processes that underlie the community structure (MacNally 1983; Bell 2001). Under the classical niche paradigm, i.e., competitive niche differentiation resulting from exploitation of limited resources, interspecific competition over shared resources will drive the community structure (MacNally 1983; Hubbell 2006). Alternatively, neutral theory states that patterns can be the result of neutral processes such as stochasticity and dispersal ability rather than competition and niche partitioning (Bell 2001; Hubbell 2001, Hubbell 2006). Where competition results in characteristic ecological patterns, the comparative study of patterns with appropriate neutral models (null models) may reveal the degree of influence of competition on the community structure (Connor and Simberloff 1979; Strong et al. 1979; MacNally 1983; Bell 2001).

The null model is  a pattern-generating model that is based on randomization of ecological data or random sampling from a known or imagined distribution’ (Gotelli and Graves 1996). The null model tests if observed data are non-random with respect to the null hypothesis (Gotelli 2001). Thus, in the context of niche overlap and competition, null modeling allows determination of how much niche overlap could be expected in the absence of competition.

In Mexico, studies of waterbird communities are insufficient and were mostly conducted in coastal wetlands, particularly in the northwestern portion of the country. Those studies analyzed diversity, habitat use, guild structure, and migratory species (see Mellink 2005). However, studies focused on waterbird assemblies in epicontinental lakes are scarce (Ramírez-Bastida 2000; Pineda-López and Arellano-Sanaphre 2010) and largely focused on a single species (Sartor 1989; Munguía et al. 2005; Mellink and Riojas-López 2009; Luevano et al. 2010; Villamagna et al. 2010). Additionally, studies on the community structure of waterbird communities are almost non-existent (see Hernández-Vázquez 2005), and the only study that tested patterns of resource utilization with null models failed in its interpretation (Núñez et al. 2008). Additional studies of waterbirds are needed.

In this study, we evaluated guild patterns of resource utilization within waterbird communities in an epicontinental lake in central Mexico. Three niche dimensions or axes were documented: habitat use, feeding technique, and time. To assess the statistical significance of the observed patterns, we compared observed patterns to those expected under the null hypothesis. Additionally, we discuss ecological mechanisms that structure the waterbird community.


Study site

This study was conducted at Lake Acuitlapilco, in the southern part of the state of Tlaxcala (at 2,300 m in elevation), 4.5 km to the southeast of Tlaxcala de Xicohténcatl, the capital city of the state. It is located at 19°44′ ~ 19°06′N and 97°38′ ~ 98°43′W (Figure 1; INEGI 2000). The lake has a catchment basin of 10.3 km2. Average annual precipitation was 839.3 mm over a 40-year period (1967 ~ 2006; Meteorological Observatory of Tlaxcala City). The annual average volume of water drained by the catchment is 1.97 × 106 m3. The lake volume varies throughout the year because the hydrological input comes exclusively from rainfall (CONAGUA 2010). In October to May (the dry season), the lake's depth reaches a maximum of 0.80 m and a minimum area of 20 ha. In June to September (the rainy season), the lake's depth reaches a maximum of 1.80 m and a maximum area of 75 ha.

Figure 1

Location of Lake Acuitlapilco, Tlaxcala, Mexico.

Precipitation has an effect on the composition, height, and cover of vegetation within the lake and perimeter zones, and the vegetation undergoes large variations throughout the year. Cynodon dactylon (L.) Pers., Cyperus hermaphroditus (Jacq.) Standl., Gnaphalium luteo-album L., Paspalum distichum L., and Pennisetum clandestinum Hochst. ex Chiov border areas adjacent to wetlands. Uplands surrounding the lake are cultivated with corn (Zea mays L.). In the transition zone between cultivated areas and the lake, Echinochloa holciformis (Kunth) Chase and Polygonum punctatum Ell. were found. Finally, Juncus arcticus Willd. and P. punctatum Ell. were the two main floating species within the lake.

A previous study by Fonseca et al. (2012) reported a total of 36 waterbird species in Lake Acuitlapilco. Twelve were residents, 10 were migratory, and 14 were transient species or accidental records. The highest species richness and abundance were observed in winter (September to January), when most migratory species arrived. Additionally, Pérez-Crespo et al. (2013) studied temporal variations in abundances of birds in this water body. They established three seasons from matrices of the abundance and richness of species, taking into account fluctuations in the size and depth of the lake. Results from both studies showed that the lake is a highly dynamic environment and an important area for resident and migratory waterbirds.

Waterbird monitoring

A waterbird census was conducted every 15 days from February 2011 to January 2012 (24 counts in total). We used the point count method at points every 300 m along the perimeter of the lake. We counted individuals at each point within a radius of 150 m. Censuses began at 7:30 a.m., initiating from a different point count and a different direction to avoid order effects. Binoculars (10 × 50 mm) were used, and species were identified using field guides (Sibley 2003; van Perlo 2006). Observers recorded data at each point count for 10 min and recorded individuals by species feeding behavior (the first and single observation from an individual) and feeding habitat (water depth and vegetation type) according to categories described in the next section. The number of points at which we found individuals feeding varied from the dry season to the rainy season (9 ~ 13 points, Fonseca et al. 2012). In the dry season, we recorded no individuals feeding at four points.

Feeding behavior

Feeding behavior was characterized by the use of feeding techniques, following categories previously used by Pöysä (1983) and Sarrías et al. (1996): (D) diving in which a bird is completely immersed in water and is lost from sight of the observer; (PM) picking from mud in which the bird's bill is submerged in the mud and balanced from side to side; (HS) head submerged; (BS) bill submerged; (NS) neck submerged (in HS, BS, and NS, the bird might or might not be in motion); (FL) filtering in which a bird is in motion and its bill is partially submerged; (PC) picking in which a bird uses intermittent pecking movements in water, mud, or vegetation; and (UP) up-ending in which a bird is not completely submerged, in a vertical position, with its tail and legs above the water.

Feeding habitat

The feeding habitat was categorized according to Pöysä (1983), by taking into account the water depth and the presence or absence of vegetation. Water depth was measured every 3 months using a marked rope. Additionally, the depth at the shoreline and beyond was monitored monthly to follow changes in water level. Eleven habitat types were defined: the central part of open deep water of >30 cm deep with (DWV) or without (DW) emerging vegetation; the edge part of open waters, i.e., middle water, of depths >10 cm and <30 cm with (MWV) or without (MW) emerging vegetation; shoreline, i.e., shallow waters, of depths <10 cm with (SWV) or without (SW) emerging vegetation; mud with (MUV) or without (MU) emerging vegetation; dry areas with (DRVN) or without (DR) vegetation next to the shoreline; and dry areas with vegetation (DRVA) inside the lake. Each point count sample contained all of these habitat types within the radius of data observation.

Time dimension

A third dimension, time, was also evaluated. For this purpose, three seasons were established through a cluster analysis from a matrix of species and abundances (Pérez-Crespo et al. 2013). Seasons ranged from February to May (T1), May to September (T2), and September to February 2012 (T3). Data were subdivided by season, and uni- and bidimensional matrices were generated (nine seasonal matrices in total). These matrices were used to perform the overlap analysis and null models.

Data analysis

Data of species observed in at least 15 foraging records (Gatto et al. 2008) were included in the matrices (21 species of a total of 36, Fonseca et al. 2012). We also only used the first feeding behavior recorded per individual. Data were grouped into three matrices: habitat (21 species × 11 habitat variables), feeding technique (21 species × 9 feeding technique variables), and both dimensions simultaneously (21 species × 55 possible combinations of feeding technique and habitat variables). Each row of the matrix represented a different species. Each column represented a different variable (resource or niche). Entries in each cell represented counts of feeding individuals. Then, matrix entries were calculated as proportional values of observed utilization of any particular resource by a species. These proportional values were calculated by summing up counts (rows) of all resources and then dividing each resource count (an entry in the original matrix) by its total (row total). Therefore, entries in a row of final matrices would add up to 1.0 for each species. These unidimensional (habitat and feeding technique) and bidimensional matrices were used to establish guild, niche breadth, niche overlap, and null models.

Guild establishment

A cluster analysis was used to establish the guilds. Original matrices (all data) were transformed (angular transformation y = arcsine x0.5) to reduce the kurtosis of a variable's distribution. Three dendograms were constructed (habitat, foraging technique, and both dimensions together) using the unweighted pair group method with arithmetic mean (UPGMA) (Sarrías et al. 1996; Gatto et al. 2008) linked to a Euclidean distance matrix (Sarrías et al. 1996; Legendre and Legendre 1998; López de Casenave et al. 2008). The average Euclidean distance between all species pairs was used to determine the level of similarity defining groups (guilds) in both the uni- and bidimensional dendograms (Pöysä 1983; Holmes and Recher 1986; Sarrías et al. 1996; Gatto et al. 2008; López de Casenave et al. 2008). The cluster analysis and dendograms were calculated with R project package, vers. 2.15.0 (Project 2012) and the Vegan package, vers. 2.0-3 (Oksanen et al. 2012).

Niche breadth and niche overlap

Niche breadth (for each species) and niche overlap (between all pairs of species) were calculated using the aforementioned uni- and bidimensional matrices (with untransformed data). The niche breadth of a species was estimated with the index of Levins (1968)): B = (1 / ΣP i 2), where P is proportional to each resource of a particular species. B is maximal when there is at least a count in each column and is minimal when all counts are in a column. As this index places species along a continuum from generalist to specialist, data were not subdivided by season in this calculation. Niche overlaps were calculated for all data (three matrices), and then niche overlaps were explored by season (nine matrices). The two results were compared.

Niche overlap was calculated with the index of Pianka (1973)): O jk  = (Σp ij p ik ) (Σp ij 2 p ik 2)-1/2, where p ij and p ik are proportional values of utilization of resource i by species j and k, respectively. Pianka's index is symmetrical and assumes values ranging from 0 (no resources used in common between two species) to 1 (complete overlap in resource use).

Null models

To assess whether the observed patterns in niche overlap differed from patterns of random communities, we compared the mean of observed niche overlap with the mean of niche overlap of communities in the absence of competition. Null models (1,000 iterations) of communities were generated. Null models were calculated with the software EcoSim Professional, vers. 1 (Entsminger 2012), using the RA4 randomization algorithm. As waterbird morphology limits the habitat and feeding techniques used, the RA4 algorithm was chosen to preserve the observed niche. The RA4 algorithm retains the niche breadth (values of rows) of each species and fixes zero states to their observed values. Thus, only non-zero values are reshuffled within each row. Therefore, any differences between the observed data and the null model are above and beyond those imposed by morphological constraints. This algorithm is very conservative as it maintains the structure of the original matrix and produces niche overlap values closer to those of the actual data (Jaksic and Medel 1990; Winemiller and Pianka 1990;Albrecht and Gotelli 2001,1990). Consequently, if the observed mean statistically differs (higher or lower) from the expected mean, the results reveal significant overlap patterns (Albrecht and Gotelli 2001). Observed niche overlap that is higher than the expected level of overlap further implies either that species are sharing a niche (i.e., flocking behavior or clumped resources), a lack of competition, or a strong competition that has not yet led to divergence in resource use. Conversely, observed niche overlap lower than expected implies interspecific competition and resource partitioning (i.e., dispersed resources; Gotelli and Graves 1996).



Results of the cluster analysis of feeding techniques suggested that an average Euclidean distance of 1.112 reliably defined species groups. This resulted in three guilds: (T1) divers, (T2) pickers, and (T3) generalists (Figure 2a). Furthermore, the habitat use matrix analysis suggested that an average Euclidean distance of 1.058 split species into four guilds: (H1) deep-water birds, (H2) medium-water birds, (H3) shallow-water birds, and (H4) generalist birds in waters with vegetation of both the peripheral and interior zones (Figure 2b). Guild characteristics were determined using a table of frequency of habitat use and feeding technique for each bird species (Figures 3 and 4).

Figure 2

Cluster analysis of waterbird species by niche dimension: (a) feeding technique and (b) habitat use. The average Euclidean distances between all species pairs are marked with a dashed line (feeding technique = 1.112; habitat use = 1.058). Guild codes for feeding technique are (T1) divers, (T2) pickers, and (T3) generalists, and codes for habitat use are (H1) deep-water birds, (H2) medium-water birds, (H3) shallow-water birds, and (H4) generalist birds in waters with vegetation in both peripheral and interior zones.

Figure 3

Percentages of utilization of various feeding techniques by waterbird species. Feeding technique codes are (D) diving, (PM) picking from the mud, (HS) head submerged, (BS) bill submerged, (NS) neck submerged, (FL) filtering, (PC) picking, and (UP) up-ending. Guild codes are (T1) divers, (T2) pickers, and (T3) generalists.

Figure 4

Percentages of utilization of various habitats by waterbird species. Habitat use codes are (DW) deep waters of >30 cm deep without emerging vegetation, (DWV) deep waters of >30 cm deep with emerging vegetation, (MW) medium waters of >10 cm and <30 cm deep without emerging vegetation, (MWV) medium waters of >10 cm and <30 cm deep with emerging vegetation, (SW) waters of <10 cm deep without emerging vegetation, (SWV) waters of <10 cm deep with emerging vegetation, (MU) mud without emerging vegetation, (MUV) mud with emerging vegetation, (DR) dry areas without vegetation, (DRVA) dry areas with vegetation away from the periphery of the lake, and (DRVN) dry areas with vegetation near the periphery of the lake. Guild codes are (H1) deep-water birds, (H2) medium-water birds, (H3) shallow-water birds, and (H4) generalist birds in waters with vegetation in both peripheral and interior zones.

When we examined both niche dimensions combined (feeding technique and habitat use) and an average Euclidean distance of 1.314, four guilds were established (Figure 5): (G1) divers; (G2) pickers in water, mud, and vegetation; (G3) pickers with neck submerged; and (G4) generalists.

Figure 5

Cluster analysis of waterbird species by both niche dimensions (feeding technique and habitat use). The average Euclidean distance between all species pairs is indicated by a dashed line (mean = 1.314). Guild codes for the obtained guilds are (G1) divers; (G2) pickers in water, mud, and vegetation; (G3) pickers with neck submerged; and (G4) generalists.

Composition of guilds

The guild of divers (G1) was comprised of Oxyura jamaicensis and Podiceps nigricollis. To obtain food, these bird species dive in deep water without emergent vegetation. Both species show great specialization in using deep waters to feed. Pickers in water, mud, and vegetation comprised guild G2 and were egrets, ibises (Bubulcus ibis, Egretta thula, and Plegadis chihi), and shorebirds (Himantopus mexicanus, Tringa flavipes, Limnodromus scolopaceus, Charadrius vociferus, Actitis macularius, and Calidris minutilla). These wading species particularly fed in areas of shallow water with vegetation and occasionally in cultivated areas adjacent to the lake.

Guild G3 was comprised of bird species that made intermittent peak movements in water, mud, or vegetation to seek prey but, in deep waters, typically caught prey by submerging their necks. These birds were Leucophaeus pipixcan, Phalaropus tricolor, Gallinula galeata, Fulica americana, and Anas cyanoptera.

Finally, G4 included five generalist duck species that captured prey by submerging their bill, head, and neck in deep and shallow waters. These generalist birds were Anas acuta, Anas discors, Anas clypeata, Anas crecca, and Anas platyrhynchos.

Niche measurements

Niche breadth by species for each of the niche dimensions (feeding technique and habitat) and for the bidimensional niche was calculated (Table 1). In general, the niche breadth was lower for feeding technique than for habitat use. Guilds G3 and G4 showed higher niche breadths for the three dimensions than the community. These two guilds showed great flexibility in habitat use and feeding technique.

Table 1 Niche breadth (Levins’ index) of waterbird species calculated from the three niche dimensions used

Niche overlaps for matrices (uni- and bidimensional) were calculated to assess the similarity in yearly patterns of resource utilization among species (Tables 2 and 3). Mean niche overlaps for all pairs of species were 0.48 for feeding technique, 0.42 for habitat use, and 0.19 for both dimensions. Niche overlaps between species of a particular guild were higher than those between other species (Table 4). Species belonging to guild G4 overlapped less than the remaining species in other guilds in all dimensions. The overall pattern in the community was higher niche overlap between species of a guild and also reduced values of bidimensional niche overlap with respect to unidimensional overlap.

Table 2 Niche overlap values of waterbird species calculated from feeding technique and habitat use as niche dimensions
Table 3 Niche overlap values of waterbird species calculated by considering both niche dimensions together
Table 4 Total and mean overlap values for species within guilds, for each guild, and for all species

Afterward, seasonality patterns were explored (Table 4, see Additional file 1). The composition of guilds was not constant between seasons (Additional file 1), and mean niches by guild overlap changed between seasons. Guild 4 overlapped less than species of other guilds. A similar annual pattern was observed in seasonality overlaps. First, overlaps between species of a guild were higher than the mean overlap of the entire community (Figure 6). Second, bidimensional overlaps tended to be lower than unidimensional overlaps.

Figure 6

Histogram comparing the mean overlaps from the observed (dashed arrows) and generated communities (solid arrows). With the RA4 algorithm and Pianka index with 1,000 iterations. (A) Feeding technique overlaps, (B) habitat use overlaps, and (C) bidimensional niche overlaps. *p < 0.05, **p < 0.01.

Null models

Yearly and seasonality patterns were compared to simulated communities. Yearly overlaps for habitat (p = 0.01) and for both dimensions (p = 0.02) were significantly higher than the expected niche overlaps. Seasonality overlaps followed a similar pattern. Habitat overlaps were higher than the expected in T1 (p = 0.01), T2 (p = 0.01), and T3 (p = 0.05). Additionally, bidimensional overlaps were higher in T2 (p = 0.01) and T3 (p = 0.01), but did not significantly differ in T1. Feeding technique overlaps in T2 (p = 0.04) differed from those expected in communities without competition.


Our study describes the guild structure of a waterbird community in central Mexico and analyzes resource utilization patterns through three niche dimensions: habitat use, feeding technique, and time. Patterns characterized from niche breadth and niche overlap of species showed that species were specialists in feeding technique and more flexible in terms of feeding habitat. To detect if the observed pattern arose from competition between species, null models were used. Niche overlaps of the waterbird community were higher than expected in a community without competition, suggesting a lack of competition. Processes such as morphological differences, different abundances of species, migration, resource fluctuations, and clumped resources could explain the observed patterns.

The bidimensional niche (under the assumption that it reflects differences in resource exploitation; sensu Holmes and Recher 1986) structured the waterbird community into four feeding guilds (Wiens 1989; Sarrías et al. 1996). However, species belonging to the same guild mostly differed in bill and leg morphologies. For instance, guild G2 could be subdivided into subgroups according to morphological characteristics, such as bill or leg size. Morphological differences may explain why members of the same guild feed in different areas using the same techniques or in the same area (apparently exploiting the same resource) but catching different prey (Schoener 1974; Simberloff and Boecklen 1981; Gotelli and Ellison 2002; Zeffer et al. 2003). To provide an accurate description of feeding guilds, more dimensions should be added to the analysis. Data on diet (stomach contents) and availability of prey would be informative (Sarrías et al. 1996).

Important patterns in the waterbird community structure at Lake Acuitlapilco were characterized through niche breadths and niche overlaps. The calculated niche breadths were narrow, suggesting that guilds were mainly specialists in feeding techniques. Only three species (F. americana, A. clypeata, and A. crecca) showed niche breadths wider than the other species. The first two were the most abundant species in the community (Fonseca et al. 2012) and also had the largest values of niche breadth. These species appeared to be unaffected by high abundances of individuals of the same species (A. clypeata) or by changes in food habitat availability (F. americana). The flocking feeding behavior of A. clypeata and F. americana and the wide niche breadths in all dimensions suggest that competition for resources or interspecific competition did not play a major role in structuring their populations.

Additionally, narrow niches suggest that changes in resource availability may also affect the composition of the community (Pöysä 1983). Under this scenario, a fluctuation in resources (habitat) would affect species with a narrow niche breadth, such as wading species (of the Scolopacidae and Charadriidae) from guild G2. These guilds use pecking to opportunistically exploit resources in areas with particular characteristics such as muddy areas and shallow water (Skagen and Knopf 1994). Their presence and abundance were restricted to months of water withdrawal (Pérez-Crespo et al. 2013). In contrast, guilds G4 (A. acuta, A. discors, A. clypeata, A. crecca, and A. platyrhynchos) and G3 (A. cyanoptera, F. americana, G. galeata, L. pipixcan, and P. tricolor) had wider niche breadths in both dimensions and would have been less affected. The ability of these guilds to exploit resources in several habitats of the lake using diverse techniques allowed segregation, thus decreasing potential inter- and intraspecific interactions.

The general pattern of niche overlap found in the Acuitlapilco waterbird community was larger among species of the same guild than between other species in the community. Several authors suggested that competitive interactions are more likely among species of the same guild (Pianka 1980; MacNally 1983; Jaksic and Medel 1990), and they usually occur in guilds with a moderate to small number of species (MacNally 1983). Liordos (2010) found a similar pattern of niche overlap of foraging guilds of waterbirds wintering in a Mediterranean coastal wetland. He concluded that a small niche overlap between species of different guilds suggested a relatively high degree of specialization within the waterbird assemblage. Overlaps of species of the same guild were high, but habitat partitioning was observed. No conclusions about the existence of ecological processes underlying the pattern observed were provided by Liordos. In contrast, the use of null models in our study allowed us to discriminate between ecological phenomena such as competition and species sharing niches.

Results from the null models showed that the observed overlaps were higher than expected, particularly in habitat use and both dimensions together. When data were seasonally subdivided, the same pattern was observed. Therefore, species share habitat more than randomly expected, thus denoting a lack of competition (Gotelli and Graves 1996). Several mechanisms could explain this pattern.

First, seasonal variability of resources allows the addition or removal of species in each guild, reducing competitive interactions (Wiens 1977). Second, clumped resources attract more species and individuals. Studies suggested that shallow waters have greater organic matter and submerged plant beds, providing a rich foraging habitat and protection from predators (Rozas and Odum 1988; Minello et al. 1994; Rozas and Zimmerman 2000; Castellanos and Rozas 2001; Gossman 2005; Cannaday 2006). Other studies also suggested that shallow waters can accommodate more species than deep waters (Williams 1996; Colwell and Taft 2000), which suggests that clumped and rich resources in shallow waters increase bird density there and reduce competition. Third, rather than simply forming in areas of existing high prey density, social flocks may actively enhance their foraging success through herding or confusing escape reactions of prey (Saino et al. 1995; Battley et al. 2003). Guild G2, pickers in water, mud, and vegetation (egrets, ibises, and shorebirds), feed in groups in shallow waters with high prey availability, and aggressive interactions were not noted between individuals when foraging at our study site. Fourth, the existence of differences in morphology between members of the same guild, as mentioned above (Wiens 1989), allows species to coexist. Fifth, the arrival of migrating species in winter coincides with an increased availability of resources and habitats (Aguilar 2003). Finally, differences in species abundances could be a mechanism explaining coexistence. For example, O. jamaicensis (5,300 records, Fonseca et al. 2012) and P. nigricollis (280 records) had almost total niche overlap (all dimensions) and narrow niche breadths. In contrast, A. clypeata and A. platyrhynchos had high niche overlap, but niche breadths and abundances were not equal. Asymmetries in abundance and niche breadth could potentially be acting as mechanisms for coexistence.


In short, our results showed that waterbird species in Lake Acuitlapilco were specialists in resource utilization patterns and therefore vulnerable to fluctuations in resources, particularly feeding habitats. Niche overlaps were generally largest among species belonging to the same guild. The use of null models showed that habitat and observed bidimensional overlaps were higher than those of randomly generated communities, suggesting a lack of competition or species sharing niches. Thus, our study suggested that other processes can be used to predict resource utilization patterns instead of competition alone, as suggested by neutral theory (Hubbell 2001). Future studies analyzing the mechanisms that structure waterbird communities should include the use of null models to support their conclusions.


  1. Aguilar V: Aguas continentales y diversidad biológica de México: un recuento actual. Biodiversitas 2003, 48: 2–16.

  2. Albrecht M, Gotelli NJ: Spatial and temporal niche partitioning in grassland ants. Oecologia 2001, 126: 134–141. 10.1007/s004420000494

  3. Battley PF, Poot M, Wiersma P, Gordon C, Ntiamoa-Baidu Y, Piersma T: Social foraging by waterbirds in shallow coastal lagoons in Ghana. Waterbirds 2003, 26: 26–34. 10.1675/1524-4695(2003)026[0026:SFBWIS]2.0.CO;2

  4. Bell G: Neutral macroecology. Science 2001, 293: 2413–2418. 10.1126/science.293.5539.2413

  5. Cannaday CD: Effects of terraces on submerged aquatic vegetation in shallow marsh ponds in coastal southwestern Louisiana. Louisiana State University, Baton Rouge, MS thesis; 2006.

  6. Castellanos DL, Rozas LP: Nekton use of submerged aquatic vegetation, marsh, and shallow unvegetated bottom in the Atchafalaya river delta, a Louisiana tidal freshwater ecosystem. Estuaries 2001, 24: 184–197. 10.2307/1352943

  7. Cody ML: Competition and the structure of bird communities. Princeton University Press, Princeton; 1974.

  8. Colwell RK, Futuyma DJ: On the measurement of niche breadth and overlap. Ecology 1971, 52: 567–576. 10.2307/1934144

  9. Colwell MA, Taft OW: Waterbird communities in managed wetlands of varying water depth. Waterbirds 2000, 23: 45–55.

  10. CONAGUA: Delegación Tlaxcala. Comisión Nacional del Agua (CONAGUA), Tlaxcala; 2010.

  11. Connor EF, Simberloff D: The assembly of species communities: chance or competition? Ecology 1979, 60: 1132–1140. 10.2307/1936961

  12. Entsminger GL: EcoSim professional: null modeling software for ecologists, vers. 1. In Acquired Intelligence. Kesey-Bear & Pinyon Publishing, Montrose, CO; 2012. . Accessed 13 Oct 2012

  13. Fonseca J, Pérez-Crespo MJ, Cruz M, Porras B, Hernández-Rodríguez E, Martínez Pérez JL, Lara C: Aves acuáticas de la Laguna de Acuitlapilco, Tlaxcala, México. Huitzil 2012, 13: 104–109.

  14. Gatto A, Quintana F, Yorio P: Feeding behavior and habitat use in a waterbird assemblage at a marine wetland in coastal Patagonia, Argentina. Waterbirds 2008, 31: 463–471. 10.1675/1524-4695-31.3.463

  15. Gossman BP: Use of terraced marsh habitats by estuarine nekton in southwestern Louisiana. Louisiana State University, Baton Rouge, Master's dissertation; 2005.

  16. Gotelli NJ: Research frontiers in null model analysis. Glob Ecol Biogeogr 2001, 10: 337–343. 10.1046/j.1466-822X.2001.00249.x

  17. Gotelli NJ, Ellison AM: Assembly rules for New England ant assemblages. Oikos 2002, 99: 591–599. 10.1034/j.1600-0706.2002.11734.x

  18. Gotelli NJ, Graves GR: Null models in ecology. Smithsonian Institution Press, Washington, DC; 1996.

  19. Hernández-Vázquez S: Aves acuáticas de la Laguna de Agua dulce y el Estero El hermitaño, Jalisco, México. Rev Biol Trop 2005, 53: 229–238.

  20. Holmes RT, Recher HF: Determinants of guild structure in forest bird communities: an intercontinental comparison. Condor 1986, 88: 427–439. 10.2307/1368268

  21. Hubbell SP: The unified neutral theory of biodiversity and biogeography (MPB 32). Volume 32. Princeton University Press, Princeton; 2001.

  22. Hubbell SP: Neutral theory and the evolution of ecological equivalence. Ecology 2006, 87: 1387–1398. 10.1890/0012-9658(2006)87[1387:NTATEO]2.0.CO;2

  23. Hutchinson GE: Homage to Santa Rosalia, or why are there so many kinds of animals? Am Nat 1959, 93: 137–45.

  24. INEGI: Marco geoestadístico. 2000. . Accessed 21 Oct 2012

  25. Jaksic FM, Medel RG: Objective recognition of guilds: testing for statistically significant species clusters. Oecologia 1990, 82: 87–92. 10.1007/BF00318537

  26. Legendre P, Legendre L: Numerical ecology: second English edition. Developments in environmental modelling. Elsevier, Amsterdam; 1998:870.

  27. Levins R: Evolution in changing environments. Princeton University Press, Princeton; 1968.

  28. Liordos V: Foraging guilds of waterbirds wintering in a Mediterranean coastal wetland. Zool Stud 2010, 49: 311–323.

  29. López de Casenave J, Cueto VR, Marone L: Seasonal dynamics of guild structure in a bird assemblage of the central Monte desert. Basic Appl Ecol 2008, 9: 78–90. 10.1016/j.baae.2006.08.006

  30. Luevano J, Mellink E, Riojas-López M: Plovers breeding in the highlands of Jalisco, Aguascalientes, Zacatecas and San Luis Potosí, Central Mexico. West N Am Nat 2010, 70: 121–125. 10.3398/064.070.0114

  31. MacNally RC: On assessing the significance of interspecific competition to guild structure. Ecology 1983, 64: 1646–1652. 10.2307/1937517

  32. Mellink E (2005) Current status of research on the shorebirds, marshbirds and waders of the peninsula of Baja California. In: Ralph CJ, Rich TD (eds) Bird conservation implementation and integration in the Americas: proceedings of the third international partners in flight conference: General technical report PSW-GTR-191, vol 1. U.S. Dept. of Agriculture, Forest Service, Pacific Southwest Research Station, Albany; 2002:149–150.

  33. Mellink E, Riojas-López M: Waterbirds and human-related threats to their conservation in Laguna Cuyutlán, Colima, México. Rev Biol Trop 2009, 57: 1–12.

  34. Minello TJ, Zimmerman RJ, Medina R: The importance of edge for natant macrofauna in a created salt marsh. Wetlands 1994, 14: 184–198. 10.1007/BF03160655

  35. Munguía P, López P, Fortes I, Brush T: Seasonal changes in waterbird habitat and occurrence in Laguna de Sayula, western Mexico. South Nat 2005, 50: 318–322. 10.1894/0038-4909(2005)050[0318:SCIWHA]2.0.CO;2

  36. Núñez JP, Oropeza GO, Fernández JE, García DJ: Distribución y solapamiento espacial de las aves acuáticas y ribereñas en un humedal de zonas semiáridas del NE de México. Acta Zool Mex 2008, 24: 125–141.

  37. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H: Vegan: community ecology package. GNU 2012. General Public License

  38. Palmer TM, Stanton ML, Young TP: Competition and coexistence: exploring mechanisms that restrict and maintain diversity within mutualist guilds. Am Nat 2003, 162: S63-S79. 10.1086/378682

  39. Pérez-Crespo MJ, Fonseca J, Pineda-López R, Palacios E, Lara C: Response of waterbird assemblage to fluctuations in size and depth in an epicontinental lake from central Mexico. Stud Neotrop Fauna Environ 2013. in press

  40. Pianka ER: The structure of lizard communities. Ann Rev Ecol Syst 1973, 4: 53–74. 10.1146/

  41. Pianka ER: Guild structure in desert lizards. Oikos 1980, 35: 194–201. 10.2307/3544427

  42. Pineda-López R, Arellano-Sanaphre A: Noteworthy records of aquatic birds in the state of Querétaro, México. Huitzil 2010, 11: 49–59.

  43. Pöysä H: Resource utilization pattern and guild structure in a waterfowl community. Oikos 1983, 40: 295–307. 10.2307/3544594

  44. Project R: R package vers. 2.0–3. 2012. . Accessed 17 Oct 2012

  45. Ramírez-Bastida P: Aves de humedales en zonas urbanas del noroeste de la ciudad de México. Facultad de Ciencias, Universidad Nacional Autónoma de México, México, Master's dissertation; 2000.

  46. Robinson SK, Holmes RT: Foraging behavior of forest birds: the relationships among search tactics, diet, and habitat structure. Ecology 1982, 63: 1918–1931. 10.2307/1940130

  47. Root RB: The niche exploitation pattern of the blue-gray gnatcatcher. Ecol Monogr 1967, 37: 317–350. 10.2307/1942327

  48. Rozas LP, Odum WE: Occupation of submerged aquatic vegetation by fishes: testing the roles of food and refuge. Oecologica 1988, 77: 101–106. 10.1007/BF00380932

  49. Rozas LP, Zimmerman RJ: Small-scale patterns of nekton use among marsh and adjacent shallow nonvegetated areas of the Galveston Bay Estuary, Texas (USA). Mar Ecol Progr Ser 2000, 193: 217–239.

  50. Saino N, Fasola M, Wayyakp E: Do white pelicans Pelecanus onocrotalus benefit from foraging in flocks using synchronous feeding? Ibis 1995, 137: 227–230.

  51. Sarrías AM, Blanco D, de Casenave JL: Estructura en gremios de un ensamble de aves acuáticas durante la estación reproductiva. Ecol Aust 1996, 6: 106–114.

  52. Sartor OW: Notes on the rail Rallus longirostris in the highlands of central Mexico. Wilson Bull 1989, 101: 117–120.

  53. Schoener TW: Resource partitioning in ecological communities. Science 1974, 185: 27–39. 10.1126/science.185.4145.27

  54. Sibley DA: The Sibley field guide to birds of western North America. Knopf, New York; 2003.

  55. Simberloff D, Boecklen W: Santa Rosalia reconsidered: size ratios and competition. Evolution 1981, 35: 1206–1228. 10.2307/2408133

  56. Simberloff D, Dayan T: The guild concept and the structure of ecological communities. Ann Rev Ecol Syst 1991, 22: 115–143. 10.1146/

  57. Skagen SK, Knopf FL: Migrating shorebirds and habitat dynamics at a prairie wetland complex. Wilson Bull 1994,106(1):91–105.

  58. Strong JDR, Szyska LA, Simberloff DS: Test of community-wide character displacement against null hypotheses. Evolution 1979, 33: 897–913. 10.2307/2407653

  59. van Perlo B: Birds of Mexico and Central America. Princeton University Press, Princeton; 2006.

  60. Villamagna A, Murphy BR, Trauger DL: Behavioral response of American coots ( Fulica americana ) to water hyacinth ( Eichhornia crassipes ) in Lake Chapala, Mexico. Waterbirds 2010, 33: 550–555. 10.1675/063.033.0416

  61. Weller MW: Wetlands birds: habitat resources and conservation implications. Cambridge University Press, Cambridge; 1999.

  62. Wiens JA: On competition and variable environments. Am Sci 1977, 65: 590–597.

  63. Wiens JA: The ecology of bird communities. Volume I. Cambridge University Press, Cambridge, Foundations and patterns; 1989.

  64. Williams OE: Waterbird responses to late winter and early spring drawdowns of moist-soil managed wetlands in California's San Joaquin valley. Humboldt State University, Arcata, Master's dissertation; 1996.

  65. Winemiller KO, Pianka ER: Organization in natural assemblages of desert lizards and tropical fishes. Ecol Monogr 1990, 60: 27–55. 10.2307/1943025

  66. Zárate-Ovando B, Palacios E, Reyes-Bonilla H: Estructura de la comunidad y asociación de las aves acuáticas con la heterogeneidad espacial del complejo lagunar Bahía Magdalena-Almejas, Baja California Sur, México. Rev Biol Trop 2008, 56: 371–389.

  67. Zeffer A, Johansson LC, Marmebro A: Functional correlation between habitat use and leg morphology in birds. Biol J Linn Soc 2003, 79: 461–484. 10.1046/j.1095-8312.2003.00200.x

Download references


We thank Bélgica Porras, Enrique Hernández, and Aristarco Cortés for their help during fieldwork and the staff of Presidencia Municipal de Acuitlapilco for the facilities to conduct our research. We also thank Arturo Estrada and Ian McGregors for the statistical advice. Comments by two anonymous reviewers greatly improved an early version of this paper. This work was supported by scholarships from The Consejo Nacional de Ciencia y Tecnología to M. J. Pérez-Crespo (no. 248109) and J. Fonseca (no. 248103).

Author information

Correspondence to Carlos Lara.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

MJPC carried out the fieldwork, participated in its design, and performed the statistical analysis. JF carried out the fieldwork. RPL participated in the design of the study. EP participated in the design. CL conceived of the study, participated in its design and coordination, and drafted the manuscript. All authors read and approved the final manuscript.

Electronic supplementary material

Additional file 1: Seasonality patterns. Table S1. Seasonal niche overlaps for T1 (February 2011 to May 2011) calculated from feeding technique (above the diagonal line) and habitat use (below the diagonal line). Table S2. Seasonal bidimensional (feeding technique and habitat use) niche overlaps for T1 (February 2011 to May 2011). Table S3. Seasonal niche overlaps for T2 (May 2011 to September 2011) calculated from feeding technique (above the diagonal line) and habitat use (below the diagonal line). Table S4. Seasonal bidimensional (feeding technique and habitat use) niche overlaps for T2 (May 2011 to September 2011). Table S5. Seasonal niche overlaps for T3 (September 2011 to February 2012) calculated from feeding technique (above the diagonal line) and habitat use (below the diagonal line). Table S6. Seasonal bidimensional (feeding technique and habitat use) niche overlaps for T3 (September 2011 to February 2012). (DOC 346 KB)

Authors’ original submitted files for images

Rights and permissions

Reprints and Permissions

About this article


  • Communities
  • Feeding behavior
  • Habitat use
  • Niche overlap
  • Null models
  • Neutral theory