Nitrogen and carbon stable isotope ratios analysis sheds light on trophic competition between two syntopic land iguana species from Galápagos

doi:10.21203/rs.3.rs-1638777/v1

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Nitrogen and carbon stable isotope ratios analysis sheds light on trophic competition between two syntopic land iguana species from Galápagos

https://doi.org/10.21203/rs.3.rs-1638777/v1

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Coexistence between closely related species can lead to intense competition for resources. Stable isotope ratio analysis (SIRA) is a reliable tool to estimate the extent of species competition. We performed SIRA to assess niche partitioning among two syntopic species of Galápagos land iguanas: Conolophus subcristatus and the critically endangered C. marthae. We collected samples from 60 C. marthae and 58 C. subcristatus within an area of about 2 km² on Wolf Volcano, Isabela Island, where C. marthae is endemic. We determined δ¹³C and δ¹⁵N ratios and described the isotopic niche of each species using corrected standard ellipse area (SEA_c). We tested for differentiation between the isotopic niches, while controlling for sex, using bivariate linear models. Despite the extensive overlap of the isotopic niches, our results indicate the existence of niche partitioning mechanisms acting between species and sexes. Evaluating the effect of ecological variables, we found that body size and productivity at the capture points, plus further, undetermined spatial effects explain ca. 75% of the differences observed between species and sexes, providing evidence for differential microhabitat and food-items usage. Our study provides essential baselines for evaluating conservation actions for C. marthae, such as the potential translocation to a sanctuary area.

Conolophus marthae

Diet diversification

Interspecific competition

Pink iguana

Toenails

Trophic niche partitioning

Competition among species is a critical determinant of population dynamics [1–3]. In spite of the competitive exclusion principle [4–5], several examples of syntopic (sensu [6]) closely related species competing, directly or indirectly, for limited resources have been reported [7–11]. A simple explanation for such a pattern is that even recently diverging species are unlikely to share the exact same niche [7], as theory predicts that natural selection would favor mechanisms reducing niche-overlap and, therefore, competition [12].

Beyond its fundamental importance as a key concept of animal ecology, a better understanding of competitive dynamics between co-occurring, closely related species can contribute important insights for the conservation of endangered species involved in these interactions. One such case involves the occurrence in syntopy of two species of Galápagos land iguanas: Conolophus subcristatus and C. marthae. While the former is found on seven islands across the Galápagos Archipelago, namely Santa Cruz, Plaza Sur, Isabela, Fernandina, Seymour Norte (introduced), Baltra (repatriated) and Santiago (reintroduced; [13]), the latter is only found in a very small high-altitude area (ca. 25 km²) on Wolf Volcano, Isabela Island [14, 15]. At this site, the only known population of C. marthae is syntopic with a population of C. subcristatus. C. marthae has been recently described to science [16] and, shortly after, assessed as Critically Endangered in the IUCN Red List of Threatened Species [14]. The main justifications for this assessment include small population size, scarce recruitment, introduced predators, limited distribution, and the potential for intense competition with C. subcristatus [14, 15]. One source of competition can be identified in the use of trophic resources. Very little is known about the dietary habits of C. marthae, but some evidence obtained from chemical signature of femoral pore secretions suggest they could be partially different from those of C. subcristatus [17] for which a generalist trophic behavior has been described [18, 19]. Moreover, field observations seem to indicate differential habitat and microhabitat use by the two species and this could be related to the use of different trophic resources [20]. Equally important, because the area where C. marthae occurs has remained scarcely known until very recently, it is not known how long the populations of the two species have been coexisting in syntopy. As intense competition for trophic resources may lead to the extinction of the least competitive species [21, 22], a better understanding of the trophic ecology of syntopic and interacting species is essential for guiding actions directed to their conservation [23, 24].

Trophic competition typically represents a major, and often the most important, component of overall competitive interaction among co-occurring herbivore species [10, 11]. Trophic niche overlap may be regarded as a good proxy of the overall degree of competition between interacting species [25]. Trophic niche partitioning is one of the mechanisms that could reduce competition [12]. It can be achieved by feeding in different microhabitats [3], foraging on different food resources within the same microhabitat [1] or, finally, feeding on the same resources within the same microhabitat, but at different times [2].

Stable isotope ratio analysis (SIRA) is an effective and widely applicable tool to characterize the trophic niche of species [26]. The isotopic composition of animal tissues is known to reflect the isotopic composition of their diet [27–29], with differences in diet composition translating into differences in the stable isotope signature [26, 30]. In animal ecology, SIRA is typically performed by analyzing the ratios between the two main stable isotopes of carbon (¹²C and ¹³C) and nitrogen (¹⁴N and ¹⁵N), which can then be compared among individuals, species or populations [27–29]. The stable isotopes ratio of carbon (δ¹³C) extracted from tissues closely reflects the ratio in the animal’s diet, as animal tissues are generally enriched in ¹³C by only ≈ 1‰ relative to their food [27, 29]. Therefore, the distribution of δ¹³C in a sample of individuals is typically used to estimate the degree of variation in the diet of the population or species they belong to. In contrast, the tissues of animals are enriched in ¹⁵N by ≈ 3–4‰ compared to their source of food and δ¹⁵N may clearly distinguish herbivores from carnivores [28, 29]. For this reason, the stable isotopes ratio of nitrogen (δ¹⁵N) is generally used to estimate the trophic level of individuals and species.

In this work, we used isotope ratios to evaluate the dietary overlap between the syntopic populations of C. marthae and C. subcristatus. We determined δ¹³C and δ¹⁵N isotopic signatures in toenails sampled from individuals of these two species on Wolf Volcano. We first tested for the null hypothesis of no differentiation between trophic niches, controlling for the sex of the individuals. We then used a variance partitioning approach to assess how much ecologically relevant predictors such as body size and mean primary productivity at the capture points, plus the effect of the spatial location itself, explained variation in isotopic profiles and the differences between species and sexes.

Study area and sampling

We captured 60 individuals of C. marthae (38 males, 22 females) and 58 individuals of C. subcristatus (33 males, 25 females), from 14 to 23 of June 2014, on the northwestern slope of Wolf Volcano at an altitude of 1488–1659 m asl, within an area no larger than 2 km². At the sampling location, June is at the turn between the warm/wet season (typically occurring between January and May) and the hot/dry season (approximately from June to December; [31, 32]). We observed (and captured) 114/118 individuals in patches of deciduous shrubland (only 2 C. marthae and 2 C. subcristatus were captured in a different habitat), but other habitat types in this area include deciduous forest, tallgrass vegetated areas, and evergreen forest on the western side of the volcano [33].

For each captured individual, we collected toenail samples and recorded GPS coordinates of the capture point, snout-to-vent length (SVL; in cm), mass (in kg) and sex. In compliance with the Galápagos National Park regulation, we minimized the toenail amount sampled, taking three-four toenail samples from each individual, using sterilized bolt cutters. Toenail samples were immediately placed into 1.5 ml polypropylene collection tubes. Sixty individuals were identified as having been captured and tagged in previous field expeditions by our research group [14, 15, 17]. All other captured iguanas were assigned a new ID and were tagged with a subcutaneous electronic marker (a passive integrated transponder; PIT). To counter the illegal trade of Galápaganian wildlife [15, 34] (Gentile et al. 2013, 2016), in agreement with the Galápagos National Park, we decided not to disclose the exact GPS coordinates of the capture points here and avoid publishing a detailed map of our sampling.

Stable isotopes ratio analysis (SIRA)

The turnover rates of stable isotopes vary largely among tissues, with metabolically more active tissues reflecting diet within a few weeks, and less active tissues being informative about the diet from several months [35, 36]. Differences in δ¹⁵N and δ¹³C from different tissues from a single iguana individual have been described and interpreted as informative on diet composition in different time periods [37, 38]. Inert tissues, such as hair or toenails, provide long-term information on consumed food sources [39]. For example, it has been demonstrated that, for turtles’ claws, a change in diet requires about 6 and 12 months to be reflected by a change in δ¹⁵N and δ¹³C, respectively [40], while it takes 3 to 4 months in endothermic Sauropsida (birds; [41]).

To determine the isotopic composition of carbon and nitrogen, toenail samples were cleaned using distilled water to remove any sources of contamination. Toenail fragments were freeze-dried and then ground into a fine, homogeneous powder with an agate pestle and mortar. For each individual, a pair of samples of 0.12–0.2 mg were analyzed, using continuous-flow isotope ratio mass spectrometry (Thermo Flash 1112 Elemental Analyzer coupled to a Finnigan Delta Plus mass spectrometer) at IGAG (Istituto di Geologia Ambientale e Geoingegneria, CNR). Isotopic compositions were expressed in the usual notation δ notation, which represents the relative deviation in part per thousand of the heavy isotope/light isotope ratios of the sample from the same ratio of a reference standard. Isotope data were normalized to the V-PDB (Vienna Pee-Dee Belemnite) scale for carbon and AIR (atmospheric air) scale for nitrogen using IAEA standards (CH-6, CH-7 USGS-24 for carbon, and N-1, N-2, USG25 for nitrogen). Based on repeated measurements of laboratory standards, the analytical error was < 0.3‰ for both carbon and nitrogen.

Data analysis

To characterize the isotopic niche of each species and sex, we calculated standard ellipse areas corrected for small sample size (SEA_c), as described by Jackson and colleagues [42]. SEA_c was developed to represent the core of the isotopic niche of a sampled population, and we used these metrics to measure niche overlap between species and sexes as the proportion of overlap between ellipses. The entire procedure was carried out using the “SIBER” R-package [42].

We then tested for the null hypothesis of no difference between the mean position of species in the carbon and nitrogen isotope space, while controlling for the effect of sex, by fitting a bivariate linear model, with δ¹³C and δ¹⁵N as joint response variables and species, sex and their interaction as predictors. To evaluate the effect of individual morphology, habitat features and spatial distribution of the samples, we fitted Generalized Additive Models (GAMs) including parametric terms for body-size and mean primary productivity at the capture point, and a spatial tensor product on the X and Y coordinates (UTM/WGS-84 Zone 15S) of the capture points accounting for unmeasured effects of the spatial distribution of samples. We expressed body size as snout-to-vent-length (SVL). We chose SVL rather than mass to express body size following previous studies on iguanas [43–45] because it represents a relatively stable measure of body size, typically not affected by reproductive status, fat storage and digestive state of the animal [46, 47]. We measured primary productivity as Normalized Difference Vegetation Index (NDVI; [48]), using Copernicus Sentinel-2 10 meters resolution images (COPERNICUS_S2_SR), freely available on the cloud service Google Earth Engine (https://earthengine.google.com/). We calculated the mean NDVI for a 50-m radial buffer around the capture point of each individual averaged on a 3-year period (2019–2021), after masking for clouds (i.e., excluding from the averaging all pixels where clouds were detected in a given image). Before fitting our models, both SVL and NDVI were standardized to zero mean and unit standard deviation using the scale() function from package “base” [49] in order to obtain more easily interpretable coefficients. We preliminarily investigated whether these two variables differed between species and sexes by fitting two linear models with scaled SVL and NDVI as response variables and species and sex as predictors. To assess spatial aggregation of the samples, we conducted a multiple regression on distance matrices using the MRM() function in the “ecodist” R package [50] with the Euclidean distance matrix computed from X and Y coordinates of the capture points as response variable and the dissimilarity matrices of species and sex as predictors (where 0 indicates matching and 1 indicates not-matching).

To investigate the contribution of ecologically-relevant variables (size, productivity and space) in defining the isotopic differences observed between species and sexes, we used a variance partitioning approach based on partial correlation analyses [51] (Randin et al. 2009), which we implemented by adapting the ecospat.varpart() function from package “ecospat” [52]. To this end, we fitted two additional models: first, a “full” bivariate generalized additive model (GAM) with δ¹³C and δ¹⁵N as joint response variables and species, sex, body size and mean productivity at the capture points as parametric predictors and a tensor product smooth interaction of geographic coordinates to adjust for the spatial effect of samples distribution; second, an analogous model excluding species and sex from predictors. We then compared these models with the previously described model considering species and sex only, and computed the portions of deviance i) uniquely explained by species + sex, ii) uniquely explained by size + productivity + spatial tensor product, iii) jointly explained by the two sets of predictors, and iv) left unexplained [53].

We fitted all models using the R function gam() from package “mgcv” [54]. For each model we also checked that distribution of residues was consistent with assumptions of normality and homoscedasticity. We used Likelihood Ratio Test (LRT) as implemented in the R function anova() from package “stats” [49] to test for the significance of individual predictors in GAM models and F as test statistics to compute P-values for linear models with SVL and NDVI as response variables. Non-significant interactions were removed from our final models. We checked for model stability by re-fitting each model 200 times on random sub-samples with 90% of the data and visually assessing the robustness of the coefficient estimates. We did not find evidence of instability for any of our models (for details see SM Fig. 1; SM Fig. 2; SM Fig. 3).

We found that SEA_c was larger for C. subcristatus than for C. marthae (Fig. 1A-B). The overlapping portions of SEA_c were 65% and 41% for C. marthae within C. subcristatus and C. subcristatus within C. marthae, respectively. Both sexes of C. subcristatus had larger SEA_c than the corresponding sex of C. marthae (Fig. 1A-B). At intraspecific level, we found higher levels of overlap between sexes for C. marthae (76% for males and 49% for females; Fig. 1C) than for C. subcristatus (42% for males and 49% for females; Fig. 1C).

Results of models fitted using δ¹³C and δ¹⁵N as response variables are reported in Table 1. Model 1 (Table 1), which only included species, sex and their interaction as predictors, indicated that species and sex independently influenced δ¹³C, with values in C. marthae being lower than those in C. subcristatus and higher in males than females (Fig. 1A), while δ¹⁵N depended on the interaction between sex and species, with similar values for males and females in C. marthae and clearly higher values for males than females in C. subcristatus (Fig. 1A). In Model 2 (Table 1), where size, productivity and space were added, only species showed a statistically significant effect on δ¹³C, while species and sex had no effect on δ¹⁵N, and body size and primary productivity at capture points strongly influenced the relative position of each individual in the δ¹³C, δ¹⁵N bi-plot space. The spatial tensor did not provide a statistically significant contribution to the model for δ¹³C, but it did for δ¹⁵N. The same pattern was found with Model 3 (Table 1).

Table 1

Estimated models coefficients for the two response variables, δ¹³C and δ¹⁵N.
Model 1: (δ¹³C, δ¹⁵N) ~ Species + Sex
		Estimate	SE	χ²	Z	df	P
δ¹³C	Intercept	-25.483	0.109	-	-	-	-
	Species (C. subcristatus)	0.499	0.114	19.130	4.374	1	<< 0.001
	Sex (male)	0.325	0.117	7.780	2.789	1	0.005
δ¹⁵N	Intercept	4.903	0.255	-	-	-	-
	Species (C. subcristatus)	-0.549	0.348	-	-1.580	-	-
	Sex (male)	-0.223	0.319	-	-0.700	-	-
	Species (C. subcristatus): Sex (male)	1.126	0.444	6.423	2.530	1	0.011
Model 2: (δ¹³C, δ¹⁵N) ~ Species + Sex + SVL + NDVI + te (X, Y)
		Estimate	SE	χ²	Z	df	P
δ¹³C	Intercept	-25.266	0.103	-	-	-	-
	Species (C. subcristatus)	0.243	0.119	4.167	2.041	1	0.041
	Sex (male)	0.174	0.105	2.733	1.653	1	0.098
	SVL	0.307	0.055	31.089	5.576	1	<< 0.001
	NDVI	-0.120	0.056	4.578	-2.140	1	0.032
	te (X, Y)	-	-	4.171	-	3	0.339
δ¹⁵N	Intercept	5.011	0.239	-	-	-	-
	Species (C. subcristatus)	-0.612	0.348	-	-1.760	-	-
	Sex (male)	-0.166	0.284	-	-0.590	-	-
	Species (C. subcristatus): Sex (male)	0.729	0.408	3.188	1.790	1	0.074
	SVL	0.356	0.103	11.906	3.450	1	0.001
	NDVI	-0.234	0.107	4.833	-2.200	1	0.028
	te (X, Y)	-	-	25.833	-	3	<< 0.001
Model 3: (δ¹³C, δ¹⁵N) ~ SVL + NDVI + te (X, Y)
		Estimate	SE	χ²	Z	df	P
δ¹³C	Intercept	-25.041	0.051	-	-	-	-
	SVL	0.365	0.051	50.472	7.100	1	<< 0.001
	NDVI	-0.135	0.057	5.683	-2.380	1	0.017
	te (X, Y)	-	-	5.725		3	0.126
δ¹⁵N	Intercept	4.814	0.094	-	-	-	-
	SVL	0.340	0.095	12.756	3.570	1	< 0.001
	NDVI	-0.258	0.105	6.033	-2.460	1	0.014
	te (X, Y)	-	-	30.947	-	3	<< 0.001

The table shows the output of the three fitted models: Model 1 is the bivariate linear regression with species and sex as predictors; Model 2 is the bivariate generalized additive model (GAM) with species, sex, body size (scaled SVL), productivity at the capture points (scaled NDVI) and a spatial tensor product smooth (te (X, Y)) as predictors; Model 3 is the bivariate generalized additive model (GAM) including only body size, productivity of the capture point and the spatial tensor product smooth as predictors. The table reports the estimated model value (Estimate), standard error (SE), degrees of freedom (df), the χ² statistic for LRT with the corresponding P-values (P) and the z-score (z). The interaction between Species and Sex was not a significant predictor of δ¹³C (χ² = 0.386, P = 0.535) and was therefore removed from the final models. P-values for intercept and for main effects included in an interaction do not have a meaningful interpretation and are not shown.

Results of variance partitioning analysis are illustrated in Fig. 2. Our predictors collectively explained 36% of the deviance in the response (i.e., 64% of the total deviance was left unexplained by our analysis). Species and sex together explained only 12% of the response deviance, while size, productivity and the spatial tensor, as a whole, explained 33%. Importantly, 9% of the deviance was jointly explained by the two sets of predictors. The latter result shows that the three quarters (9% on 12%) of the variation in isotopic composition observed between species and sexes may be explained by differences in size, productivity of the habitat they exploit, and some yet unmeasured spatial variable.

Table 2

Estimated coefficients for the two univariate linear models with SVL and NDVI, respectively.
		Estimate	SE	F	df	P
SVL	Intercept	-0.613	0.163	-	-	-
	Species (C. subcristatus)	0.643	0.171	14.098	1	< 0.001
	Sex (male)	0.493	0.175	7.936	1	0.006
NDVI	Intercept	0.117	0.172	-	-	-
	Species (C. subcristatus)	-0.435	0.181	5.796	1	0.018
	Sex (male)	0.161	0.185	0.759	1	0.386

The table shows the estimated model value (Estimate), standard error (SE), degrees of freedom (df), the F statistic and corresponding P-values (p).

In this study, we estimated the level of competition between the only known population of the Galápagos Pink Land Iguana, Conolophus marthae, and the syntopic population of the closely related and more widely distributed C. subcristatus on Wolf Volcano, Isabela Island. Our results indicate that C. marthae occupies a smaller isotopic niche than C. subcristatus, with 65% of the standard ellipse area (SEA_c) falling within the SEA_c of C. subcristatus (Fig. 1A). This overlap is reflected in the similar δ¹⁵N recorded for the two species (Table 1 – Model 1), which suggests that, overall, they occupy a similar trophic level, consistently with previous reports indicating that both species primarily feed on vegetation, as typical of most large iguanas [18, 19, 55, 56]. Importantly, males and females show larger overlap in C. marthae than in C. subcristatus (Fig. 1A-C), suggesting that higher differentiation between the isotopic niches of males and females contributes to the larger overall niche occupied by C. subcristatus. Moreover, comparing the standard ellipses obtained from raw data (Fig. 1A) and those from the residuals of a model accounting for size, productivity and space (SM Fig. 5), shows that, while the difference between sexes in residual δ¹³C of C. subcristatus is much smaller than in the raw data, the difference in δ¹⁵N is similar, implying that differences in trophic levels between male and female C. subcristatus are not explained by differences in size or occupied habitat and may directly reflect sex-specific resource selection.

Despite the broad overlap, our results showed that δ¹³C clearly differ between C. marthae and C. subcristatus at Wolf Volcano (Table 1 – Model 1), supporting the existence of resource partitioning mechanisms acting to reduce the competition between these species. Evidence in this regard is also provided by a recent study indicating that differences in chemical signatures of femoral pore secretions extracted from these two species could be associated with a difference in species diet [17]. Niche-partitioning might be the result of two non-mutually exclusive mechanisms. First, individuals of the two species could feed on different trophic resources in the overlapping distribution area. The generalist habit of C. subcristatus [18, 19] could provide a competitive advantage to the species, allowing the use of resources that are present inside areas occupied by C. marthae individuals but not accessible to them perhaps due to some dietary or metabolic constraints. Second, they could feed in different habitats or microhabitats and consequently use different types of food [3]. Recent field observations would support a differential microhabitat use for these two species, with C. marthae that seems to preferentially occupy more shaded areas. The potential different use of habitats or microhabitats by the two species has already been considered as a mechanism acting to enhance the avoidance of interspecific hybridization between these two populations on Wolf Volcano [20].

Both strategies are supported by our data. On the one hand, we found that i) the capture locations of the two species were spatially aggregated, ii) the two species were captured at locations differing in primary productivity (Table 2; SM Fig. 4) iii) productivity at capture points is a significant predictor of both δ¹³C and δ¹⁵N (Table 1) and iv) unmeasured features of the space (measured by the spatial tensor product) have a significant effect on δ¹⁵N (Table 1), indicating selection of different microhabitats as a likely niche partitioning mechanism. On the other hand, resource selection may also marginally contribute to differences in isotope niches. For example, while C₃ plants have a δ¹³C ranging from − 22‰ to -30‰, C₄ show values ranging from − 10‰ to -14‰ [57], and CAM (Crassulacean Acid Metabolism) from − 10 to -20‰ [58]. The diet of C. subcristatus could therefore include a larger portion of C₄ and/or CAM plants than the diet of C. marthae, translating to the higher values of δ¹³C observed in the former (Fig. 1A). Consistent with this view, Opuntia cactus, which were previously reported to constitute a large portion of the diet of C. subcristatus [59] and C. pallidus [60] during the dry season, is a constitutive CAM species [61], relatively rare inside the area of distribution of C. marthae, but abundant on the eastern side of Wolf Volcano. While this area is outside the core area of C. marthae, it is inhabited by C. subcristatus. It is not uncommon that when two species compete for common resources, the dominant species (often the larger one) could displace the less competitive one to a suboptimal trophic niche [62]. Therefore, the current situation on Wolf Volcano could be the result of a competitive process that has led C. marthae to use a suboptimal array of trophic resources.

Our data hint at resource partitioning operating at an intraspecific level too, with males of both species showing higher δ¹³C than females (Fig. 1A) and C. subcristatus males showing higher δ¹⁵N than their conspecific females (Fig. 1A). Intraspecific niche partitioning mechanisms are widespread in animal populations and can be interpreted as a strategy to reduce intersexual competition for food resources [63]. The isotopic pattern observed in our data is likely to reflect behavioral differences between sexes. It is indeed well known that, during the reproductive season, approximately between January and May, on Fernandina Island, C. subcristatus males exhibit a territorial behavior, defending areas that constitute the core part of the mating area, while the females of the species shift between territories defended by different males [64]. Males reduce feeding during the mating season and food resources inside or near their territories are primarily necessary for females [64]. After mating, females leave these areas to reach suitable nesting sites, while males remain in their territories if food is still abundant or they disperse, looking for alternative feeding areas [64]. These observations, therefore, indicate that both temporal and spatial mechanisms act to reduce intersexual competition for trophic resources in C. subcristatus population on Fernandina Island. As δ¹⁵N of consumers generally increase with starvation [65], if the same behavioral mechanisms acted in C. marthae and C. subcristatus populations on Wolf Volcano, males would show higher δ¹⁵N during the period for which our data are informative (which can be very approximately estimated to encompass the months from January to June). Interestingly, our results suggest that this explanation might be reasonable for C. subcristatus population on Wolf Volcano as males of the species showed δ¹⁵N values higher than those of conspecific females (Fig. 1A), while this difference was not revealed for C. marthae (males and females were characterized by similar δ¹⁵N values; Fig. 1A), suggesting that this behavior may not be shared by the two syntopic populations.

A large part of the variance observed in δ¹³C and δ¹⁵N between species and sexes can be explained in terms of body size, productivity and relative location of the capture points (Fig. 2). Moreover, these ecological variables provided the highest independent contribution to explaining δ¹³C and δ¹⁵N recorded in the samples (Fig. 2). We found that, other predictors being equal, larger individuals show higher levels of both δ¹³C and δ¹⁵N (Table 1, Fig. 3), suggesting that they occupy higher trophic levels. It is not uncommon to find a positive relation between body size and trophic level in natural populations [66, 67]. Larger individuals often have a competitive advantage over smaller ones, allowing them to integrate their diet with trophic resources of animal origin that could not be available for smaller individuals. Accordingly, Hanson and colleagues [68] found a positive relationship between δ¹³C and SVL in Crocodylus porosus, suggesting that individuals of different body size are trophically linked to different primary resources.

We also found a negative relation between the NDVI of samples location and both δ¹³C and δ¹⁵N (Fig. 3). On the one hand, different availability of C3, C4 and CAM plant resources in areas with different productivity may contribute to the differences in δ¹³C. On the other hand, as animal tissues are enriched in both δ¹³C and δ¹⁵N relative to their diet [27–29], a direct explanation of this pattern may involve a higher consumption of animal food by those iguanas that occupy less productive microhabitats compared to those that were captured in more productive habitats. Interestingly, C. marthae individuals were mostly found in areas with higher levels of NDVI, if compared with C. subcristatus (SM Fig. 4). More vegetated areas also offer better shelter opportunities. Field observations suggested that C. marthae occupy more shaded areas than C. subcristatus [20], and this preference could be an ecological response to partial skin depigmentation of C. marthae [69]. Therefore, this species might be found in more vegetated areas also because, here, iguanas might find a more shelters-enriched environment that could facilitate their basking-regulation behavior (Di Giacomo et al., submitted).

Our study outlines that small-scale spatial pattern, both in terms of habitat productivity and of an undetermined spatial effect revealed by the tensor product smooth on capture locations coordinates, did affect the isotopic composition of samples (Table 1 – Model 2; Table 1 – Model 3). On the one hand, we argued that this finding supports differential use of microhabitats by these two species. On the other hand, as the isotopic signature recorded for these species should reflect a time-scale of a few to several months [40, 41], this result strongly suggests that, at least in the time of the year for which our data may be informative, the feeding ranges of these two species may be extremely restricted. More in general, as our study only covered an area of ca. 2 km², these results highlight the importance of considering the spatial dimension of processes when assessing ecological problems at any spatial scale.

In this study, we evaluated, for the first time, trophic competition between the critically endangered C. marthae and the syntopic C. subcristatus on Wolf Volcano. Competition was quantitatively estimated, and a mechanism of resource partitioning was described, through which the two congeneric species may coexist. Some trophic niche partitioning is also likely to exist between sexes, especially in C. subcristatus. Differences in isotopic composition between species and sexes are largely (but not entirely) explained by differential use of microhabitats as well as body size differences between and within species. While the indications of niche partitioning mechanisms between the two species suggest potential for coexistence of these two endemic iguanas, the observed extent of niche overlap raises concern over the impact that interspecific competition may have on the only known population of C. marthae. This urgently calls for a careful evaluation of conservation actions aimed at sustaining the only existing population which may prudentially include the creation of a new, viable population in a sanctuary area, in another suitable area of the archipelago. Finally, this study underlines the importance of considering small-scale spatial mechanisms when working in an ecological framework.

Acknowledgments

Data presented here result from a long-term program in collaboration between the Galápagos National Park and the University of Rome "Tor Vergata," aimed at conserving Galápagos land iguanas. We thank the Galápagos National Park for the support given in this study. We are grateful to the Galápagos National Park Rangers, Martina Fabbri, and Carlos Vera for field and technical assistance.

Declarations

Funding: This work was supported in part by funding from the University of Rome “Tor Vergata” to G. Gentile.

Conflicts of interest: The authors declare no conflicts of interest.

Study design: This study was designed, carried out and reported following the ARRIVE guidelines (https://arriveguidelines.org) according to [70].

Ethics approval: The handling and sampling of the animals were carried out according to a protocol that minimized the stress of the animals. These techniques were approved by the University of Rome “Tor Vergata” ethics and animal handling protocol, and following the guidelines of the European Community and with the approval of the Directorate of the Galápagos National Park (GNPD). The GNPD does not have a specific ethics committee. However, the GNPD is responsible for the administration of the research (including the issuing of research permits) carried out in the protected areas of the Galápagos, as administrator of these areas and representative of the National Environmental Authority. The GNPD has granted a research permit to G.G. for this project. The samples were exported and imported with GNPD and CITES permits issued to G.G.

Availability of data and material: The data are available upon reasonable and documented request to the senior author.

Code availability: Code is available upon reasonable request.

Authors' contributions: GG designed the project; GG, GC and CS collected samples in the field; MB and FG carried out laboratory analysis; MG, GC, PG, GG and SM performed data analyses; MB designed the laboratory analysis; MG wrote the manuscript with significant input from GC, PG, SM and GG. All authors provided feedback.

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Nitrogen and carbon stable isotope ratios analysis sheds light on trophic competition between two syntopic land iguana species from Galápagos

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Stable isotopes ratio analysis (SIRA)

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