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The Brazilian Pampa region occupies a small area in the southern limit of Brazil, representing about 2% of Brazilian territory [15]. This region presents continuity with the grasslands in Uruguay and a small section of the Argentinean province of Entre Ríos, corresponding to the Uruguayan Savannas ecoregion [16], a biome of “tropical and subtropical grasslands, savannas, and shrublands”, defined by Olson et al. [17]. Grass-dominated vegetation types prevail, with sparse shrub and tree formations co-occurring within the grassland matrix. This lies within the South Temperate Zone and has both subtropical and temperate climates with hot summers, cool winters, and no dry season[18], classified as Cfa (humid subtropical) by Köppen’s climatic classification [19].
From October 2013 to August 2017, we opportunistically collected stomach contents of 98 road-killed specimens of four cat species, along highways of Rio Grande do Sul state, Brazil. All dead cats found in the road were exanimate (in the lab or in the field) for the presence of food in the stomach. The stomach contents, when present, were stored in alcohol 70% for diet analysis. Individuals with empty stomachs were not taking into account for this study. Preserved individuals were taken to Laboratório de Biologia de Mamíferos e Aves (LABIMAVE) of Universidade Federal do Pampa (UNIPAMPA), taxidermised and included in the scientific collection of the Institution, as voucher specimens. Samples of muscular tissue were collected from all individuals included in this study, stored in alcohol 96% for future molecular analyses or to solve any doubts in the identification of individuals. The macroscopic items contained in the stomachs such as hairs, teeth, feathers, beaks, and scales were separated and identified to the lowest possible taxonomic level of prey consumed by these cats. Mammal prey was mainly identified by microscopic hair patterns and bird feathers based on barbule nodules of the down [20], comparing with the reference collection of LABIMAVE. Reptiles and amphibians were identified by consulting a specialist.
Food items were expressed in terms of Frequency of Occurrence (FO), where the number of samples in which one prey type occurred divided by the total number of samples multiplied by 100, and Percentage of Occurrence (PO), calculated by dividing the number of occurrences of a prey type by the total occurrences of all prey types multiplied by 100. The FO indicates how common an item was in the diet, while the PO indicates the relative importance of an item in the diet. Similarity among diets was evaluated using the clustering technique with the unweighted pair-group method and arithmetic averaging (UPGMA) based on the proportion of each prey type using the Morisita’s index on software PAST 2.17c [21]. Diet overlap between species pairs were calculated using Pianka’s index [22]: Ojk = ΣPijPik/√ΣPij2ΣPik2, where Pij is the proportion of a prey type in one predator’s diet and Pik is the proportion of the same prey type in a second predator’s diet. The index ranges from 0 (no food resources in common) to 1 (total overlap of food niches). The proportion of each prey type was calculated through their relative volume estimated on a nine-point scale: 0 (absence), 1 (< 1%), 2 (1–5%), 3 (6–10%), 4 (11–25%), 5 (26–50%), 6 (51–75%), 7 (76–98%), and 8 (> 98%). For the niche overlap calculation, scores were converted to the midpoint of each percentage interval (1 = 0.5%, 2 = 3%, 3 = 8%, 4 = 18%, 5 = 38%, 6 = 63%, 7 = 87%, 8 = 99%), following Kruuk & Parish [23], Ray & Sunquist [24], and Kasper et al. [25]. To evaluate trophic niche breadth we used Levins’ index: B = 1 / (Σp2j), where pj is the Percentage of Occurrence of a prey type [26]. This index was standardized to a scale ranging from 0 (generalist habit, when prey items are consumed in equal proportions) to 1 (specialized diet, when few prey categories are eaten in greater frequency, while most are eaten in lower frequency) [27]: Bsta = (B-1) / (n-1), were B is Levins’ index and n is the total number of prey types consumed. Major axes of dietary variation among the small cat species were identified through a correspondence analysis on software PAST 2.17c [21]. Only the proportions of prey types that composed at least 5% of the diet were included in this analysis. The average adult body mass and primary lifestyle of mammal prey were obtained from the literature [28–31]. We estimated the minimum number of individuals consumed (MNI) by counting teeth, feet, and tails. When only hairs were encountered, we assumed the MNI equal to 1. The Index of Relative Importance (IRI) combines the frequency, number of individuals, and volume measures into a single estimate of the relative importance of food types [32]: IRI = F(N + V), where F is the Frequency of Occurrence, N is the Percentage of Occurrence, and V is the volumetric percentage. Only IRI for mammal prey were considered as this was the most represented group in the diet of the four cats. The volumetric percentage was calculated based on ingested biomass. Small-sized cats can consume 60–90 g per kg of body mass per day [33]. Based on the fresh body weight of individuals collected in this study, we considered the average body mass to be 3.69 kg (SD 0.82) for Geoffroy’s cat (n = 20) and 2.64 kg (SD 0.38) for margay (n = 8); based on the literature we used 3.5 kg for pampas cat, and 5.2 kg for jaguarundi [6]. Considering an average of 75 g of prey consumed daily for each kg of predator, we estimated that cats consumed 276.8, 198, 262.5, and 390 g per day, respectively. These values were used as the estimated ingested biomass of prey too large to be consumed entirely. For prey types with biomass below these values, the ingested biomass was estimated by the multiplication of their average body mass by their MNI. Taxonomy follows Gardner [34] for marsupials, Patton, Pardinas & D’Elía [35] for rodents, Kitchener et al. [8] for the cats, Bencke et al. [36] for birds, Costa & Bérnils [37] for reptiles and Segalla et al. [38] for amphibians.
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