Seabird temporal composition, abundance and habitat use in “Punta La Metalera” (Arequipa), Southern Peru

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¿Cómo referenciar?

Los usuarios deben citar este trabajo de la siguiente manera:

Vilca Taco, L.M., Mamani T., E., Luque Fernández, C. R., 2021. Seabird temporal composition, abundance and habitat use in “Punta La Metalera” (Arequipa), Southern Peru. Museu de Ciències Naturals de Barcelona. Dataset/Occurrence. https://doi.org/10.15470/9umyvz

Derechos

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El publicador y propietario de los derechos de este trabajo es Museu de Ciències Naturals de Barcelona. Esta obra está bajo una licencia Creative Commons de Atribución/Reconocimiento-NoComercial (CC-BY-NC 4.0).

Registro GBIF

Este recurso ha sido registrado en GBIF con el siguiente UUID: 2fb0b491-a53a-40ee-98ef-d3e9a377c9b8.  Museu de Ciències Naturals de Barcelona publica este recurso y está registrado en GBIF como un publicador de datos avalado por GBIF Spain.

Palabras clave

Diversity; Land-use; Seabird; Behavior; Disturbances; Larosterna inca; Occurrence

Contactos

L. M. Vilca Taco

• Originador

Universidad Nacional de San Agustín de Arequipa

Arequipa

PE

http://orcid.org/0000-0001-7875-6607

E. Mamani

• Originador

Universidad Nacional de San Agustín de Arequipa, Peru

Arequipa

PE

http://orcid.org/0000-0002-2566-6410

C. R. Luque Fernández

• Proveedor De Los Metadatos ●
• Originador ●
• Punto De Contacto

Universidad Nacional de San Agustín de Arequipa

Arequipa

PE

http://orcid.org/0000-0001-8050-461X

Montse Ferrer

• Proveedor De Los Metadatos

Managing Editor

Arxius de Miscel·lània Zoològica, Museu de Ciències Naturals de Barcelona

Ps Picasso s/n

08003 Barcelona

Barcelona

ES

montseferrerf@gmail.com

Cobertura geográfica

The study was conducted in Punta La Metalera in the Islay district of the city of Arequipa, 10 km northeast of Mollendo (-72.111527 °S, -17.015428 °W). Punta La Metalera is a cape that has varied landforms: cliffs, shoreline, rocky outcrops with steep slopes and guano-covered surface, and algae vegetation. Its surrounding areas are islets.

Cobertura taxonómica

No hay descripción disponible

Cobertura temporal

Datos del proyecto

The South American Pacific coast is one of the most biologically productive habitats on Earth and its influence on the communities and relationships therein is strong (Flores et al., 2013). In the case of Peru, the coast is bathed by the Peruvian or Humboldt current (Brack and Mendiola, 2000), which together with the extensive areas of coastal upwelling and the dynamics in the processes of nutrients and biogeochemical cycles (Morón, 2000; Graco et al., 2007) has produced the conditions for great biodiversity. This diversity is especially based on the extremely high primary productivity that is reflected in an abundance of zooplankton fish, birds and marine mammals (Chavez et al., 2008; Montecino and Lange, 2009; Cisterna, 2020). The most important seabird habitats along this coast consist of a system of islands, islets, and guano points which in many cases host unique bird species (Lara et al., 2008). The study of bird population dynamics in this system is limited, however (Tovar et al., 1969, Tovar et al., 1987; Goya, 2000; Weimerskirch et al., 2012; Figueroa, 2013; SERNANP, 2016). Besides, these bird populations are under pressure from natural events such as the phenomenon "El Niño" (Flores et al., 2013), which had severe repercussions. They are also affected by anthropic activities such as the extraction of guano (with the greatest boom occurring in the 19th century) and over fishing which affect the availability of food for many of these birds (Tovar et al., 1987; Apaza and Figari, 1999; Brack and Mendiola, 2000). Additionally, species respond differently to environmental and physiographic factors (Véliz et al., 2002), as monthly variations have shown on one or some specific species (González and Málaga, 1997). As fluctuations can strongly influence a system's functionality they should be monitored. A vast portion of coastal economic activities are related to the fishing ports and may therefore be linked to the population dynamics within bird communities. The south of Peru houses the country’s second largest international port (Matarani), the international terminal port (TISUR in Islay), and many small-scale port infrastructures, such as Punta La Metalera (El Faro). The main activities in Punta La Metalera are tourism, recreation, and the extraction of fish, shellfish, algae and guano. However, information that would help decision-making regarding development plans (Järvinen and Väisänen, 1979; Koskimies, 1989; Bibby et al., 1992) of the urban-rural population and nearby activities for sustainable development is lacking. Such information could provide multiple benefits for biodiversity conservation at a regional scale (Luna-Jorquera et al., 2012). The aim of the present study was to evaluate changes in the bird community at Punta La Metalera on a temporal scale in terms of species composition and richness-abundance, and to characterize habitat use and behavior of the species present in late 2019 and early 2020.

Personas asociadas al proyecto:

Métodos de muestreo

We conducted 24 counts from October 2019 to March 2020 using the point count method (Bibby et al. 1992), covering around 700 m of coastline. Counting points were set for the four zones, selected based on accessibility (most of the cape coastline was difficult to access). Six trips were made (one per month). On each trip we conducted three censuses: one between 5:30 a.m. and 9:30 a.m., a second between 12 p.m. and 2.30 p.m., and a third between 3:30 p.m. and 6:00 p.m.). We spent 20 minutes at each point (Bibby et al., 1992), making a total effort of 1,680 minutes (28 hours). We only counted birds that were perched on land or at sea, not those in flight. We did not exclude only coastal birds as our aim was also to look at behavior and habitat use. However, all birds sighted (all species passing through any area) were recorded for richness. At each point, the species present were identified and quantified using Bushnell, Tasco, Nikon, and Galileo binoculars (10x50, 12x45, and 90x80), Fujifilm camera (eight megapixels), field cards, and notes. Before starting the census we waited for five minutes for the birds to adapt to our presence as our arrival caused a slight displacement of some of them, especially those on the edges. The birds we considered as coastal seabirds were species of the orders Anseriformes, Ciconiiformes, Charadriiformes, Pelecaniformes Suliformes, Podicipediformes, Falconiformes, Passeriformes (Acosta et al., 2013), Sphenisciformes, and Cathartiformes. To identify the species, we used the guides of Jaramillo (2003), Tabini and Paz-Soldán (2007) and Schulenberg et al. (2010). The taxonomic nomenclature was taken from the SACC (Remsen et al., 2020), and the category of species risk was assigned using the IUCN Red List of Threatened Species.

Descripción de la metodología paso a paso:

1. We analyzed the temporal fluctuation by comparing months and comparing the mean values for each month of the abundance variation using ANOVA (one way, p < 0.05.). Data normality was previously evaluated using the Shapiro test (Peña-Villalobos et al., 2012) and normalized using the bestNormalize (Peterson, 2020) package in RStudio (RStudio Team, 2020). The species occurrence frequency (SOF) was analyzed considering six categories (Nores, 1996 cited by Brandolin et al, 2007), which are: i) very common (0.8–1), ii) common (0.6–0.8), iii) frequent (0.4–0.6), iv)scarce (0.2–0.4), v) occasional (0.1–0.2), and vi) accidental (< 0.1). These values were obtained for each species as the number of months in which the species was present, divided by the total number of sampled months. For the species relative abundance (SRA), we considered five categories: i) abundant (90–100 %), ii) common (65–89 %), iii) moderately common (31–64 %), iv)uncommon (10–30 %), and v) rare (1–9 %). These percentages were obtained for each species as the number of individuals of a species divided by the total number of individuals considering all species and multiplied by 100 (Güitrón–López et al., 2018). The dissimilarity of species abundance between months was calculated using the index of similarity (Bray-Curtis), 1 - (2c/S1 + S2), where S1 and S2 are the number of species in sample months 1 and 2, respectively, and c is the number of species present in both sample months. This dissimilarity was represented with dendrograms using the UPGMA method with PAST v.2.17 (Kusch et al. 2008 cited by Peña-Villalobos et al., 2012) to establish a similarity relationship between assessment months on species/abundance fluctuations. And finally, habitat use (land-use) was analyzed comparing the birds' behavior s per month, for which we summed up each behavior record.

Referencias bibliográficas

1. Vilca Taco, L.M., Mamani T., E., Luque Fernández, C. R., 2021. Seabird temporal composition, abundance and habitat use in “Punta La Metalera” (Arequipa), Southern Peru. Arxius de Miscel·lània Zoològica, 19: 161-181, https://doi.org/10.32800/amz.2021.19.0161 https://doi.org/10.32800/amz.2021.19.0161

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