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Migration patterns and seasonal forest use by birds in the Brazilian Pantanal

Published online by Cambridge University Press:  18 May 2017

JOÃO BATISTA DE PINHO*
Affiliation:
Núcleo de Estudos Ecológicos do Pantanal (NEPA)/Instituto de Biociências, Universidade Federal de Mato Grosso, 78060-900, Cuiabá - MT, Brazil; and Instituto Nacional de Ciência e Tecnologia em Áreas Úmidas (INAU).
MÔNICA ARAGONA
Affiliation:
Instituto de Engenharias - CUVG, Universidade Federal de Mato Grosso, 78060-900, Cuiabá - MT, Brazil; Núcleo de Estudos Ecológicos do Pantanal (NEPA)/Instituto de Biociências, Universidade Federal de Mato Grosso, 78060-900, Cuiabá - MT, Brazil; and Instituto Nacional de Ciência e Tecnologia em Áreas Úmidas (INAU).
KARLO YOSHIHIRO PIOTO HAKAMADA
Affiliation:
Núcleo de Estudos Ecológicos do Pantanal (NEPA)/Instituto de Biociências, Universidade Federal de Mato Grosso, 78060-900, Cuiabá - MT, Brazil.
MIGUEL ÂNGELO MARINI
Affiliation:
Departamento de Zoologia, IB, Universidade de Brasília, 70910-900, Brasília, DF, Brazil.
*
*Author for correspondence; e-mail: pinhoufmt@gmail.com
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Summary

The use of forest habitats and migratory patterns are still unclear for tropical birds. Some are described herein for the Pantanal wetlands of Brazil. Thus, our aim was to describe different patterns of forest habitat use by birds and classify the birds’ migration patterns for the northern Pantanal region, Brazil. From September 1999 to December 2003, we sampled four forest types, during which we collected standardised data with mist-net captures and point counts, with additional ad lib. observations. We recorded 214 bird species: 113 (52.8%) were total habitat generalists; 41 (19.2%) were forest generalists; 19 (8.9%) were flooded habitat specialists; and 28 (13.1%) were not classified due to the low number of records; three other categories of habitat use divide the remaining 6% of records. About half of the species showed some migratory behaviour, these were classified by us according to the season they spent in the area: 121 species (56.5%) as residents, 28 (13.1%) as run-off and dry migrants, 11 (5.1%) as run-off (winter) migrants, eight (3.7%) as dry (breeding) migrants, eight (3.7%) as dry and flooding (summer) migrants, eight (3.7%) as flooding migrants, three (1.4%) as flooding and run-off migrants, and 27 (12.6%) as uncommon. We constructed community occupancy models with six of the eight patterns of migration described; flooding migrants and run-off migrants were not modelled since the few species recorded also had very few detections. As expected, the model confirmed that species from all six tested migration patterns arrive and depart from the Pantanal across the seasons. Contrary to most Neotropical forests, there was a high percentage (43.5%) of non-resident species. The results show the need of investing heavily in preserving different landscape units within the Pantanal, but also in the surrounding Cerrado region, in order to conserve resident and short distance intra-tropical migrants.

Information

Type
Research Article
Copyright
Copyright © BirdLife International 2017 
Figure 0

Table 1. Records of migrant or uncommon Pantanal species in the surrounding plateau for each month of the year. Numbers indicate the number of records (banded individuals or sightings) of each species in the sites sampled (Appendix S2). Grey bars indicate the months that each species was recorded in the Pantanal.

Figure 1

Figure 1. Migratory status of Passeriformes and non-Passeriformes bird species registered at Pirizal, Pantanal of Poconé, Brazil.

Figure 2

Figure 2. Examples of monthly variation of index of point abundance for resident species (Cercomacra melanaria), the flooding (Chloroceryle inda) and breeding migrant (Momotus momota) recorded at Pirizal, Pantanal of Poconé, Brazil.

Figure 3

Table 2. Ranking of the concurrent community models for the patterns of migration. The probability of the species being present on the dry season is set as constant (.) over the habitats in all models, represented as (ψ(.)). The first three models consider that this probability did not change on the flooding and dry period, because it did not include habitat immigrations, γ, and habitat emigrations, ε. The last three models are multi season (s) models, which were best on most of the cases. They defined the immigrations and emigrations as seasonally varied ((γ(s), ε(s)). Five of the migration patterns had the selected models, ∆AIC = 0, that described the phytophysiognomy (phy) effect over detectability stronger than the season effect (p(phy) and p(s)).

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