Reproductive parameters and potential geographical distribution of nesting areas of Grus canadensis nesiotes (Aves, Gruidae) in Cuba: conservation implications
Grus canadensis nesiotes (Cuban sandhill crane) is an endemic and endangered subspecies from Cuba. Protection of wetland habitats is essential for survival of this species, but studies that could contribute to its management and conservation are lacking. In this study we recorded the reproductive parameters of Grus canadensis nesiotes in eight breeding seasons between 2005 and 2015 in a wetland of Cuba. We modeled and characterized the potential geographical distribution of the nesting areas, analyzing its representation within protected areas. Maximum entropy algorithm and habitat variables were used for modeling (100 m of pixel size). To characterize the potential distribution we calculated each land–use–vegetation within the potential distribution. We used the same procedure to determine the extent of the protected area. A hundred and fifty–one nests were located in marsh grasslands. These nests were simple platforms built on wet soil/water; the largest nests were observed in 2006. Seventy percent of nests had two eggs (1.7 eggs/nest) and 63.5% were successful with 1.6 chicks per successful nest. The potential nesting habitat is a narrow stretch (242 km2) located in the center of the wetland. The area with high probability of presence makes up 13.8% of the predicted distribution. Sixty percent of marsh grassland of the study area was included in the potential distribution, while the proportion of crops (1.2%) and pastures (2.1%) was low. Managed protected areas cover only 39.1% of the potential distribution of the nesting sites and 12% of the high probability areas. We propose three priority sites to study and monitor nesting of the subspecies. Species conservation actions should consider the potential geographical distribution of nesting sites both inside and outside the protected areas.
Cuban sandhill crane, Reproduction, Conservation, Ecological niche modeling
Reception date: 4 I 16 | Acceptation date: 9 III 17 | Publication date: 30 III 17
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