Population Trends of a Mixed-Species Colony of Humboldt and Magellanic Penguins in Southern Chile after Establishing a Protected Area

Worldwide marine protected areas (MPAs) have been designated to protect marine resources, including top predators such as seabirds. There is no conclusive information on whether protected areas can improve population trends of seabirds when these are further exploited as tourist attractions, an activity that has increased in past decades. Humboldt Penguins (Spheniscus humboldti) and Magellanic Penguins (S. magellanicus) breed sympatrically on Puñihuil Islets, two small coastal islands off the west coast of Chiloé Island (41° S) in southern Chile that are subject to exploitation for tourism. Our goal was to compare the population size of the mixed colony of Humboldt and Magellanic Penguins before and after protection from unregulated tourism and freely roaming goats in 1997. For this purpose, two censuses were conducted in 2004 and 2008, and the numbers compared with those obtained in 1997 by other authors. The proportion of occupied, unoccupied, and collapsed/flooded burrows changed between years; there were 68% and 34% fewer collapsed burrows in 2004 and 2008, respectively, than in 1997. For the total number of burrows of both species, we counted 48% and 63% more burrows in 2004 and 2008, respectively, than in 1997. We counted 13% more burrows of Humboldt Penguins in 2008 than in 1997, and for Magellanic Penguins, we estimated a 64% increase in burrows in 2008. Presumably, this was as a result of habitat improvement attributable to the exclusion of tourists and the removal of goats from the islets. Although tourist visits to the islets are prohibited, tourism activities around the colonies are prevalent and need to be taken into account to promote appropriate management.

Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species–area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species–area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km × 10 km) and regional (290 km × 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.