Differential effects of increased corticosterone on behavior at the nest and reproductive output of chick-rearing Adélie penguins

Glucocorticoid hormones (GCs) are important mediators of physiological and behavioral responses to stress. While many studies have evaluated the environmental, behavioral, or physiological correlates of GCs and their effects on reproductive performances, further work is needed to clarify the relationship between GCs and fitness. Assessing the effects of increased GC levels on specific behaviors of breeding animals should improve our understanding of how GCs affect parental care. In this experimental study, we measured the effects of an experimental increase in corticosterone (CORT, the main avian GC) levels on the behavior of free-living male Adélie penguins (Pygoscelis adeliae) within the colony, their reproductive output, and the indirect consequences of both on the behavior of their partners. We show that increased CORT levels in males decreased their foraging time at sea while increased their attendance at the nest, although their attentiveness toward the nest itself decreased. In addition, treated males spent more time on comfort behaviors (e.g., preening), vocalizing, and engaging in positive social interactions relative to controls. Treatment further affected the behavior of their partners, but not chick begging and feeding rates. Penguins with increased CORT levels also exhibited decreased reproductive output. Previous studies of Adélie penguins in different life history stages and environmental conditions suggest that the consequences of CORT treatment on reproductive performance are context-dependent. In addition to the potential delay in the effects of increased CORT levels on reproduction, this context dependence should be taken into account when studying the behavior of free-living animals in relation to stress-inducing situations.     

Regulating insect resistance management: the case of non-Bt corn refuges in the US

In this paper, we analyze the insect resistance management (IRM) plan put in place by the US Environmental Protection Agency (EPA) to delay the evolution of resistance to Bt corn in natural populations of the European corn borer, Ostrinia nubilalis Hübner. This IRM plan is the most impressive mandatory IRM system ever developed. It forms a coherent whole and includes mandatory refuges, actions to increase growers' compliance and a program for monitoring the evolution of resistance. However, our analysis suggests that two components of this IRM plan are not entirely satisfactory: growers' compliance and monitoring of the evolution of resistance. Moreover, the implementation of these two components of IRM has been required of the registrants, whose incentives for IRM are probably lower than the social optimum. Our analysis suggests that alternatives to the IRM plan currently in place could improve these two components.     

Capabilities and management utility of recreation impact monitoring programs

A recreation impact monitoring system was developed and applied in 1984–1986 and in 1991 to all backcountry river-accessed campsites within Delaware Water Gap National Recreation Area, Pennsylvania and New Jersey. Results suggest that actions implemented by park managers in response to problems identified by the initial survey were highly effective in reducing resource degradation caused by camping. In particular, the elimination of some designated campsites and installation of anchored firegrates reduced the total area of disturbance by 50%. Firegrate installation provided a focal point that increased the concentration of camping activities, allowing peripheral areas to recover. As suggested by predictive models, additional resource degradation caused by increased camping intensities is more than offset by improvements in the condition of areas where use is eliminated. The capabilities and management utility of recreation impact monitoring programs, illustrated by the Delaware Water Gap monitoring program, are also presented and discussed.     

Moorhens have an internal representation of their own eggs

How do birds recognize their own eggs? Do they have a stored template for their own egg characteristics, or do they use another mechanism? Intraspecific brood parasitism is considered to be an additional reproductive tactic where females can increase their own reproductive success. Because of the costs involved in rearing young that are not their own, it will pay females to detect and reject the eggs of a parasite, although it is not known how they do this. Here, we show experimentally that moorhens will cease laying in a nest when their first egg is replaced with another hen’s egg but not when it is replaced with their own egg taken from an earlier clutch. This provides good evidence that birds have an internal representation of their own eggs and use this in decisions about whether to reject foreign eggs.     

Siblicide in Serengeti spotted hyenas: a long-term study of maternal input and cub survival

In the Serengeti National Park, Tanzania, large fluctuations of prey abundance alters the frequency at which spotted hyena (Crocuta crocuta) cubs are nursed and thus the total level of maternal input available to them. Maternal input is high when mothers feed on high densities of locally available migratory herbivores and low when mothers travel up to 70 km to forage. Using data from 19 cub cohorts on the incidence of siblicide (from monitoring the survival of 609 cubs in twin litters) and cub growth rates (from 195 cubs in twin litters) as a measure of maternal input, we demonstrate that the incidence of siblicide increased as average cohort growth rate declined. In total, there were 37 siblicides in 384 litters (9% of litters). When both cubs were alive, total maternal input in siblicidal litters was significantly lower than in non-siblicidal litters and the mean share of the dominant sib of 64.6% was significantly higher than the mean of 52.1% for dominant sibs of non-siblicidal litters. After siblicide, growth rates of siblicide victors substantially increased, demonstrating that mothers did not reduce maternal input after litter reduction. As a result, siblicide victors achieved a long-term growth rate similar to that of singletons and thus significantly increased their expected survival. We conclude that in spotted hyenas, high maternal input in lactation has favoured the evolution of facultative siblicide in populations inhabiting areas with low or fluctuating food resources.     

Integrated mangrove-shrimp cultivation: Potential for blue carbon sequestration

Globally, shrimp farming has had devastating effects on mangrove forests. However, mangroves are the most carbon-rich forests, with blue carbon (i.e., carbon in coastal and marine ecosystems) emissions seriously augmented due to devastating effects on mangrove forests. Nevertheless, integrated mangrove-shrimp cultivation has emerged as a part of the potential solution to blue carbon emissions. Integrated mangrove-shrimp farming is also known as organic aquaculture if deforested mangrove area does not exceed 50% of the total farm area. Mangrove destruction is not permitted in organic aquaculture and the former mangrove area in parts of the shrimp farm shall be reforested to at least 50% during a period of maximum 5 years according to Naturland organic aquaculture standards. This article reviews integrated mangrove-shrimp cultivation that can help to sequester blue carbon through mangrove restoration, which can be an option for climate change mitigation. However, the adoption of integrated mangrove-shrimp cultivation could face several challenges that need to be addressed in order to realize substantial benefits from blue carbon sequestration.     

Monitoring and assessing of landscape heterogeneity at different scales

In numerous studies, spatial and spectral aggregations of pixel information using average values from imaging spectrometer data are suggested to derive spectral indices and the subsequent vegetation parameters that are derived from these. Currently, there are very few empirical studies that use hyperspectral data, to support the hypothesis for deriving land surface variables from different spectral and spatial scales. In the study at hand, for the first time ever, investigations were carried out on fundamental scaling issues using specific experimental test flights with a hyperspectral sensor to investigate how vegetation patterns change as an effect of (1) different spatial resolutions, (2) different spectral resolutions, (3) different spatial and spectral resolutions as well as (4) different spatial and spectral resolutions of originally recorded hyperspectral image data compared to spatial and spectral up- and downscaled image data. For these experiments, the hyperspectral sensor AISA-EAGLE/HAWK (DUAL) was mounted on an aircraft to collect spectral signatures over a very short time sequence of a particular day. In the first experiment, reflectance measurements were collected at three different spatial resolutions ranging from 1 to 3 m over a 2-h period in 1 day. In the second experiment, different spectral image data and different additional spatial data were collected over a 1-h period on a particular day from the same test area. The differently recorded hyperspectral data were then spatially and spectrally rescaled to synthesize different up- and down-rescaled images. The normalised difference vegetation index (NDVI) was determined from all image data. The NDVI heterogeneity of all images was compared based on methods of variography. The results showed that (a) the spatial NDVI patterns of up- and downscaled data do not correspond with the un-scaled image data, (b) only small differences were found between NDVI patterns determined from data recorded and resampled at different spectral resolutions and (c) the overall conclusion from the tests carried out is that the spatial resolution is more important in determining heterogeneity by means of NDVI than the depth of the spectral data. The implications behind these findings are that we need to exercise caution when interpreting and combining spatial structures and spectral indices derived from satellite images with differently recorded geometric resolutions.     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.