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.     

Effect of temperature and humidity on formaldehyde emissions in temporary housing units

The effect of temperature and humidity on formaldehyde emissions from samples collected from temporary housing units (THUs) was studied. The THUs were supplied by the U.S. Federal Emergency Management Administration (FEMA) to families that lost their homes in Louisiana and Mississippi during the Hurricane Katrina and Rita disasters. On the basis of a previous study, four of the composite wood surface materials that dominated contributions to indoor formaldehyde were selected to analyze the effects of temperature and humidity on the emission factors. Humidity equilibration experiments were carried out on two of the samples to determine how long the samples take to equilibrate with the surrounding environmental conditions. Small chamber experiments were then conducted to measure emission factors for the four surface materials at various temperature and humidity conditions. The samples were analyzed for formaldehyde via high-performance liquid chromatography. The experiments showed that increases in temperature or humidity contributed to an increase in emission factors. A linear regression model was built using the natural log of the percent relative humidity (RH) and inverse of temperature (in K) as independent variables and the natural log of emission factors as the dependent variable. The coefficients for the inverse of temperature and log RH with log emission factor were found to be statistically significant for all of the samples at the 95% confidence level. This study should assist in retrospectively estimating indoor formaldehyde exposure of occupants of THUs.     

Seasonal water demand in Benin's agriculture

This paper describes and analyzes agricultural water demands for Benin, West Africa. Official statistical data regarding water quantities as well as knowledge on factors influencing the demand for water are extremely rare and often reveal national trends without considering regional or local differences. Thus policy makers usually work with this estimated and aggregated data, which make it very difficult to adequately address regional and local development goals. In the framework of an interdisciplinary analysis the following paper provides insight into water quantification and detects water problems under seasonal aspects for agriculture according to regional differences. Following the definition of the Food and Agriculture Organization [FAO, 1995. Water Report 7. Irrigation in Africa in Figures. Rome] agriculture is divided into irrigation and livestock watering, which were analyzed using different field methods. The study reveals that although water supply in absolute terms seems to be sufficient in Benin, seasonal water problems occur both in irrigation and in livestock management. Thus arising seasonal water problems are not the consequence of general water scarcity but more linked to three major problems. These problems emerge from difficulties in technical equipment and financial means of farmers, from the specific local conditions influencing the access to water sources and the extraction of groundwater, and third from the overall low organizational structure of water management. Therefore regional differences as well as a general improvement of knowledge on better management structures, technical know how, and access to credits for farmers need to be considered in national strategies in order to improve the agricultural water usage in Benin.     

II. Incidence of Acute Respiratory Illness

A study of acute respiratory illness was conducted from November 1968 through April 1969 among families residing in an area of relatively high nitrogen dioxide exposure, in an area of elevated suspended particulate exposure, and in two control areas of Greater Chattanooga. Respiratory illness rates were consistently higher in all family segments in the high-nitrogen dioxide exposure area when rates were averaged for the entire 24 weeks of study, the A₂/Hong-Kong epidemic period, or post-epidemic interval. A relative excess in respiratory illness of 18.8 percent was found among families exposed to elevated NO₂ concentrations and an excess of 10.4 percent was found among families in the elevated-suspended particulate exposure area.     

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.     

Kin discriminators in the eusocial sweat bee <Emphasis Type="Italic">Lasioglossum malachurum</Emphasis>: the reliability of cuticular and Dufour’s gland odours

The ability to discriminate degrees of relatedness may be expected to evolve if it allows unreciprocated altruism to be preferentially directed towards kin (Hamilton in J Theor Biol 7:1–16, 1964). We explored the possibility of kin recognition in the primitively eusocial halictid bee Lasioglossum malachurum by investigating the reliability of worker odour cues that can be perceived by workers to act as indicators of either nest membership or kinship. Cuticular and Dufour’s gland compounds varied significantly among colonies of L. malachurum, providing the potential for nestmate discrimination. A significant, though weak, negative correlation between chemical distance and genetic relatedness (r = −0.055, p < 0.001) suggests a genetic component to variation in cuticular bouquet, but odour cues were not informative enough to discriminate between different degrees of relatedness within nests. This pattern of variation was similar for Dufour’s gland bouquets. The presence of unrelated individuals within nests that are not chemically different from their nestmates suggests that the discrimination system of L. malachurum is prone to acceptance errors. Compounds produced by colony members are likely combined to generate a gestalt colony chemical signature such that all nestmates have a similar smell. The correlation between odour cues and nest membership was greater for perceived compounds than for non-perceived compounds, suggesting that variability in perceived compounds is a result of positive selection for nestmate recognition despite potentially stabilising selection to reduce variability in odour differences and thereby to reduce costs derived from excessive intracolony nepotistic behaviour.