Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.     

Loss of Competition in the Outside Host Environment Generates Outbreaks of Environmental Opportunist Pathogens

Environmentally transmitted pathogens face ecological interactions (e.g., competition, predation, parasitism) in the outside-host environment and host immune system during infection. Despite the ubiquitousness of environmental opportunist pathogens, traditional epidemiology focuses on obligatory pathogens incapable of environmental growth. Here we ask how competitive interactions in the outside-host environment affect the dynamics of an opportunist pathogen. We present a model coupling the classical SI and Lotka–Volterra competition models. In this model we compare a linear infectivity response and a sigmoidal infectivity response. An important assumption is that pathogen virulence is traded off with competitive ability in the environment. Removing this trade-off easily results in host extinction. The sigmoidal response is associated with catastrophic appearances of disease outbreaks when outside-host species richness, or overall competition pressure, decreases. This indicates that alleviating outside-host competition with antibacterial substances that also target the competitors can have unexpected outcomes by providing benefits for opportunist pathogens. These findings may help in developing alternative ways of controlling environmental opportunist pathogens.     

Spatio-Temporal Environmental Correlation and Population Variability in Simple Metacommunities

Natural populations experience environmental conditions that vary across space and over time. This variation is often correlated between localities depending on the geographical separation between them, and different species can respond to local environmental fluctuations similarly or differently, depending on their adaptation. How this emerging structure in environmental correlation (between-patches and between-species) affects spatial community dynamics is an open question. This paper aims at a general understanding of the interactions between the environmental correlation structure and population dynamics in spatial networks of local communities (metacommunities), by studying simple two-patch, two-species systems. Three different pairs of interspecific interactions are considered: competition, consumer–resource interaction, and host–parasitoid interaction. While the results paint a relatively complex picture of the effect of environmental correlation, the interaction between environmental forcing, dispersal, and local interactions can be understood via two mechanisms. While increasing between-patch environmental correlation couples immigration and local densities (destabilising effect), the coupling between local populations under increased between-species environmental correlation can either amplify or dampen population fluctuations, depending on the patterns in density dependence. This work provides a unifying framework for modelling stochastic metacommunities, and forms a foundation for a better understanding of population responses to environmental fluctuations in natural systems.     

A plasmid-based reverse genetics system for animal double-stranded RNA viruses

Mammalian orthoreoviruses (reoviruses) are highly tractable experimental models for studies of double-stranded (ds) RNA virus replication and pathogenesis. Reoviruses infect respiratory and intestinal epithelium and disseminate systemically in newborn animals. Until now, a strategy to rescue infectious virus from cloned cDNA has not been available for any member of the Reoviridae family of dsRNA viruses. We report the generation of viable reovirus following plasmid transfection of murine L929 (L) cells using a strategy free of helper virus and independent of selection. We used the reovirus reverse genetics system to introduce mutations into viral capsid proteins sigma1 and sigma3 and to rescue a virus that expresses a green fluorescent protein (GFP) transgene, thus demonstrating the tractability of this technology. The plasmid-based reverse genetics approach described here can be exploited for studies of reovirus replication and pathogenesis and used to develop reovirus as a vaccine vector.     

Biochemical Heterogeneity of the Lipid Status of the Prespawn Eggs of Pink Salmon <Emphasis Type="Italic">Oncorhynchus gorbuscha</Emphasis> (Walbaum 1792) (Varzuga River,White Sea basin)

A comparative analysis of lipid and fatty acids contents in certain portions of female gonads—head, central, and caudal—of the prespawned pink salmon Oncorhynchus gorbusha has been performed. Heterogeneity of the lipid status of eggs located in certain portions of ovaries has been found: in the head portion, a high level of physiologically important eicosapentaenoic 20:5(n-3) and docosahexaenoic 22:6(n-3) fatty acids has been registered, which coincided with a higher intensity of lipid metabolism evidenced by higher ratio of 16:0/18:1(n-9); the central portion is characterized by a low level of total lipids due to phospholipids (including phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin) and cholesterol; in the caudal portion, a high amount of certain phospholipids (phosphatidylcholine, phosphatidylethanolamine, lysophosphatidylcholine, sphingomyelin, and phosphatidylinositol) has been found. Such heterogeneity in certain portions of ovaries indicates asynchronous biochemical processes in oocytes of these portions that finally affects fertilization, growth and development of embryos, and further differentiation of the young fish.     

A specific and rapid neural signature for parental instinct

Darwin originally pointed out that there is something about infants which prompts adults to respond to and care for them, in order to increase individual fitness, i.e. reproductive success, via increased survivorship of one's own offspring. Lorenz proposed that it is the specific structure of the infant face that serves to elicit these parental responses, but the biological basis for this remains elusive. Here, we investigated whether adults show specific brain responses to unfamiliar infant faces compared to adult faces, where the infant and adult faces had been carefully matched across the two groups for emotional valence and arousal, as well as size and luminosity. The faces also matched closely in terms of attractiveness. Using magnetoencephalography (MEG) in adults, we found that highly specific brain activity occurred within a seventh of a second in response to unfamiliar infant faces but not to adult faces. This activity occurred in the medial orbitofrontal cortex (mOFC), an area implicated in reward behaviour, suggesting for the first time a neural basis for this vital evolutionary process. We found a peak in activity first in mOFC and then in the right fusiform face area (FFA). In mOFC the first significant peak (p<0.001) in differences in power between infant and adult faces was found at around 130 ms in the 10-15 Hz band. These early differences were not found in the FFA. In contrast, differences in power were found later, at around 165 ms, in a different band (20-25 Hz) in the right FFA, suggesting a feedback effect from mOFC. These findings provide evidence in humans of a potential brain basis for the "innate releasing mechanisms" described by Lorenz for affection and nurturing of young infants. This has potentially important clinical applications in relation to postnatal depression, and could provide opportunities for early identification of families at risk.     

Epiphytic macrolichen community correlates with modeled air pollutants and forest conditions

Novel systems combining bioindicators, models, and remote sensing are possible cost-effective methods to monitor regional-scale pollution. Epiphytic macrolichen communities have been widely used as air pollution bioindicators, however these communities are also affected by microclimate conditions as influenced by forest structure. We used the Finnish epiphytic macrolichen survey method SFS5670 to collect data in 27 spruce and birch dominated forests in southern Finland and northwestern Russia. The method measures the abundance and physiological damage of Hypogymnia physodes and Bryoria spp., and the frequency of 13 epiphytic macrolichen species of known sensitivity which can be used to calculate the widely used Index of Atmospheric Purity (IAP). The location of the sites represents an east–west gradient of air pollution conditions of SO₂, SO₄^2?, NO₂, NH₃ + NH₄⁺, and HNO₃ + NO₃^?. We also recorded living and dead forest structure characteristics at these sites, which we initially chose to be as similar as possible on either side of the border. Abundance and damage of H. physodes were correlated with forest structure but not with air pollution, indicating that these macrolichen variables may not be reliable bioindicators at low air pollution concentrations. However, the Index of Atmospheric Purity, calculated from observed presence/absence data of multiple epiphytic macrolichen species, was strongly correlated with sulfur and nitrogen pollutant concentrations. These results suggest that the IAP as calculated using data from the Finnish epiphytic macrolichen survey method may be a useful air pollution indicator in combination with modeled data, even in relatively clean regions.     

Environmental Variation Generates Environmental Opportunist Pathogen Outbreaks

Many socio-economically important pathogens persist and grow in the outside host environment and opportunistically invade host individuals. The environmental growth and opportunistic nature of these pathogens has received only little attention in epidemiology. Environmental reservoirs are, however, an important source of novel diseases. Thus, attempts to control these diseases require different approaches than in traditional epidemiology focusing on obligatory parasites. Conditions in the outside-host environment are prone to fluctuate over time. This variation is a potentially important driver of epidemiological dynamics and affect the evolution of novel diseases. Using a modelling approach combining the traditional SIRS models to environmental opportunist pathogens and environmental variability, we show that epidemiological dynamics of opportunist diseases are profoundly driven by the quality of environmental variability, such as the long-term predictability and magnitude of fluctuations. When comparing periodic and stochastic environmental factors, for a given variance, stochastic variation is more likely to cause outbreaks than periodic variation. This is due to the extreme values being further away from the mean. Moreover, the effects of variability depend on the underlying biology of the epidemiological system, and which part of the system is being affected. Variation in host susceptibility leads to more severe pathogen outbreaks than variation in pathogen growth rate in the environment. Positive correlation in variation on both targets can cancel the effect of variation altogether. Moreover, the severity of outbreaks is significantly reduced by increase in the duration of immunity. Uncovering these issues helps in understanding and controlling diseases caused by environmental pathogens.