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.     

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.     

The lipid status of young of the year mykiss <Emphasis Type="Italic">Parasalmo mykiss</Emphasis> and coho salmon <Emphasis Type="Italic">Oncorhynchus kisutch</Emphasis>

The young of the year mykiss Parasalmo mykiss and coho salmon Oncorhynchus kisutch which perform downstream migration and which stay in the coastal zone during the period of primary dispersion represent different phenotypic groups. They differ in weight, length, and lipid status. Such differentiation is a factor controlling the formation of intrapopulation diversity and of the life strategy of fish. It may determine the timing of smoltification in the future and, further on, of the return for spawning. There were found some analogies and differences in characteristics of lipid metabolism in the investigated species. The content of total lipids decreases by autumn in underyearlings of both species. Furthermore, changes in the content of particular lipid fractions are multidirectional and various scaled, seemingly being related to physiological preparation for the wintering.     

Special traits of tissue lipids of whitefish <Emphasis Type="Italic">Coregonus lavaretus</Emphasis> living in water bodies with different anthropogenous load

The impact of water pollution on the content of lipid components of the liver and eggs of whitefish Coregonus lavaretus is investigated. The content of triacylglycerols (TAG), sphingomyelin (SPM), phosphatidylinositol (PI), and phosphatidylserine (PS) is higher in the liver of whitefish from polluted waters being a part of adaptogenous reactions (modification of permeability of biomembranes, of activity of membrane enzymes, etc.) providing a possibility of the survival of fish under unfavorable ecological factors. The lipid spectra of whitefish gonads are more stable in comparison with the liver. This may be related to protection of the reproductive system from external influences.     

Enzymatic hydrolysis combined with mechanical shearing and high-pressure homogenization for nanoscale cellulose fibrils and strong gels

Toward exploiting the attractive mechanical properties of cellulose I nanoelements, a novel route is demonstrated, which combines enzymatic hydrolysis and mechanical shearing. Previously, an aggressive acid hydrolysis and sonication of cellulose I containing fibers was shown to lead to a network of weakly hydrogen-bonded rodlike cellulose elements typically with a low aspect ratio. On the other hand, high mechanical shearing resulted in longer and entangled nanoscale cellulose elements leading to stronger networks and gels. Nevertheless, a widespread use of the latter concept has been hindered because of lack of feasible methods of preparation, suggesting a combination of mild hydrolysis and shearing to disintegrate cellulose I containing fibers into high aspect ratio cellulose I nanoscale elements. In this work, mild enzymatic hydrolysis has been introduced and combined with mechanical shearing and a high-pressure homogenization, leading to a controlled fibrillation down to nanoscale and a network of long and highly entangled cellulose I elements. The resulting strong aqueous gels exhibit more than 5 orders of magnitude tunable storage modulus G' upon changing the concentration. Cryotransmission electron microscopy, atomic force microscopy, and cross-polarization/magic-angle spinning (CP/MAS) 13C NMR suggest that the cellulose I structural elements obtained are dominated by two fractions, one with lateral dimension of 5-6 nm and one with lateral dimensions of about 10-20 nm. The thicker diameter regions may act as the junction zones for the networks. The resulting material will herein be referred to as MFC (microfibrillated cellulose). Dynamical rheology showed that the aqueous suspensions behaved as gels in the whole investigated concentration range 0.125-5.9% w/w, G' ranging from 1.5 Pa to 105 Pa. The maximum G' was high, about 2 orders of magnitude larger than typically observed for the corresponding nonentangled low aspect ratio cellulose I gels, and G' scales with concentration with the power of approximately three. The described preparation method of MFC allows control over the final properties that opens novel applications in materials science, for example, as reinforcement in composites and as templates for surface modification.     

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re‐assign non identified species in each site to any of the other species found in the remaining sites. After each re‐assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re‐assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus‐resolution, family‐resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.     

Lipid Metabolism of Caddisfly Larvae at Low pH

The influence of low pH (5.0 and 4.0) on lipid metabolism of caddisfly larvae Hydropsyche contubernalis L. (Trichoptera) was studied in 48 h toxicity experiments. The results were correlated with lipid composition of caddisfly larvae directly isolated from natural water. Phospholipids, cholesterol, mono-, di-, triacylglycerols, and fatty acids were detected by thin-layer and liquid chromatography. Minimal environmental changes were shown to initiate the biochemical adaptation mechanisms strengthening the cellular membranes through their condensation due to additional phospholipid and cholesterol synthesis. In the natural medium the adaptation processes are more active than in the artificial medium. More serious changes, such as pH decrease to 4.0, suppress the adaptation processes in the first medium and terminate them in the second one.     

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.