The Bias of Complementarity Hotspots toward Marginal Populations

Abstract: It has been suggested that using complementarity to identify networks of important areas for conserving biodiversity may preferentially select areas within the margins of species ranges. We tested this idea by examining the location of complementarity hotspots in relation to two measures of range core-periphery. The first measures patterns of aggregation among records within each species' range to identify areas within the core (i.e., areas with aggregated distributions) and periphery (i.e., areas with scattered distributions) of the range. The second measures spatial turnover among species to identify areas with a high density of range edges. For three selected groups of terrestrial vertebrates in Europe—mammals, birds, and herptiles—areas chosen based on complementarity were located within the margins of species' ranges more often than expected by chance. This pattern was consistent for the two measures of core-periphery we used. The bias of complementarity hotspots toward marginal populations is especially important for species with restricted range sizes. If extinctions are determined mainly by demographic factors, then selecting areas at the peripheries of species' ranges might be a poor option. But if extinctions are determined mainly by extrinsic factors, then peripheral populations might be important to ensure the long-term persistence of species.     

Molecular response of the sponge Suberites domuncula to bacterial infection

The aim of this study was the documentation of the molecular immune response of Suberites domuncula upon bacterial infection. Additionally, the bacteria that are naturally present in the sponge after prolonged aquarium maintenance were characterized. After 6 months of maintenance of S. domuncula in seawater aquaria, only one bacterial 16S rDNA sequence could be recovered, which belongs to the genus Pseudomonas. Concomitantly, morphologically uniform bacteria were found encapsulated in bacteriocytes. These findings indicate that certain bacteria, possibly of the genus Pseudomonas, are able to persist for long periods in host bacteriocytes. Subsequent to performing a previously established infection assay with S. domuncula, a potentially pathogenic Vibrio sp. was isolated from the tissues. Furthermore, the host tissue disintegrated and asexual propagation bodies (gemmules) were formed. In order to gain insights into the molecular events occurring after bacterial infection, the stress-response kinases, p38 protein kinase and JNK protein kinase, were analyzed. It is demonstrated that these two kinases are activated (phosphorylated) upon incubation of the tissue with the bacterial endotoxin lipopolysaccharide (LPS). Moreover, LPS strongly inhibits protein synthesis. It is concluded that there are many functionally different interactions between S. domuncula and bacteria and that the animal possesses mechanisms to differentiate between bacteria and to respond accordingly.     

Genetic, morphological, and chemical divergence in the sponge genus Latrunculia (Porifera: Demospongiae) from New Zealand

We undertook a comprehensive study of Latrunculia in New Zealand to determine the relationship between taxonomic, environmental, and chemical variation within the genus. Sponges were collected from five locations around New Zealand: Three Kings Islands, Tutukaka, Wellington, Kaikoura, and Doubtful Sound. Allozyme electrophoresis at nine polymorphic loci indicated that sponges from each geographic location were genetically distinct, and that they displayed genetic differences of the magnitude usually associated with reproductively isolated species (Nei's D between locations =0.375-2.476). Additionally, the comparisons revealed that the green and brown colour morphs of Latrunculia that are sympatric at Three Kings Islands and Kaikoura are distinct from each other, and that there are two genetic groups within the green sponges in Doubtful Sound. On the basis of genetic data we conclude that there are at least eight species of Latrunculia in New Zealand waters, not one to four as had been previously thought. Morphological comparisons of the eight genetic species based on skeletal characters (i.e. skeletal organisation of the choanosome, spicule composition, size, and geometry) indicated that the eight Latrunculia species fell into only two morphological groups that could be easily diagnosed on the basis of discorhabd type. Within these two primary morphological groups, skeletal characteristics among the eight species largely overlap and are not diagnostic. These findings emphasise the limitations of traditional taxonomic methods based solely on skeletal characters for distinguishing species of Latrunculia. However, multivariate analysis (MANOVA and CDA) based on six measured skeletal variables did reveal significant morphological variation among the species (Pillai's Trace=3.28, F=6.90, P<0.0001), supporting the division of the genus into eight species. Comparisons of chemical extracts from Latrunculia also showed that the amounts of five different bioactive compounds (discorhabdins A, B, C, D, and J) varied predictably among the eight species. This finding suggests that discorhabdin variation within Latrunculia, previously thought to be associated with intra-specific environmental variability, is more likely to reflect differences among species rather than phenotypic plasticity. Our results also highlight the importance of thorough taxonomic studies associated with marine natural products research to understand fully the variation in bioactive properties among individuals. The potential processes underlying the unusually high speciation rates in New Zealand Latrunculia that are indicated in our study are discussed.     

A Systematic Test of an Enterprise Strategy for Community-Based Biodiversity Conservation

Abstract: A commonly held belief is that if people can benefit financially from enterprises that depend on nearby forests, reefs, and other natural habitats, then they will take action to conserve and sustainably use them. The Biodiversity Conservation Network brought together conservation and development organizations and local communities to systematically test this hypothesis across 39 conservation project sites in Asia and the Pacific. Each project implemented one or more community-based enterprises such as setting up an ecotourism lodge, distilling essential oils from wild plant roots, producing jams and jellies from forest fruits, harvesting timber, or collecting marine samples to test for pharmaceutical compounds. Each project team collected the biological, enterprise, and social data necessary to test the network's hypothesis. We present the results of this test. We found that a community-based enterprise strategy can lead to conservation, but only under limited conditions and never on its own. We summarize the specific conditions under which an enterprise strategy will and will not work in a decision chart that can be used by project managers to determine whether this strategy might make sense at their site. We also found that an enterprise strategy can be subsidized and still create a net gain that pays for conservation. Based on our experiences, we recommend developing "learning portfolios" that combine action and research to test other conservation strategies.     

Regulation of ovary activation in worker honey-bees (Apis mellifera): larval signal production and adult response thresholds differ between anarchistic and wild-type bees

One-day-old anarchistic (selected for successful worker reproduction) and wild-type honey-bee workers were introduced into queenright colonies of honey-bees of two treatments. In treatment 1, all eggs and larvae were offspring of queens from an anarchistic line. In treatment 2, all eggs and larvae were offspring of wild-type queens. In both treatments, adult workers were wild type. This experimental arrangement was used to test the importance of larval genotype on ovary activation in young adult workers. After 12 days, the introduced bees were dissected to determine the frequency of ovary activation. In those colonies provided with wild-type brood, 0% of introduced wild-type bees and 16% of anarchistic bees had activated ovaries. In those colonies provided with anarchistic brood, 13% of introduced wild-type bees and 41% of anarchistic bees had activated ovaries. These results strongly support the hypothesis that selection for high levels of worker reproduction in anarchistic stocks has reduced the amount or composition of brood pheromones produced by larvae that normally signal workers to refrain from reproduction. They also suggest that anarchistic workers have a higher threshold for these signals than wild-type bees.     

The role of periodic boundary forcing in plankton pattern formation

We consider one and two-dimensional minimal models in plankton dynamics. The influence of oscillating boundary forcing functions as agents for triggering pattern formation is discussed. In particular it is found that in these conditions population waves arise for one dimensional models, while for two dimensional models, different amplitudes and frequencies in the boundary forcing generate definite patterns, mimicking the boundary term. This happens even though the model we investigate is very simple. The emergence of these features is an interesting metaphor for the fundamental biological problem of how pattern formation processes may be inevitable in natural heterogeneous ecosystems.     

Variability in the phytoplankton community of Kavaratti reef ecosystem (northern Indian Ocean) during peak and waning periods of El Niño 2016

El Niño, an interannual climate event characterized by elevated oceanic temperature, is a prime threat for coral reef ecosystems worldwide, owing to their thermal threshold sensitivity. Phytoplankton plays a crucial role in the sustenance of reef trophodynamics. The cell size of the phytoplankton forms the “master morphological trait” with implications for growth, resource acquisition, and adaptability to nutrients. In the context of a strong El Niño prediction for 2015–2016, the present study was undertaken to evaluate the variations in the size-structured phytoplankton of Kavaratti reef waters, a major coral atoll along the southeast coast of India. The present study witnessed a remarkable change in the physicochemical environment of the reef water and massive coral bleaching with the progression of El Niño 2015–2016 from its peak to waning phase. The fluctuations observed in sea surface temperature, pH, and nutrient concentration of the reef water with the El Niño progression resulted in a remarkable shift in phytoplankton size structure, abundance, and community composition of the reef waters. Though low nutrient concentration of the waning phase resulted in lower phytoplankton biomass and abundance, the diazotroph Trichodesmium erythraeum predominated the reef waters, owing to its capability of the atmospheric nitrogen fixation and dissolved organic phosphate utilization.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.