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opencc-by-4.0Feb 2022View details →

State of biodiversity documentation in the Philippines: Metadata gaps, taxonomic biases, and spatial biases in the DNA barcode data of animal and plant taxa in the context of species occurrence data

<p>These files can be categorized into three groups: (1) raw datasets obtained from public databases (i.e., GBIF, BOLD, and GenBank), (2) manually edited files needed for parsing and analysis, and (3) supplementary files for spatial analysis. All are used in the examination of gaps and biases present in Philippine biodiversity data, which can direct research on the taxa and spatial regions that need more sampling.</p>

Fig. 2 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 2: Flowchart of steps and methods followed (AHP: Analytic Hierarchy Process, FM: Fuzzy Membership).

Fig. 7 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 7: Spatial representation of the Fishing pressure index from the small scale coastal fishery (FPc).

opencc-by-4.0Feb 2018View details →

Figure 3 in Effects of genetic relatedness, spatial distance, and context on intraspecific aggression in the red wood ant Formica pratensis (Hymenoptera: Formicidae)

Figure 3. Correlation between spatial distance and aggression levels in the field. Open circles correspond to monodomous colonies and filled circles correspond to the polydomous one.

opencc-by-4.0Feb 2018View details →

Figure 1. Map showing the localities where F in Effects of genetic relatedness, spatial distance, and context on intraspecific aggression in the red wood ant Formica pratensis (Hymenoptera: Formicidae)

Figure 1. Map showing the localities where F. pratensis colonies were sampled for the analysis of genetic relatedness and tested for their aggressive behavior towards each other. The numbers denote the localities. 1: Balaban village (N 41°49ʹ18ʺ, E 27°40ʹ44ʺ) containing three nests; B1, B2, and B3, 2: Asilbeyli village (N 41°39ʹ32ʺ, E 27°13ʹ50ʺ), one nest (As), 3: Ulukonak village (N 41°39ʹ35ʺ, E 27°01ʹ52ʺ) one nest (U), 4: Doğanköy village (N 41°56ʹ12ʺ, E 26°41ʹ20ʺ) one nest (D), and 5: Ahmetler village (N 42°00ʹ37ʺ, E 27°11ʹ12ʺ), three nests; Ah1, Ah2, and Ah3.

Fig. 1 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 1: Map of the study area.

Fig. 6 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 6: Scatterplot matrices for Large (A) and Linear (B) FM functions.

Fig. 8 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 8: High values of the FP c index as estimated by Local Moran's I test.

Fig. 5 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 5: Spatial representation of coastal vessels activity indexes (Ac).

Fig. 4 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 4: Spatial representation of the Coastal fishery suitability index (Sc).

Fig. 3 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive

Fig. 3: Spatial representation of the criteria ranking taken into account in MCDA.

opencc-zeroJul 2021View details →

Estimating migration of the cold-tolerant leaf beetle Gonioctena quinquepunctata inside a mountain range in a spatially explicit context

<p>The cold-tolerant leaf beetle <em>Gonioctena quinquepunctata</em> displays a large but fragmented European distribution and is restricted to mountain regions in the southern part of its range. Using a RAD-seq-generated large SNP data set (> 10,000 loci), we investigated the geographic distribution of genetic variation within the Vosges mountains, where the species is common. To translate this pattern of variation in an estimate of its capacity to disperse, we simulated SNP data under a spatially explicit model of population evolution and compared the simulated and real data with an approximate Bayesian computation (ABC) approach. For this purpose, we propose a new SNP statistic summarizing genetic variation in a spatially explicit context. The estimated number of effective migrants inferred with this statistic was compared to that derived from a combination of standard population genetic statistics often used in population genetic analyses. We conducted this ABC analysis with a relatively low number of data points compared to traditional ABC analyses, because spatially explicit models require long simulation times. A test of our overall strategy was conducted with simulated data and showed that it could provide a good estimate of the level of dispersal of an organism over its continuous geographic range. We suggest that the lower number of explored data points were at least partially compensated by the much larger number of simulations per data point associated with a large SNP data set. The results of our analyses suggested that this insect disperses well within the Vosges mountains, much more than was initially expected given the current and probably past fragmentation of its habitat and given the results of previous studies on genetic variation in other mountain leaf beetles.</p>

opencc-zeroAug 2023View details →

Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency

<p><span>Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs high).</span><span> We found that </span><span>bacteria were consistently associated with certain soil properties and both bacteria and fungi were consistently associated with plant community composition within different sites. Moreover, there was a microbial community signal that clearly distinguished high and low-productivity soils that was shared across different grasslands independent of their location in the world.</span><span> In this study, we show that </span><span>there is high congruence between predictors of bacterial and fungal community composition at different spatial scales and that regional productivity differences are typified by characteristic soil microbial communities across the grassland biome. These results suggest that it might be feasible to predict the overall effects of global changes on soil microbial community composition in different grasslands, as well as to discriminate fertile from infertile systems using generally applicable microbial indicators.</span></p>

publicAug 2023View details →

Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency

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publicJul 2021View details →

Estimating migration of the cold-tolerant leaf beetle Gonioctena quinquepunctata inside a mountain range in a spatially explicit context

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