Pairwise Dissimilarity Research Articles

Dissimilarity-Preserving Representation Learning for One-Class Time Series Classification.

We propose to embed time series in a latent space where pairwise Euclidean distances (EDs) between samples are equal to pairwise dissimilarities in the original space, for a given dissimilarity measure. To this end, we use auto-encoder (AE) and encoder-only neural networks to learn elastic dissimilarity measures, e.g., dynamic time warping (DTW), that are central to time series classification (Bagnall et al., 2017). The learned representations are used in the context of one-class classification (Mauceri et al., 2020) on the datasets of UCR/UEA archive (Dau et al., 2019). Using a 1-nearest neighbor (1NN) classifier, we show that learned representations allow classification performance that is close to that of raw data, but in a space of substantially lower dimensionality. This implies substantial and compelling savings in terms of computational and storage requirements for nearest neighbor time series classification.

Using joint species distribution modelling to identify climatic and non‐climatic drivers of Afrotropical ungulate distributions

The relative importance of the different processes that determine the distribution of species and the assembly of communities is a key question in ecology. The distribution of any individual species is affected by a wide range of environmental variables as well as through interactions with other species; the resulting distributions determine the pool of species available to form local communities at fine spatial scales. A challenge in community ecology is that these interactions (e.g. competition, facilitation, etc.) often are not directly measurable. Here, we used hierarchical modelling of species communities (HMSC), a recently developed framework for joint species distribution modelling, to estimate the role of biotic effects alongside environmental factors using latent variables. We investigate the role of these factors determining species distributions in communities of Artiodactyla, Perissodactyla and Proboscidea in the Afrotropics, an area of peak species richness for hoofed mammals. We also calculate pairwise trait dissimilarity between these species, from a mixture of morphological and behavioural traits, and investigate the relationship between dissimilarity and estimated residual co‐occurrence in the model. We find that while ungulate distributions appear to be predominantly determined (~ 70%) by climatic variables, such as precipitation, a substantial proportion of the variance in ungulate species distributions (~ 30%) can also be attributed to modelled latent variables that likely represent a combination of dispersal barriers and biotic factors. Although we find only a weak relationship between residual co‐occurrence and trait dissimilarity, we suggest that our results may show evidence that biotic factors, likely influenced by historical barriers to species dispersal, are important in determining species communities over a continental area. The HMSC framework can be used to provide insight into factors affecting community assembly at broad scales, and to make more powerful predictions about future species distributions as we enter an era of increasing impacts from anthropogenic change.

Long-term changes and seasonal variability in the stream macrofauna of a Himalayan river system

Interpreting long-term variability in mountain stream ecosystems is challenging where potential causes such as climate change and altered land-use act simultaneously. The scarcity of historical data also limits research opportunity, especially at low latitudes. Here we assess the macroinvertebrate fauna of 12 Himalayan streams in Nepal covering an altitudinal gradient from 1500 to 3900 m asl using data from 1992, 2022 and 2023. We aimed to: 1) compare long-term change in richness and community composition over three decades to short-term seasonal variation, and 2) analyse long-term changes in relation to catchment properties. Rarefied richness decreased equally with altitude in 1992 and 2022, but was greater at most sites in 2022, with several new families detected. In contrast, no clear seasonal pattern was found. The 2022:1992 ratio in rarefied richness was positively correlated with catchment area and weakly with maximum catchment altitude, while the two highest and glaciated sites gained relatively more taxa than other sites. NMDS ordinations from rarefied Bray-Curtis dissimilarities showed considerable overlap in communities among the three datasets. Pairwise rarefied dissimilarities among all sites increased significantly with altitudinal distance between sites in 1992 while there was no such relationship in 2022. Dissimilarities between 1992 and 2022 samples showed a near-significant correlation with increased catchment vegetation cover as shown by NDVI. Our study is the first to document long-term variations in stream macroinvertebrate communities in Himalayan mountain streams, illustrating how some altitudinal patterns have remained stable through time while others appear to have weakened with links to global change.

Higher‐order dissimilarity in biodiversity: Identifying dissimilarities of spatial or temporal dissimilarity structures

Abstract Elucidating biodiversity patterns and their background processes is critical in biodiversity science. Dissimilarity, which is calculated based on multivariate biological quantities, is a major component of biodiversity. As spatial and temporal biodiversity information availability increases, the scope of dissimilarity studies has been expanded to cover various levels and types of spatiotemporal biodiversity facets (e.g. gene, community and ecosystem function), and diverse pairwise dissimilarity indices have been developed. However, further development of the dissimilarity concept is required in comparative studies on spatiotemporal structures of biodiversity compositional patterns, such as those exploring commonalities of biogeographical boundaries among taxa, compared to the conventional ones to consider higher dimensions of dissimilarity: dissimilarity of dissimilarity structures. This study proposes a novel and general concept, higher‐order dissimilarity (HOD), for quantitatively evaluating the dissimilarities of spatial or temporal dissimilarity structures among different datasets, proposes specific implementations of HOD as operational indices, and illustrates the potential resolution of scientific and practical questions through HOD. We further demonstrate the advantages of the HOD concept by applying it to actual patterns, such as long‐term and/or large‐spatial hypothetical monitoring datasets. Our conceptual framework on HOD extends the existing framework of biodiversity science and is versatile, with many potential applications in acquiring more valuable information from ever‐increasing biodiversity data.

Quantitative Stylistic Analysis of Middle Chinese Texts Based on the Dissimilarity of Evolutive Core Word Usage

Stylistic analysis enables open-ended and exploratory observation of languages. To fill the gap in the quantitative analysis of the stylistic systems of Middle Chinese, we construct lexical features based on the evolutive core word usage and scheme a Bayesian method for feature parameters estimation. The lexical features are from the Swadesh list, each of which has different word forms along with the language evolution during the Middle Ages. We thus count the varied word of those entries along with the language evolution as the linguistic features. With the Bayesian formulation, the feature parameters are estimated to construct a high-dimensional random feature vector to obtain the pair-wise dissimilarity matrix of all the texts based on different distance measures. Finally, we perform the spectral embedding and clustering to visualize, categorize, and analyze the linguistic styles of Middle Chinese texts. The quantitative result agrees with the existing qualitative conclusions and, furthermore, betters our understanding of the linguistic styles of Middle Chinese from both the inter-category and intra-category aspects. It also helps unveil the special styles induced by the indirect language contact.

Plant beta-turnover rather than nestedness shapes overall taxonomic and phylogenetic beta-diversity triggered by favorable spatial-environmental conditions in large-scale Chinese grasslands.

Although it is widely acknowledged that biodiversity maintains plant community assembly processes, exploring the patterns and drivers of beta-diversity (β-diversity; species variation among local plant communities) has received much less attention compared to alpha-diversity (α-diversity; species variation within a local plant community). Here, we aim to examine the patterns and spatial-environmental drivers of taxonomic and phylogenetic β-diversity, and their components such as species turnover and nestedness, in large-scale Leymus chinensis grassland communities. We collected plant community data from 166 sites across widely distributed L. chinensis communities in northern China, and then calculated the taxonomic and phylogenetic β-diversity indices (overall, turnover and nestedness) using a pairwise dissimilarity approach. To assess the effects and to explain the variation in the patterns of β-diversity, we collected data on geospatial, climate and soil conditions. We applied descriptive statistics, Mental correlations, and multiple linear regression models to assess the patterns and spatial-environmental drivers of β-diversity. The β-turnover, as compared to β-nestedness, exhibited a predominant influence, constituting 92.6% of the taxonomic β-diversity and 80.4% of the phylogenetic β-diversity. Most of the spatial-environmental variables were significantly positively correlated with the overall taxonomic and phylogenetic β-diversity and β-turnover, but not with β-nestedness. Climatic factors such as MAP and MAT were the strongest predictors of both taxonomic and phylogenetic β-diversity and β-turnover. The variance partitioning analysis showed that the combined effects of spatial and environmental factors accounted for 19% and 16% of the variation in the taxonomic and phylogenetic β-diversity (overall), 17% and 12% of the variation in the β-turnover, and 7% and 1% of the variation in the β-nestedness, respectively, which were higher than independent effects of either spatial or environmental factors. At larger spatial scales, the turnover component of β-diversity may be associated with the species complementarity effect, but dominant or functionally important species can vary among communities due to the species selection effect. By incorporating β-diversity into grassland management strategies, we can enhance the provision of vital ecosystem services that bolster human welfare, serving as a resilient barrier against the adverse effects of climate change at regional and global scales.

Scale-dependent influences of environmental, historical, and spatial processes on taxonomic and functional beta diversity of Japanese bat assemblages.

This study investigated the relative influences of environmental, spatial, and historical factors, including the island-specific history of land connectivity, on bat assemblages in the Japanese Archipelago. We collected bat distribution data from 1408 studies and assigned them to Japan's First Standard Grid (approximately 6400 km2). Japanese bat assemblages were analyzed at two scales: the entire Japanese Archipelago comprised 16 islands and exclusively the four main islands. At first, we calculated taxonomic and functional total beta diversity (β total) by Jaccard pairwise dissimilarity and then divided this into turnover (β repl) and richness-difference (β rich) components. We conducted hierarchical clustering of taxonomic beta diversity to examine the influence of the two representative sea straits, Tsugaru and Tokara, which are considered biogeographical borders. Variation partitioning was conducted to evaluate the relative effects of the three factors on the beta diversity. Clustering revealed that the Tokara Strait bordered the two major clades; however, the Tsugaru Strait did not act as a biogeographical border for bats. In the variation partitioning, shared fraction between spatial and historical factors significantly explained taxonomic and functional β total and taxonomic β repl at the entire archipelago scale, but not at the four main islands scale extending only Tsugaru Strait but not Tokara Strait. Pure environmental factors significantly explained functional β total at both scales and taxonomic β total only at the four main islands scale. These results suggest that spatial and historical factors are more pronounced in biogeographical borders, primarily structuring assemblage composition at the entire archipelago scale, especially in taxonomic dimension. However, current environmental factors primarily shape the assemblage composition of Japanese bats at the main island scale. The difference in results between the two scales highlights that the primary processes governing assemblages of both dimensions depend on the quality of the dispersal barriers between terrestrial and aquatic barriers for bats.

Asynchrony in terrestrial insect abundance corresponds with species traits.

Asynchrony in population abundance can buffer the effects of environmental change leading to greater community and ecosystem stability. Both environmental (abiotic) drivers and species functional (biotic) traits can influence population dynamics leading to asynchrony. However, empirical evidence linking dissimilarity in species traits to abundance asynchrony is limited, especially for understudied taxa such as insects. To fill this knowledge gap, we explored the relationship between pairwise species trait dissimilarity and asynchrony in interannual abundance change between pairs of species for 422 moth, butterfly, and bumblebee species in Great Britain. We also explored patterns differentiating traits that we assumed to capture 'sensitivity to environmental variables' (such as body mass), and traits that may reflect 'diversity in exposure' to environmental conditions and lead to niche partitioning (for example, habitat uses, and intra-annual emergence periods). As expected, species trait dissimilarity calculated overall and for many individual traits representing response and exposure was positively correlated with asynchrony in all three insect groups. We found that 'exposure' traits, especially those relating to the phenology of species, had the strongest relationship with abundance asynchrony from all tested traits. Positive relationships were not simply due to shared evolutionary history leading to similar life-history strategies: detected effects remained significant for most traits after accounting for phylogenetic relationships within models. Our results provide empirical support that dissimilarity in traits linked to species exposure and sensitivity to the environment could be important for temporal dissimilarity in insect abundance. Hence, we suggest that general trait diversity, but especially diversity in 'exposure' traits, could play a significant role in the resilience of insect communities to short-term environmental perturbations through driving asynchrony between species abundances.

Cortical morphological networks for profiling autism spectrum disorder using tensor component analysis.

Atypical neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) can alter the cortex morphology at different levels: (i) a low-order level where cortical regions are examined individually, (ii) a high-order level where the relationship between two cortical regions is considered, and (iii) a multi-view high-order level where the relationship between regions is examined across multiple brain views. In this study, we propose to use the emerging multi-view cortical morphological network (CMN), which is derived from T1-w magnetic resonance imaging (MRI), to profile autistic and typical brains and pursue new ways of fingerprinting 'cortical morphology' at the intersection of 'network neuroscience'. Each CMN view models the pairwise morphological dissimilarity at the connection level using a specific cortical attribute (e.g., thickness). Specifically, we set out to identify the inherently most representative morphological connectivities shared across different views of the cortex in both autistic and normal control (NC) populations using tensor component analysis. We thus discover the connectional profiles of both populations shared across different CMNs of the left and right hemispheres, respectively. One of the most representative morphological cortical attributes for assessing the abnormal brain structures in patients with ASD is cortical thickness. The most representative morphological connectivities in multi-view CMN population of normal control and ASD subjects, respectively, and in both left and right hemispheres within the temporal, frontal, and insular lobes of individuals with ASD. These representative connectivities are corresponded to specific clinical features observed in individuals with ASD.

Controlling for the effects of environmental availability when testing how the environment determines community compositional uniqueness

Abstract Identifying the drivers that promote unique species compositions (i.e. ecological uniqueness) is crucial to understanding the mechanisms underpinning diversity patterns and for effective conservation planning. Environmental conditions are often sampled differentially in datasets, which can lead to rarer environments having unique species compositions, provided that environmental differences increase compositional differences. This effect, however, will be undesirable when a study aims to test the direct impact of environments rather than their availability. We developed an approach to reduce the effects of environmental availability in ecological uniqueness analyses through calculating expected pairwise compositional dissimilarities for each unique environmental condition. We further used simulations to assess the performance of our methods by randomly generating communities from two hypothetical environments with non‐overlapping species pools. Additionally, we used a dataset of 50 tree communities to demonstrate how environmental availability could impact relationships between environmental conditions and ecological uniqueness in empirical studies. Our simulations revealed that uniqueness metrics based on observed values are sensitive to environmental availability, while our approach correctly concluded that there were no differences among environments under the unbalanced design. Our analysis of tree communities produced divergent conclusions between the two approaches, as increasing slope reduced ecological uniqueness after controlling for their low availability in the dataset only. This suggests that low environmental availability inflated the ecological uniqueness of sites with high slope, which opposed its direct negative effects on ecological uniqueness, leading to a weak relationship based on observed values. To achieve a more mechanistic understanding of ecological uniqueness patterns, the effects of environmental availability must be considered. We recommend that studies use both uncorrected and corrected analyses to identify not only the direct effects of environmental conditions but also the degree to which their availability influences the observed relationships between ecological uniqueness and environment conditions. Our approach should be most necessary and applicable in unbalanced designs, which is a common characteristic in empirical studies.

On the biodiversity of diatom communities in lakes of East China: Geochemical effects dominated after eutrophication

AbstractAimOver the last century, lakes all over the world have experienced significant eutrophication and become more susceptible to critical transitions. This has prompted a growing need to understand how community dynamics shift following ecological perturbations. This study aims to elucidate the present status, spatial patterns and determinants of biological diversity, and how they have changed in response to alterations driven by eutrophication.LocationLakes of East China, mostly in the Yangtze River Basin.TaxaBacillariophyceae (163 species in 33 genres, see taxa names in Appendix S1).MethodsThe environmental conditions of over 60 lakes were assessed based on parameters such as water quality, physical characteristics and biogeochemical constituents. Surface sediment samples and high‐resolution sediment records were collected to quantify the biodiversity of diatom communities, and principal component analysis (PCA) was used to determine the major environmental gradients. Meanwhile, linear regression, canonical correlation analysis and Mantel tests were used to quantify the correlations between variables.ResultsBiodiversity metrics showed no distinct geographic patterns, although areas near large lakes showed comparatively high evenness. Smaller pairwise dissimilarities were observed among hypereutrophic lakes in comparison to lakes with a lower trophic status. The past century has witnessed a decrease in both pairwise dissimilarity and the standard deviation of evenness. A significant statistical association was found between dissimilarity and ionic concentration and composition in the surface sediment of lakes, rather than nutrient levels.Main ConclusionsFollowing regional eutrophication and human disturbance, a significant reduction in biodiversity differentiation was observed in lakes located in East China. Currently, the dominant factor in determining the beta diversity of diatom communities is geochemical conditions rather than nutrient concentrations. Long‐term stress caused by cultural eutrophication may also have altered the dominant determinant of regional biodiversity and diatom community dynamics.

Exploring functional flow heterogeneity in regulated flow regime: Fish species turnover along hydraulic gradients in an artificial waterway network

AbstractHumans have altered river flows leading to a loss of connection with floodplain habitats. The expansion of agriculture in floodplains has resulted in landscapes dominated by irrigated farmland. A key challenge in water management is to conserve existing ecological communities and habitat heterogeneity, while simultaneously maintaining engineered infrastructure for agriculture. In this study, we focused on an artificial channel network for irrigation with a regulated flow regime and its function as habitat for various fish species. Differences in hydraulic conditions among channels and compositional changes in fish species were examined to clarify functional flow heterogeneity. Analyzed using pairwise Simpson dissimilarity among sampling reaches, species turnover was positively associated with Froude number (flow intensity) differences at intermediate discharges, and with differences in cross‐sectional areas (flow magnitude) at low discharges. Drastic changes in inflows should be considered for the effective conservation of flow heterogeneity, even under a regulated flow regime. Improved engineering design to manage the hydraulic environment is one option for maintaining the ecological value of lateral waterbodies in human‐dominated landscapes. Our findings provide insights into the importance of functional flow heterogeneity to conserve fish species diversity.

A new GNSS outlier mitigation method for GNSS/INS integrated system

High-precision positioning with global navigation satellite systems (GNSS) remains a significant challenge in urban environments, due to the outliers caused by the insufficient number of accessible satellites and environmental interference. A GNSS outlier mitigation algorithm with effective fault detection and exclusion (FDE) is required for high-precision positioning. The traditional methods are designed to deal with zero-mean noise in GNSS, which leads to instabilities under biased measurements. Considering that GNSS data are typical time series data, a dynamic FDE scheme is constructed by combining a prediction-model-based method and a dissimilarity-based method. First, a hybrid prediction model which combines autoregressive integrated moving average (ARIMA) model and multilayer perceptron (MLP) model is proposed to provide pseudo-GNSS series by predicting the vehicle’s location for several future steps. Then, a dissimilarity-based method of dynamic time warping measure is utilized to analyze the pairwise dis-similarity between the pseudo-GNSS series and the received GNSS series. The performance of the different models in forecasting is evaluated, and the results show that the positioning accuracy is significantly improved by applying the ARIMA-MLP. The effectiveness of the proposed FDE method is verified through simulation experiments and real experiments based on a typical urban canyon public dataset collected in Tokyo.

Scale dependency in fish beta diversity–hydrology linkages in lowland rivers

AbstractAimA key aspect of biodiversity research is to determine the environmental drivers affecting the degree to which ecological assemblages vary in space (beta diversity). The strength and significance of environmental drivers of beta diversity is, however, influenced by the spatial extent over which beta diversity is assessed. Beta diversity of riverine biota is affected by flow variability. We examined hydrology–beta diversity relationships at two spatial extents (reaches vs. entire systems) within rivers to determine if relationships with hydrological variables are scale dependent or generalisable across spatial scales.LocationMurray–Darling Basin, Australia.TaxonFreshwater fish.MethodsFish assemblage data were sourced from two monitoring programmes that sampled sites annually during 2014–2019 and spanned either reaches (<100 km) or the broader ‘system’ extent (>1000 km) of five tributaries. Beta diversity was examined by calculating pairwise (incidence and abundance) dissimilarities for each year to compare temporal trends in beta diversity. Multi‐site dissimilarities were modelled against hydrological variables using beta regression.ResultsInter‐annual change in assemblage composition was detected only at the extent of river reaches but not at the extent of river systems. Temporal variation in within‐river beta diversity showed inconsistent patterns when compared between the two spatial extents. Within‐river beta diversity relationships with hydrological gradients were inconsistent among rivers. Overall, statistical models explained much more variation in within‐river beta diversity when assessed at the reach extent when compared to broader river system extents.Main ConclusionsOur findings highlight that changes in within‐river beta diversity are likely to depend on the spatial extent of sampling. Furthermore, inconsistent beta diversity–hydrology relationships among rivers suggest that both empirical evidence and theoretical predictions adopted in ecohydrology may not be transferable among river systems.

Beta diversity dynamics in East Asian angiosperm woody plants: taxonomic turnover in relation to temperature gradients during the Cenozoic

Information on the paleo-beta diversity of fossil assemblages and its patterning in different geological time intervals helps us to better understand the community-level response of biodiversity patterns to current global warming. We focused on the impact of paleoclimate changes on large-scale taxonomic sorting related to geography; specifically, how cooler and warmer climatic conditions affect the distance-dependency of beta diversity. Using a dataset of Cenozoic fossil assemblages of angiosperm woody plants (7,468 data points; 310 genera in 95 families) in the East Asian archipelago, we modeled the distance-dependency of genus turnover (Sørensen’s pairwise dissimilarity) through the Oligocene, Miocene, Pliocene, Pleistocene, Last Glacial Period, Holocene, and the present day. The genus turnover of angiosperm woody plants during the Oligocene to Holocene interval was positively correlated with geographical and climatic distance, but was significant only after the Last Glacial Period to the present day. During the warm Tertiary period, genus turnover was mostly independent of geographical distance. Spatial/climatic distance-dependent turnover under colder environments involved a climate-induced sorting process to spatially diversify woody-plant assemblages across the archipelago. Moreover, the predominance of distant-independent turnover suggested the effect of dispersal release under warmer, stable climates. Our findings suggest that future tropicalization in temperate habitats could promote geographical homogenization of biodiversity patterns.

The Role of Infant Health Problems in Constraining Interneighborhood Mobility: Implications for Citywide Employment Networks.

Infant health problems are a persistent concern across the United States, disproportionally affecting socioeconomically vulnerable communities. We investigate how inequalities in infant health contribute to differences in interneighborhood commuting mobility and shape neighborhoods' embeddedness in the citywide structure of employment networks in Chicago over a 14-year period. We use the Census Bureau's Longitudinal Employer-Household Dynamics' Origin-Destination Employment Statistics to analyze commuting networks between 2002 and 2015. Results from longitudinal network analyses indicate two main patterns. First, after the Great Recession, a community's infant health problems began to significantly predict isolation from the citywide employment network. Second, pairwise dissimilarity in infant health problems predicts a lower likelihood of mobility ties between communities throughout the entire study period. The findings suggest that infant health problems present a fundamental barrier for communities in equally accessing the full range of jobs and opportunities across the city-compounding existing inequalities.

Clustering multivariate time series using energy distance

A novel methodology is proposed for clustering multivariate time series data using energy distance defined in Székely and Rizzo (2013). Specifically, a dissimilarity matrix is formed using the energy distance statistic to measure the separation between the finite‐dimensional distributions for the component time series. Once the pairwise dissimilarity matrix is calculated, a hierarchical clustering method is then applied to obtain the dendrogram. This procedure is completely nonparametric as the dissimilarities between stationary distributions are directly calculated without making any model assumptions. In order to justify this procedure, asymptotic properties of the energy distance estimates are derived for general stationary and ergodic time series. The method is illustrated in a simulation study for various component time series that are either linear or nonlinear. Finally, the methodology is applied to two examples; one involves the GDP of selected countries and the other is the population size of various states in the U.S.A. in the years 1900–1999.

Assessing Genetic Distinctness and Redundancy of Plant Germplasm Conserved Ex Situ Based on Published Genomic SNP Data

Assessing genetic distinctness and redundancy is an important part of plant germplasm characterization. Over the last decade, such assessment has become more feasible and informative, thanks to the advances in genomic analysis. An attempt was made here to search for genebank germplasm with published genomic data and to assess their genetic distinctness and redundancy based on average pairwise dissimilarity (APD). The effort acquired 12 published genomic data sets from CIMMYT, IPK, USDA-ARS, IRRI, and ICRISAT genebanks. The characterized collections consisted of 661 to 55,879 accessions with up to 2.4 million genome-wide SNPs. The assessment generated an APD estimate for each sample. As a higher or lower APD is indicative of more genetic distinctness or redundance for an accession, respectively, these APD estimates helped to identify the most genetically distinct and redundant groups of 100 accessions each and a genetic outlier group with APD estimates larger than five standard deviations in each data set. An APD-based grouping of the conserved germplasm in each data set revealed among-group variances ranging from 1.5 to 53.4% across all data sets. Additional analyses showed that these APD estimations were more sensitive to SNP number, minor allele frequency, and missing data. Generally, 5000 to 10,000 genome-wide SNPs were required for an effective APD analysis. These findings together are encouraging and useful for germplasm management, utilization, and conservation, particularly in the genetic categorization of conserved germplasm.

Diversity of benthic diatoms in the Baltic Sea: alpha and beta diversity, environmental drivers, and diversity-biomass relationships

Benthic diatoms are crucial for the functioning of ecosystems, but their diversity patterns along large gradients are poorly studied. By using 3 self-collected data sets along large environmental gradients in the Baltic Sea, represented over spatial scales of 60, 1300, and 2300 km, I investigated whether different aspects of diversity follow general patterns or are context- and region-specific. General diversity patterns along different gradients would likely indicate high resilience of benthic diatoms against differences and changes in the environment, whereas context-dependent patterns would possibly suggest that environmental change is likely to modify diatom communities and that region-specific differences should be considered when designing ecosystem management. I investigated the effect of environmental conditions on taxonomic and functional diatom diversity with distance-based redundancy analyses, variability of taxonomic diversity with species accumulation curves, taxonomic and functional aspects of spatial beta diversity with pairwise Bray-Curtis dissimilarity indices and Mantel tests, and diversity-biomass relationships with generalized linear models. The effect of environment on diatom communities was context-dependent, and different factors controlled communities along different gradients. Diversity varied along gradients and correlated with salinity in a U-shaped way. Beta diversity followed a general pattern of high taxonomic but low functional beta diversity along all gradients. Relationships between diatom diversity and ecosystem biomass were weak along all gradients. These results suggest that although the regional diversity of diatoms seems resilient, environmental change is likely to modify the local diversity of diatom communities. Finding out how these changes will affect ecosystem functioning requires further investigation.

On the Performance of Bayesian Generalized Dissimilarity Model Estimator

The Generalized Dissimilarity Model (GDM) is an extension of Generalized Linear Model (GLM) that is used to describe and estimate biological pairwise dissimilarities following a binomial process in response to environmental gradients. Some improvement has been made to accommodate the uncertainty quantity of GDM by applying resampling scheme such as Bayesian Bootstrap (BBGDM). Because there is an ecological assumption in the GDM, it is reasonable to use a proper Bayesian approach rather than resampling method to obtain better modelling and inference results. Similar to other GLM techniques, the GDM also employs a link function, such as the logit link function that is commonly used for the binomial regression model. By using this link, a Bayesian approach to GDM framework which called Bayesian GDM (BGDM) can be constructed. In this paper, we aim to evaluate the estimators' performance of Bayesian Generalized Dissimilarity Model (BGDM) in relative to BBGDM. Our study revealed that the performance of BGDM estimator outperformed that of BBGDM, especially in term of unbiasedness and efficiency. However, the BGDM estimators failed to meet consistency property. Moreover, the application of the BGDM to a real case study indicates that its inferential abilities are superior to the preceding model.