Multidimensional Scaling Model Research Articles

Spatio-temporal patterns and predictions of size-fractionated chlorophyll a in a large subtropical river, China

Spatio-temporal patterns in chlorophyll a (Chl-a) from size-fractionated phytoplankton were examined in the Pearl River (PR), China, during 2015 and 2016. The concentration of total Chl-a was a good indicator of spatial patterns, since it increased along a nutrient gradient. A nonmetric multidimensional scaling (NMDS) model showed clearly a spatial pattern in the distribution of size-fractionated Chl-a, dividing the study area into three groups of sampling sites. The three groups represented sites at the West River (G1), the central Pearl River Delta (G2) and the Guangzhou City center (G3). Temporal changes in physicochemical factors among the three groups were not obvious. And the Linear Discriminant Analysis (LDA) model showed G1 and G2 were mostly explained by physical factors, G3 was closely associated with chemical factors. The potential of using size-fractionated Chl-a data as an indicator of water quality was compared using two other size-based methods; the morphological traits of the algae Aulacoseira granulata and using functional groups (FGs) combined with trait-based (algae volume) classifications of benthic diatoms. Our study indicated that size-based methods of phytoplankton research could make a useful contribution to determine spatio-temporal patterns in the studied area, providing greater insight into phytoplankton dynamics and enabling better managements of water quality.

Ash Dieback and Its Impact in Near-Natural Forest Remnants - A Plant Community-Based Inventory.

Temperate European forests are currently largely under attack by the infection with Hymenoscyphus fraxineus, a fungal pathogen introduced from Asia since at least the early 1990s and causing a major dieback of common ash (Fraxinus excelsior) throughout Europe. At present, ash dieback evokes major problems for forestry, in particular in sensitive forest remnants in Northern Germany, where the disease causes serious concerns for ecosystem conservation. This makes ash dieback a focal area of ecological research. In the present study, we quantified the extent of ash dieback in adult and in young ash trees in Northern Schleswig-Holstein, Germany, in relation to community composition and associated biotic and abiotic factors. Data collection was carried out in 37 plots in communities of ash-rich forests and included floristic inventory, rating of adult and young ash individuals and recording of light and soil conditions. Data were analyzed using non-metric multidimensional scaling and general linear mixed effects models. Forest type was the strongest significant predictor for variation in crown defoliation of adult ash trees. Damage was highest in communities of wet alder-ash forests and lowest in ash-rich beech forests. A further significant predictor of adult crown defoliation was individual height of the ash tree with larger trees being less affected than smaller ones. For juveniles, total species richness displayed a significant positive relationship with the proportional abundance of fungal infection, while the mean damage proportion per individual significantly increased with increasing relative light intensity in the understorey. The study clearly shows a strong relationship between forest type and ecosystem vulnerability to ash dieback. In particular, communities belonging to the species-rich wet alder-ash forests were most severely affected by ash disease, thereby deserving special attention among the vulnerable fragmented forest remnants in Schleswig-Holstein. Co-varying factors, however, seem to differ between juvenile and adult trees, hinting at the relative importance of tree performance for the adult trees and abiotic conditions for the juveniles. Accounting for such differences along a larger ecological gradient of ash forest communities will be necessary to more comprehensively understand effects of ash dieback on the ecosystem and needs to be addressed in future research.

Contrasting distribution and foraging patterns of herbivorous and detritivorous fishes across multiple habitats in a tropical seascape

Understanding drivers behind patterns of functionally important groups of fishes is crucial for successful management and conservation of tropical seascapes. Herbivorous fishes are the most prominent consumers of marine primary production which can have profound effects on reef resilience. We explored environmental variables affecting distribution and foraging patterns of herbivorous and detritivorous fish assemblages (siganids, acanthurids and parrotfish) across distinct shallow-water habitats (coral reefs, macroalgae beds and seagrass meadows) during September–November 2016 at Mafia Island, Tanzania (8°00′S, 39°41′E). We performed underwater visual census to quantify fish assemblages, measured habitat features, deployed macroalgal assays and conducted inventories of grazing scars. Multi-dimensional scaling and mixed-effects linear models were used to evaluate differences in fish assemblages and environmental variables influencing abundance and foraging patterns of fishes. Fish communities of focal functional groups differed among habitats. Abundance of herbivores and detritivores as well as relative browsing and scraping was highest on coral reefs compared to macroalgae and seagrass meadows. Adult fish were more abundant on coral reefs while juveniles were abundant in macroalgal beds. Coral cover and crustose coralline algal cover had a positive effect on the abundance of fish in coral reef areas, while macroalgal cover had a negative effect. Contrastingly, in macroalgae habitats, macroalgal cover had a positive effect on the abundance of parrotfish. These results highlight the importance of considering connectivity between macroalgal beds and coral reefs through ontogenetic shifts in habitat use by primarily microphagous parrotfish and of incorporating a range of habitats within coastal management plans.

Biochar amendment alters the relation between the Pb distribution and biological activities in soil

In the present investigation, the impact of biochar amendments on the Pb fractionation pattern and soil enzymatic activities in soil was evaluated. Two spiking concentrations of exogenous Pb, two application rates (2% and 4%) of biochar and three plants such as Withania somnifera, Andrographis paniculata and Bacopa monnieri were taken for the study. Three experiment sets were designed for each plant. Distribution of Pb (in acid soluble, reducible, oxidizable and residual fractions), physicochemical and biological properties (β-glucosidase, acidic and alkaline phosphatases, urease and microbial biomass) of soil were examined. Several chemometric techniques were applied to this huge data to evaluate the association of soil microbial activities with Pb fractionation. The results revealed that biochar amendments altered the fractionation of Pb by shifting from mobile fraction (acid soluble) to immobile fraction (oxidizable and residual). The correlation analysis suggested that this could be attributed to the increase in cation exchange capacity, organic carbon and available phosphorus content in the soil after biochar amendments. The results clearly demonstrated that biochar amendments in Pb-contaminated soil improved the enzymatic activities in the soil. The multidimensional scaling, correlation and sequential equation modeling imply that biochar has a shielding effect on soil microbial activity against Pb stress from each fraction of soil.

Examining item content validity using property fitting analysis via multidimensional scaling.

Multiple-item measuring instruments are frequently used in a wide range of disciplines for the purpose of research in substantive areas. The quality of items in these instruments determine to a large extent whether the results are trustworthy. In this paper, we suggested to use property fitting analysis to evaluate the appropriateness of items content validity based on explicit item property criteria. Using Center for Epidemiologic Studies Depression scale as an example, item property fitting analyses via multidimensional scaling model was used to quantitatively evaluate the properties of items based on rating data from 12 counselors. The results of the analyses indicated that using explicit item property criteria to select items for subsequent psychometric analyses improved the item quality in terms of reliability and factor structure. Item property fitting analysis seemed to provide the researcher a viable quantitative method when evaluating item content validity.

Immunomodulatory Effects of Stress and Environmental Enrichment in Long-Evans Rats (Rattus norvegicus).

Stress can influence the secretion of neuroendocrine mediators, thereby exposing immune cells to altered signaling and interactions. Here we investigated the synergetic effect of stress and environmental enrichment on the immune response of Long-Evans rats. Subjects (n = 46) were assigned to 5 treatment groups: acute compared with chronic stress with or without environmental enrichment, plus an unmanipulated control group. Animals also were classified as active, passive, and flexible copers according to back-test assessment. Rats were exposed to enrichment in an open-field containing objects in different areas for 30 min 3 times each week, thus modeling the effects of a temporary increase in environmental stimuli. Animals assigned to chronic stress groups were exposed to predator sound stressors for 30 min daily, whereas animals assigned to acute stress groups were exposed once each week. After 7 wk, a dermal punch biopsy was administered to activate the immune response, after which rats were challenged through a forced swim test. Biologic samples were collected to measure corticosterone, dehydroepiandrosterone (DHEA), oxytocin, testosterone, and the cytokines IL6 and IL10. Rats exposed to chronic stress had lower DHEA:corticosterone ratios, suggesting increased allostatic load. Enrichment exposure modulated these effects, lowering overall corticosterone and testosterone levels and increasing DHEA and oxytocin levels in animals exposed to the predator sound. The immune response was decreased in rats exposed to chronic stress, but the effect of environmental enrichment helped to mitigate the negative influence on cells producing IL6. Combining acute stress and exposure to an enriched environment returned a healthier profile in terms of both immune activation and stress regulation. By using a multidimensional scaling model, we found that a combination of 'good' stress and exposure to brief sessions of enriching stimuli can reliably predict health in Long-Evans rats.

Low‐resolution face recognition and feature selection based on multidimensional scaling joint L 2,1 ‐norm regularisation

Face recognition is confronted with situations wherein the captured face images are not as clear as the registered ones; this is known as low-resolution face recognition. To solve this problem, the authors propose a new sparse coupled projection method using multidimensional scaling joint L 2,1 -norm regularisation (MDSL21). The MDSL21 maps the low-resolution faces and high-resolution faces into a common sparse subspace in which feature selection and coupled transformation can be simultaneously achieved. In their proposed method, the authors first learn the common responds using the multidimensional scaling model. Specifically, the distance between the responds is approximated to the distance between the high-resolution samples, and the local manifolds are preserved. Then, the seeking coupled projections are formulated as a regression model. Inspired by the sparse constraint utilised in the classical subspace learning methods, the authors add an L 2,1 -norm regularisation term to the regression model to realise the sparsity and present its optimisation method. Experimental results validate the effectiveness of their proposed method on the low-resolution face recognition task.

Efficient Inter-Geodesic Distance Computation and Fast Classical Scaling.

Multidimensional scaling (MDS) is a dimensionality reduction tool used for information analysis, data visualization and manifold learning. Most MDS procedures embed data points in low-dimensional euclidean (flat) domains, such that distances between the points are as close as possible to given inter-point dissimilarities. We present an efficient solver for classical scaling, a specific MDS model, by extrapolating the information provided by distances measured from a subset of the points to the remainder. The computational and space complexities of the new MDS methods are thereby reduced from quadratic to quasi-linear in the number of data points. Incorporating both local and global information about the data allows us to construct a low-rank approximation of the inter-geodesic distances between the data points. As a by-product, the proposed method allows for efficient computation of geodesic distances.

Environmental controls on the abundance of methanotrophs and methanogens in peat bog lakes

The aim of the present study was to identify the factors that influence the composition of methanogens and methanotrophs in the background prokaryotic community in peat bog lakes. We hypothesized that the microbial composition is a function of the physicochemical conditions of the water and a function of depth-dependent oxygen (DO) concentrations. To address this aim, we collected water samples from subsurface and near-bottom layers, representing oxic and anoxic conditions in 4 peat bog lakes in NE Poland. The structure of methanogenic Archaea and methane-oxidizing bacteria (MOB) was determined with double labeled-fluorescence in situ hybridization (DOPE-FISH).The results showed significant differences in Procaryota communities between the oxic (subsurface) and suboxic/anoxic (near-bottom) layers in peat bog lakes (t-test, p < 0.05). The methanogens from the Archaea domain were observed in anoxic periods, while methanotrophs were present regardless of water depth and season. The abundance of methanogens was inversely correlated with DO and CO2. Methanotrophs adapted better to the changing habitat conditions. The nonmetrical multidimensional scaling (NMS) and partial least square regression (PLS-R) models showed that the methanotrophs in subsurface layers are positively associated with temperature, DOC, and TON while negatively associated with pH. The DO availability is not a prerequisite condition for the presence of methanothrophs. The most important factors for MOB at the bottom were CO2 and TON. Due to a significant role of methanotrophs in the control of the methane emission flux rates, there is a need for further research on factors responsible for methanotroph development in peat bog lakes.

Arbuscular mycorrhizal fungal community structure and diversity are affected by host plant species and soil depth in the Mu Us Desert, northwest China

ABSTRACTThe vertical diversity and distribution of arbuscular mycorrhizal (AM) fungi were investigated in the Mu Us Desert, northwest China. Soils were sampled to 50 cm in depth in the rhizospheres of Hedysarum laeve, Artemisia ordosica, and Psammochloa villosa and 44 AM fungal species belonging to 10 genera were isolated. Several of these species have peculiar morphological features, which are distinct from other habitats. AM fungal diversity and distribution differed significantly among the three host plants and the five soil layers. Spore density, species richness, and the Shannon-Wiener index of AM fungi were 0.55–4.3 spores g−1 soil, 7–36 and 1.78–2.89, respectively. Spore density and species richness had a significant positive correlation with soil total phosphorus content (0.0377–0.1129 mg g−1), and a negative correlation with soil pH (7.19–7.64). Nonmetric multidimensional scaling, PerMANOVA, and structural equation model analysis demonstrated that host plant species and soil depth significantly and directly influenced the structure of AM fungal communities. We concluded that diversity and distribution of AM fungi might be influenced by plant species, soil depth patterns, and soil nutrient availability in desert ecosystems. This research into AM fungal communities may lead to the development of AM fungi treatment for the mitigation of soil erosion and desertification using mycorrhizal plants, such as H. laeve, A. ordosica, and P. villosa.

Psychometric properties of the Resilience Scale for Adults (RSA) and its relationship with life-stress, anxiety and depression in a Hispanic Latin-American community sample.

Resilience is a multi-dimensional construct associated with health and well-being. At present, we do not yet have a valid, scientific instrument that is designed to evaluate adult resilience in Spanish-speaking countries and that accounts for family, social and individual components. This study aimed at investigating the construct and cross-cultural validity of the Resilience Scale for Adults (RSA) by combining Confirmatory Factor Analysis (CFA), Multidimensional Scaling (MDS) and Hierarchical Regression models in a Hispanic Latin-American group. A community sample of 805 adults answered the RSA, Spanish Language Stressful Life-Events checklist (SL-SLE), and the Hopkins Symptom Checklist-25 (HSCL-25). First-order CFA verified the six factors structure for the RSA (RMSEA = .037, SRMR = .047, CFI = .91, TLI = .90). Five RSA scales and total score have good internal consistency (scales α > .70; total score α = .90). Two second-order CFA verified the intrapersonal and interpersonal dimensions of the protector factors of resilience, as well as their commonality and uniqueness with affective symptoms (anxiety and depression). An exploratory MDS reproduced the relations of RSA items and factors at first and second-order levels against random simulated data, thereby providing initial evidence of its cross-cultural validity in a Spanish-speaking group. The Four-steps hierarchical model showed that the RSA scales are the strongest predictors of anxiety and depression–greater than gender, age, education and stressful life-events. Three RSA scales are significant unique predictors of affective symptoms. In addition, similar to findings in diverse cultural settings, resilience is positively associated with age but not with education. Women report higher scores of Social Resources and Social Competence and lower scores of Perception of the Self. In conclusion, this study demonstrates the construct and criterion-related validity of the RSA in broad, diverse and Spanish speaking sample.

Diverse Management Strategies Produce Similar Ecological Outcomes on Ranches in Western Great Plains: Social-Ecological Assessment

Experiments investigating grazing systems have often excluded ranch-scale decision making, which has limited our understanding of the processes and consequences of adaptive management. We conducted interviews and vegetation monitoring on 17 ranches in eastern Colorado and eastern Wyoming to investigate rancher decision-making processes and the associated ecological consequences. Management variables investigated were grazing strategy, grazing intensity, planning style, and operation type. Ecological attributes included the relative abundance of plant functional groups and categories of ground cover. We examined the environmental and management correlates of plant species and functional group composition using nonmetric multidimensional scaling and linear mixed models. After accounting for environmental variation across the study region, species composition did not differ between grazing management strategy and planning style. Operation type was significantly correlated with plant community composition. Integrated cow-calf plus yearling operations had greater annual and less key perennial cool-season grass species cover relative to cow-calf−only operations. Integrated cow-calf plus yearling ranches were able to more rapidly restock following drought compared with cow-calf operations. Differences in types of livestock operations contributed to variability in plant species composition across the landscape that may support diverse native faunal species in these rangeland ecosystems. Three broad themes emerged from the interviews: 1) long-term goals, 2) flexibility, and 3) adaptive learning. Stocking-rate decisions appear to be slow, path-dependent choices that are shaped by broader social, economic, and political dynamics. Ranchers described having greater flexibility in altering grazing strategies than ranch-level, long-term, annual stocking rates. These results reflect the complexity of the social-ecological systems ranchers navigate in their adaptive decision-making processes. Ranch decision-making process diversity within these environments precludes development of a single “best” strategy to manage livestock grazing.

Selecting the optimal multidimensional scaling procedure for metric data with R environment

In multidimensional scaling (MDS) carried out on the basis of a metric data matrix (interval, ratio), the main decision problems relate to the selection of the method of normalization of the values of the variables, the selection of distance measure and the selection of MDS model. The article proposes a solution that allows choosing the optimal multidimensional scaling procedure according to the normalization methods, distance measures and MDS model applied. The study includes 18 normalization methods, 5 distance measures and 3 types of MDS models (ratio, interval and spline). It uses two criteria for selecting the optimal multidimensional scaling procedure: Kruskal’s Stress-1 fit measure and Hirschman-Herfindahl HHI index calculated based on Stress per point values. The results are illustrated by an empirical example.

Selecting the Optimal Multidimensional Scaling Procedure for Metric Data With R Environment

Abstract In multidimensional scaling (MDS) carried out on the basis of a metric data matrix (interval, ratio), the main decision problems relate to the selection of the method of normalization of the values of the variables, the selection of distance measure and the selection of MDS model. The article proposes a solution that allows choosing the optimal multidimensional scaling procedure according to the normalization methods, distance measures and MDS model applied. The study includes 18 normalization methods, 5 distance measures and 3 types of MDS models (ratio, interval and spline). It uses two criteria for selecting the optimal multidimensional scaling procedure: Kruskal’s Stress-1 fit measure and Hirschman-Herfindahl HHI index calculated based on Stress per point values. The results are illustrated by an empirical example.

Post-processing of Markov chain Monte Carlo output in Bayesian latent variable models with application to multidimensional scaling

In Bayesian analysis of multidimensional scaling model with MCMC algorithm, we encounter the indeterminacy of rotation, reflection and translation of the parameter matrix of interest. This type of indeterminacy may be seen in other multivariate latent variable models as well. In this paper, we propose to address this indeterminacy problem with a novel, offline post-processing method that is easily implemented using easy-to-use Markov chain Monte Carlo (MCMC) software. Specifically, we propose a post-processing method based on the generalized extended Procrustes analysis to address this problem. The proposed method is compared with four existing methods to deal with indeterminacy thorough analyses of artificial as well as real datasets. The proposed method achieved at least as good a performance as the best existing method. The benefit of the offline processing approach in the era of easy-to-use MCMC software is discussed.

Effect of freshwater mussels on the vertical distribution of anaerobic ammonia oxidizers and other nitrogen-transforming microorganisms in upper Mississippi river sediment.

Targeted qPCR and non-targeted amplicon sequencing of 16S rRNA genes within sediment layers identified the anaerobic ammonium oxidation (anammox) niche and characterized microbial community changes attributable to freshwater mussels. Anammox bacteria were normally distributed (Shapiro-Wilk normality test, W-statistic =0.954, p = 0.773) between 1 and 15 cm depth and were increased by a factor of 2.2 (p < 0.001) at 3 cm below the water-sediment interface when mussels were present. Amplicon sequencing of sediment at depths relevant to mussel burrowing (3 and 5 cm) showed that mussel presence reduced observed species richness (p = 0.005), Chao1 diversity (p = 0.005), and Shannon diversity (p < 0.001), with more pronounced decreases at 5 cm depth. A non-metric, multidimensional scaling model showed that intersample microbial species diversity varied as a function of mussel presence, indicating that sediment below mussels harbored distinct microbial communities. Mussel presence corresponded with a 4-fold decrease in a majority of operational taxonomic units (OTUs) classified in the phyla Gemmatimonadetes, Actinobacteria, Acidobacteria, Plantomycetes, Chloroflexi, Firmicutes, Crenarcheota, and Verrucomicrobia. 38 OTUs in the phylum Nitrospirae were differentially abundant (p < 0.001) with mussels, resulting in an overall increase from 25% to 35%. Nitrogen (N)-cycle OTUs significantly impacted by mussels belonged to anammmox genus Candidatus Brocadia, ammonium oxidizing bacteria family Nitrosomonadaceae, ammonium oxidizing archaea genus Candidatus Nitrososphaera, nitrite oxidizing bacteria in genus Nitrospira, and nitrate- and nitrite-dependent anaerobic methane oxidizing organisms in the archaeal family “ANME-2d” and bacterial phylum “NC10”, respectively. Nitrosomonadaceae (0.9-fold (p < 0.001)) increased with mussels, while NC10 (2.1-fold (p < 0.001)), ANME-2d (1.8-fold (p < 0.001)), and Candidatus Nitrososphaera (1.5-fold (p < 0.001)) decreased with mussels. Co-occurrence of 2-fold increases in Candidatus Brocadia and Nitrospira in shallow sediments suggests that mussels may enhance microbial niches at the interface of oxic–anoxic conditions, presumably through biodeposition and burrowing. Furthermore, it is likely that the niches of Candidatus Nitrososphaera and nitrite- and nitrate-dependent anaerobic methane oxidizers were suppressed by mussel biodeposition and sediment aeration, as these phylotypes require low ammonium concentrations and anoxic conditions, respectively. As far as we know, this is the first study to characterize freshwater mussel impacts on microbial diversity and the vertical distribution of N-cycle microorganisms in upper Mississippi river sediment. These findings advance our understanding of ecosystem services provided by mussels and their impact on aquatic biogeochemical N-cycling.

A new bayesian spatial model for brand positioning

PurposeJoint space multidimensional scaling (MDS) maps are often utilized for positioning analyses and are estimated with survey data of consumer preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the competitive landscape. However, little attention has been given to the possibility that consumers may display heterogeneity in their information usage (Bettman et al., 1998) and the possible impact this may have on the corresponding estimated joint space maps. This paper aims to address this important issue and proposes a new Bayesian multidimensional unfolding model for the analysis of two or three-way dominance (e.g. preference) data. The authors’ new MDS model explicitly accommodates dimension selection and preference heterogeneity simultaneously in a unified framework.Design/methodology/approachThis manuscript introduces a new Bayesian hierarchical spatial MDS model with accompanying Markov chain Monte Carlo algorithm for estimation that explicitly places constraints on a set of scale parameters in such a way as to model a consumer using or not using each latent dimension in forming his/her preferences while at the same time permitting consumers to differentially weigh each utilized latent dimension. In this manner, both preference heterogeneity and dimensionality selection heterogeneity are modeled simultaneously.FindingsThe superiority of this model over existing spatial models is demonstrated in both the case of simulated data, where the structure of the data is known in advance, as well as in an empirical application/illustration relating to the positioning of digital cameras. In the empirical application/illustration, the policy implications of accounting for the presence of dimensionality selection heterogeneity is shown to be derived from the Bayesian spatial analyses conducted. The results demonstrate that a model that incorporates dimensionality selection heterogeneity outperforms models that cannot recognize that consumers may be selective in the product information that they choose to process. Such results also show that a marketing manager may encounter biased parameter estimates and distorted market structures if he/she ignores such dimensionality selection heterogeneity.Research limitations/implicationsThe proposed Bayesian spatial model provides information regarding how individual consumers utilize each dimension and how the relationship with behavioral variables can help marketers understand the underlying reasons for selective dimensional usage. Further, the proposed approach helps a marketing manager to identify major dimension(s) that could maximize the effect of a change of brand positioning, and thus identify potential opportunities/threats that existing MDS methods cannot provides.Originality/valueTo date, no existent spatial model utilized for brand positioning can accommodate the various forms of heterogeneity exhibited by real consumers mentioned above. The end result can be very inaccurate and biased portrayals of competitive market structure whose strategy implications may be wrong and non-optimal. Given the role of such spatial models in the classical segmentation-targeting-positioning paradigm which forms the basis of all marketing strategy, the value of such research can be dramatic in many marketing applications, as illustrated in the manuscript via analyses of both synthetic and actual data.

Analysis of additional hotel services in the international luxury hotels – a case-study from Budapest

AbstractThe investigation of additional services from the aspect of local embeddedness is a novelty in the academic literature related to the tourism and hotel industry. The primary function of hotels is to provide accommodation and other services for the hotel-guests. Secondarily, they may also offer complementary-services and a community space for the city-residents and for non-hotel guests. Due to the globalization, the change in the consumer behaviour and global firms, the question of location and local resources are becoming more and more significant especially in the case of international hotel chains. The international hotel company is a member of a hotel market at a specific location, and it is surrounded by a sociological environment, local people, culture and traditions which have an impact on the competitiveness of the hotel. The author explains the results with the application of the multidimensional scaling model, finding answers for the questions in which ways the local embeddedness can have an effect on the competitiveness of a hotel based on a case-study carried out in a five-star hotel (member of an international chain) of Budapest in 2016.

Conserving reptiles within a multiple-use landscape: determining habitat affiliations of reptile communities in the northern jarrah forest of south-western Australia

Disturbed landscapes can provide habitat for a variety of species; however, for fauna, a strong understanding of their habitat affiliations is critical both to detect species and to develop management prescriptions to maintain their populations. We assessed habitat affiliations of common, uncommon and rare reptile species in a multiple-use landscape, the northern jarrah forest of south-western Australia. To identify predictors of reptile occurrence, we related reptile presence/absence, or relative abundance, to habitat, climatic and seasonal variables. Because the reptiles studied have cryptic behaviours and low numbers of detections, we used a combination of analyses including non-metric multi-dimensional scaling, occupancy and regression models. We identified specific habitat affiliations for the most common species and potential linkages with vegetation structure for most uncommon species. There were insufficient detections to determine habitat affiliations accurately for most rare species. Often species were detected too infrequently to determine specific habitat variables that influence occupancy and detection, and altering survey time and scale may increase detections so that habitat affiliations can be determined. However, in highly speciose landscapes, like our study area, we may not be able to wait until we have enough detections to define the habitat affiliations of all reptiles before we make management decisions. Therefore management activities that maintain habitat heterogeneity and complexity is likely to be the best strategy to conserve the most reptile species.

Effect of Glacial Retreat on Floral Distribution and/or Displacement in Khersan Glacier, Central Alborz Mountain range, Iran

During past few decades, worldwide various ecological alterations have beenexperienced after treatand decreasing of glaciers. Notable changes have been traced in Khersan glacier, Central Alborz of Iran by monitoring since 2013 to 2015. According to our studies, Khersan glacier surface reduced since 1991 and this signif icant reduction led to manyecological alterations. Specieseliminationclose to the glacier, displacement of various flora from sub-Alpine to Alpine and Nival area including changes in floral frequency are notable alterations taken during glacier retreat. A large number of studies in Khersan glacier area since last two centuries have evidenced complete elimination of 6 plant species. Displacement of 16 plant species during recent years revealed that such species after retreat either found a new location for the establishment or got eliminated. Besides natural changes, the glacierareawasalsoaffected by man-made developments. Perhaps new condition puts many plant species in conservation level which need proper care programs. In this study multidimensional scaling model (MDS) is used to show the Nival areas where species are under muchstress. Properevidence has been tried toput forward fordescribing suchchanges. Abstract