scholarly journals How interactions between animal movement and landscape processes modify local range dynamics and extinction risk

2014 ◽  
Vol 10 (5) ◽  
pp. 20140198 ◽  
Author(s):  
Damien A. Fordham ◽  
Kevin T. Shoemaker ◽  
Nathan H. Schumaker ◽  
H. Reşit Akçakaya ◽  
Nathan Clisby ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Landscape Structure ◽  
Animal Movement ◽  
Extinction Risk ◽  
Species Distributions ◽  
Turtle Species ◽  
Novel Approach ◽  
Range Dynamics ◽  
The Individual ◽  
Local Range

Forecasts of range dynamics now incorporate many of the mechanisms and interactions that drive species distributions. However, connectivity continues to be simulated using overly simple distance-based dispersal models with little consideration of how the individual behaviour of dispersing organisms interacts with landscape structure (functional connectivity). Here, we link an individual-based model to a niche-population model to test the implications of this omission. We apply this novel approach to a turtle species inhabiting wetlands which are patchily distributed across a tropical savannah, and whose persistence is threatened by two important synergistic drivers of global change: predation by invasive species and overexploitation. We show that projections of local range dynamics in this study system change substantially when functional connectivity is modelled explicitly. Accounting for functional connectivity in model simulations causes the estimate of extinction risk to increase, and predictions of range contraction to slow. We conclude that models of range dynamics that simulate functional connectivity can reduce an important source of bias in predictions of shifts in species distributions and abundances, especially for organisms whose dispersal behaviours are strongly affected by landscape structure.

scholarly journals Critical threshold effects of benthiscape structure on stream herbivore movement

2007 ◽  
Vol 362 (1479) ◽  
pp. 461-472 ◽  
Author(s):  
Julian D Olden
Keyword(s):  
Functional Connectivity ◽  
Current Velocity ◽  
Landscape Structure ◽  
Species Interactions ◽  
Animal Movement ◽  
Critical Threshold ◽  
Future Research ◽  
Threshold Effects ◽  
Habitat Patches ◽  
Critical Thresholds

Abstract In landscape ecology, substantial theoretical progress has been made in understanding how critical threshold levels of habitat loss may result in sudden changes in landscape connectivity to animal movement. Empirical evidence for such thresholds in real systems, however, remains scarce. Streambed landscapes provide a strong testing ground for studying critical thresholds because organisms are faced with substantial environmental heterogeneity while attempting to overcome the physical force of water. In this study, I report on the results from a series of experiments investigating the influence of habitat abundance and current velocity on the movement dynamics of two stream herbivores (caddisfly larva Agapetus boulderensis and snail Physa sp.) that differ substantially in how they perceive landscape structure. Specifically, I ask whether critical thresholds to herbivore movement exist in streambed landscapes. By exploiting the pattern recognition capabilities of artificial neural networks, I found that the rate, sinuosity and directionality of movement by Agapetus and Physa varied nonlinearly according to the abundance of habitat patches, current velocity and habitat–current interaction. Both the study organisms exhibited threshold responses to habitat abundance, yet the location and slope of these thresholds differed between species and with respect to different current velocities. These results suggest that a critical threshold in functional connectivity (i.e. the connection of habitat patches by dispersal) is not an inherent property of the landscape, but in fact emerges from the interplay of species' interactions with landscape structure. Moreover, current velocity interacted with habitat abundance to elicit strong upstream-oriented movement for both the species. This suggests that dispersing individuals may be polarized in the upstream direction and therefore functional connectivity is not equal in all directions. Such results highlight the need for future research addressing the sources of variability of critical threshold effects in ecological phenomena.

Using hidden Markov models to find discrete targets in continuous sociophonetic data

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Daniel Duncan
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Abstract Representation ◽  
Language Variation And Change ◽  
Novel Approach ◽  
Single Target ◽  
The Individual ◽  
Individual Speaker

Abstract Advances in sociophonetic research resulted in features once sorted into discrete bins now being measured continuously. This has implied a shift in what sociolinguists view as the abstract representation of the sociolinguistic variable. When measured discretely, variation is variation in selection: one variant is selected for production, and factors influencing language variation and change are influencing the frequency at which variants are selected. Measured continuously, variation is variation in execution: speakers have a single target for production, which they approximate with varying success. This paper suggests that both approaches can and should be considered in sociophonetic analysis. To that end, I offer the use of hidden Markov models (HMMs) as a novel approach to find speakers’ multiple targets within continuous data. Using the lot vowel among whites in Greater St. Louis as a case study, I compare 2-state and 1-state HMMs constructed at the individual speaker level. Ten of fifty-two speakers’ production is shown to involve the regular use of distinct fronted and backed variants of the vowel. This finding illustrates HMMs’ capacity to allow us to consider variation as both variant selection and execution, making them a useful tool in the analysis of sociophonetic data.

scholarly journals HPM: A Hybrid Model for User’s Behavior Prediction Based on N-Gram Parsing and Access Logs

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Sonia Setia ◽  
Verma Jyoti ◽  
Neelam Duhan
Keyword(s):  
Web Mining ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Web Pages ◽  
Continuous Growth ◽  
Novel Approach ◽  
Content Mining ◽  
Long Access ◽  
N Gram ◽  
The Individual

The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% increase in precision of prediction and a 10% increase in hit ratio on average as compared to other mining techniques.

scholarly journals A Genetic Algorithm Approach for Group Recommender System Based on Partial Rankings

2018 ◽  
Vol 29 (1) ◽  
pp. 653-663 ◽  
Author(s):  
Ritu Meena ◽  
Kamal K. Bharadwaj
Keyword(s):  
Genetic Algorithm ◽  
Recommender Systems ◽  
Rank Aggregation ◽  
Partial Ranking ◽  
Novel Approach ◽  
Kendall Tau Distance ◽  
Ultimate Objective ◽  
Aggregation Technique ◽  
The Individual ◽  
Group Recommender

Abstract Many recommender systems frequently make suggestions for group consumable items to the individual users. There has been much work done in group recommender systems (GRSs) with full ranking, but partial ranking (PR) where items are partially ranked still remains a challenge. The ultimate objective of this work is to propose rank aggregation technique for effectively handling the PR problem. Additionally, in real applications, most of the studies have focused on PR without ties (PRWOT). However, the rankings may have ties where some items are placed in the same position, but where some items are partially ranked to be aggregated may not be permutations. In this work, in order to handle problem of PR in GRS for PRWOT and PR with ties (PRWT), we propose a novel approach to GRS based on genetic algorithm (GA) where for PRWOT Spearman foot rule distance and for PRWT Kendall tau distance with bucket order are used as fitness functions. Experimental results are presented that clearly demonstrate that our proposed GRS based on GA for PRWOT (GRS-GA-PRWOT) and PRWT (GRS-GA-PRWT) outperforms well-known baseline GRS techniques.

scholarly journals All fingers are not the same: Handling variable-length sequences in a discriminative setting using conformal multi-instance kernels

2017 ◽  
Author(s):  
Sarvesh Nikumbh ◽  
Peter Ebert ◽  
Nico Pfeifer
Keyword(s):  
Binary Classification ◽  
Positional Information ◽  
Weight Vector ◽  
Variable Length ◽  
Genomic Sequences ◽  
String Kernels ◽  
Promoter Sequences ◽  
Novel Approach ◽  
The Individual ◽  
Visualization Techniques

AbstractMost string kernels for comparison of genomic sequences are generally tied to using (absolute) positional information of the features in the individual sequences. This poses limitations when comparing variable-length sequences using such string kernels. For example, profiling chromatin interactions by 3C-based experiments results in variable-length genomic sequences (restriction fragments). Here, exact position-wise occurrence of signals in sequences may not be as important as in the scenario of analysis of the promoter sequences, that typically have a transcription start site as reference. Existing position-aware string kernels have been shown to be useful for the latter scenario.In this work, we propose a novel approach for sequence comparison that enables larger positional freedom than most of the existing approaches, can identify a possibly dispersed set of features in comparing variable-length sequences, and can handle both the aforementioned scenarios. Our approach, CoMIK, identifies not just the features useful towards classification but also their locations in the variable-length sequences, as evidenced by the results of three binary classification experiments, aided by recently introduced visualization techniques. Furthermore, we show that we are able to efficiently retrieve and interpret the weight vector for the complex setting of multiple multi-instance kernels.

Integrating variable traits and inheritance into the individual-based model LAVESI for evaluation of their importance for larch forest performance under future adverse conditions

2021 ◽  
Author(s):  
Josias Gloy ◽  
Stefan Kruse ◽  
Ulrike Herzschuh
Keyword(s):  
Boreal Forest ◽  
Drought Resistance ◽  
Migration Rate ◽  
Extinction Risk ◽  
Climate Data ◽  
The South ◽  
Trait Variation ◽  
Individual Based Model ◽  
Future Projections ◽  
The Individual

<p>With changing climate boreal forest need to shift their distribution further north and become threatened by droughts in the south. However, whether boreal forest species can adapt to novel situations and reduce their extinction risk is largely unknown but crucial to predict future performance of populations. Exploring variable traits and ultimately trait inheritance in an individual-based model could improve our understanding and help future projections.</p><p> </p><p>Hence, we updated the individual-based spatially explicit vegetation model LAVESI to allow for variation in traits values that are normally distributed and the option of determining the trait values based on the parental values, thus allowing full inheritance.</p><p> </p><p>Using historical climate data and future projections, we ran simulation experiments of <em>Larix gmelinii</em> stands in the two areas of interest, the northern treeline expanding due to increasing temperatures, and the southern area experiencing increased drought. At these regions, the trait of ‘seed weight’ regulate migration further north and the ‘drought resistance’ protecting stands in the south, a comparison of the model variants: uniform, variable and inherited traits is being performed.</p><p>The results will be presented and will allow to disentangle how far migration rate and survival rate are influenced by this. In preliminary tests, it was already shown that both the allowing trait variation and inheritance led to an increase in migration rate, with the latter having a stronger impact. Similarly, the early tests for the drought resistance show that in changing temperatures leading to droughts the trait variation allows for adaption and leads to better surviving populations.</p><p> </p><p>We expect that variable traits ensure that if the environment changes necessary trait variants are available. Inheritance could let the populations adapt to environments and promote successful trait values and therefore lead to more optimised populations, that are able to spread faster and be as resilient as needed.</p><p> </p><p>With this, we show that implementing trait variation and inheritance may contribute to creating more accurately predicting models and understanding responses of boreal forests to global change.</p>

scholarly journals Discriminating Suicide Attempters and Predicting Suicide Risk Using Altered Frontolimbic Resting-State Functional Connectivity in Patients With Bipolar II Disorder

2020 ◽  
Vol 11 ◽  
Author(s):  
Rongxin Zhu ◽  
Shui Tian ◽  
Huan Wang ◽  
Haiteng Jiang ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Suicide Risk ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Resting State Functional Connectivity ◽  
Bipolar Ii Disorder ◽  
Individual Level ◽  
Bipolar Ii ◽  
The Individual

Bipolar II disorder (BD-II) major depression episode is highly associated with suicidality, and objective neural biomarkers could be key elements to assist in early prevention and intervention. This study aimed to integrate altered brain functionality in the frontolimbic system and machine learning techniques to classify suicidal BD-II patients and predict suicidality risk at the individual level. A cohort of 169 participants were enrolled, including 43 BD-II depression patients with at least one suicide attempt during a current depressive episode (SA), 62 BD-II depression patients without a history of attempted suicide (NSA), and 64 demographically matched healthy controls (HCs). We compared resting-state functional connectivity (rsFC) in the frontolimbic system among the three groups and explored the correlation between abnormal rsFCs and the level of suicide risk (assessed using the Nurses' Global Assessment of Suicide Risk, NGASR) in SA patients. Then, we applied support vector machines (SVMs) to classify SA vs. NSA in BD-II patients and predicted the risk of suicidality. SA patients showed significantly decreased frontolimbic rsFCs compared to NSA patients. The left amygdala-right middle frontal gyrus (orbital part) rsFC was negatively correlated with NGASR in the SA group, but not the severity of depressive or anxiety symptoms. Using frontolimbic rsFCs as features, the SVMs obtained an overall 84% classification accuracy in distinguishing SA and NSA. A significant correlation was observed between the SVMs-predicted NGASR and clinical assessed NGASR (r = 0.51, p = 0.001). Our results demonstrated that decreased rsFCs in the frontolimbic system might be critical objective features of suicidality in BD-II patients, and could be useful for objective prediction of suicidality risk in individuals.

scholarly journals Effects on Some Therapeutical, Biochemical, and Immunological Parameters of Honey Bee (Apis mellifera) Exposed to Probiotic Treatments, in Field and Laboratory Conditions

Insects ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 638
Author(s):  
Ivana Tlak Gajger ◽  
Josipa Vlainić ◽  
Petra Šoštarić ◽  
Janez Prešern ◽  
Jernej Bubnič ◽  
...  
Keyword(s):  
Honey Bee ◽  
Honey Bees ◽  
Immunological Parameters ◽  
Individual Level ◽  
Sugar Syrup ◽  
Novel Approach ◽  
The Individual ◽  
Field And Laboratory Conditions ◽  
Negative Factors ◽  
Bee Colonies

Several negative factors contribute to a decline in the number of insect pollinators. As a novel approach in therapy, we hypothesize that the EM® for bees could potentially have an important therapeutic and immunomodulatory effect on honey bee colonies. The aim of our study was to evaluate its impact on honey bees at the individual and colony level. This is the first appliance of the commercial probiotic mix EM® PROBIOTIC FOR BEES in honey bees as economically important social insects. The sugar syrup with 10% of probiotic was administered by spraying or feeding the honey bee colonies in the field conditions, in order to evaluate the infection levels with spores of Nosema spp. and colonies’ strength. Moreover, in laboratory-controlled conditions, in the hoarding cages, adult workers have been fed with sugar syrup supplemented with 2.5, 5, and 10% of EM® for bees for biochemical and immunological analyses of hemolymph, and with 5 and 10% for measuring the size of hypopharyngeal glands. It was found that following the EM® for bees administration the Nosema spp. spore counts in colonies were significantly reduced, and colonies’ strength was increased. The results at the individual level showed significant positive physiological changes in treated groups of adult bees, revealing at the same time a higher mortality rate when feeding sugar syrup supplemented with the probiotic.

scholarly journals Beyond non-integer Hill coefficients: A novel approach to analyzing binding data, applied to Na+-driven transporters

2015 ◽  
Vol 145 (6) ◽  
pp. 555-563 ◽  
Author(s):  
Silvia Ravera ◽  
Matthias Quick ◽  
Juan P. Nicola ◽  
Nancy Carrasco ◽  
L. Mario Amzel
Keyword(s):  
Hill Equation ◽  
Integer Coefficient ◽  
Novel Approach ◽  
Binding Data ◽  
Na Ions ◽  
Hill Coefficients ◽  
Integer Exponent ◽  
The Individual ◽  
The Hill ◽  
Analyze Data

Prokaryotic and eukaryotic Na+-driven transporters couple the movement of one or more Na+ ions down their electrochemical gradient to the active transport of a variety of solutes. When more than one Na+ is involved, Na+-binding data are usually analyzed using the Hill equation with a non-integer exponent n. The results of this analysis are an overall Kd-like constant equal to the concentration of ligand that produces half saturation and n, a measure of cooperativity. This information is usually insufficient to provide the basis for mechanistic models. In the case of transport using two Na+ ions, an n < 2 indicates that molecules with only one of the two sites occupied are present at low saturation. Here, we propose a new way of analyzing Na+-binding data for the case of two Na+ ions that, by taking into account binding to individual sites, provides far more information than can be obtained by using the Hill equation with a non-integer coefficient: it yields pairs of possible values for the Na+ affinities of the individual sites that can only vary within narrowly bounded ranges. To illustrate the advantages of the method, we present experimental scintillation proximity assay (SPA) data on binding of Na+ to the Na+/I− symporter (NIS). SPA is a method widely used to study the binding of Na+ to Na+-driven transporters. NIS is the key plasma membrane protein that mediates active I− transport in the thyroid gland, the first step in the biosynthesis of the thyroid hormones, of which iodine is an essential constituent. NIS activity is electrogenic, with a 2:1 Na+/I− transport stoichiometry. The formalism proposed here is general and can be used to analyze data on other proteins with two binding sites for the same substrate.

scholarly journals Elicitation as a Multilayered Process

2018 ◽  
Vol 17 (1) ◽  
pp. 160940691879701 ◽  
Author(s):  
Emma K. Tsui ◽  
Emily Franzosa
Keyword(s):  
Data Collection ◽  
Individual Interview ◽  
Novel Approach ◽  
Shared Authority ◽  
Interview Training ◽  
The Individual ◽  
The Way

This article describes a novel approach to reciprocal peer interviewing in which participants interview one another sequentially, allowing each the space of a full interview to articulate her experiences and reflections. This structure of data collection offers a new conceptualization of the way that elicitation functions; not just as a process inside of an interview, but one that is also shaped by factors preceding and outside of the individual interview, a process we call “meta-elicitation.” We argue that this form of reciprocal peer interviewing offers a view of the emic that is both participant-led and uniquely balanced between collective and individual perspectives. However, we also argue that shared authority and rapport are actively, and not always successfully, negotiated in such interviews. To prepare participants for peer interviewing, we hosted a 1-day workshop involving interview training, planning, and the recording of interviews. To maximize quality of such projects, we recommend that external researchers consider carefully (1) the balance of structure and flexibility in designing the workshop and interviews, (2) thorough preparation of participants, and (3) the role of meta-elicitation dynamics during analysis.

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