A null model for quantifying the geometric effect of habitat subdivision on species diversity

2021 ◽  
Author(s):  
David C. Deane ◽  
Dingliang Xing ◽  
Cang Hui ◽  
Melodie McGeoch ◽  
Fangliang He
Keyword(s):  
Species Diversity ◽  
Null Model ◽  
Geometric Effect

Species diversity: a new null model

Cladistics ◽  
2002 ◽  
Vol 18 (5) ◽  
pp. 537-538
Author(s):  
E PIANKA
Keyword(s):  
Species Diversity ◽  
Null Model

The tropics: cradle, museum or casino? A dynamic null model for latitudinal gradients of species diversity

2008 ◽  
Vol 11 (7) ◽  
pp. 653-663 ◽  
Author(s):  
Héctor T. Arita ◽  
Ella Vázquez-Domínguez
Keyword(s):  
Species Diversity ◽  
Null Model ◽  
Latitudinal Gradients ◽  
The Tropics

The relationship between proportion of endemics and species diversity on islands: expectations from a null model

Ecography ◽  
2008 ◽  
Vol 31 (2) ◽  
pp. 286-288 ◽  
Author(s):  
Ayşegül Birand ◽  
Daniel J. Howard
Keyword(s):  
Species Diversity ◽  
Null Model ◽  
The Relationship

scholarly journals Does regional diversity recover after disturbance? A field experiment in constructed ponds

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2455 ◽  
Author(s):  
Lauren M. Woods ◽  
Elizabeth G. Biro ◽  
Muxi Yang ◽  
Kevin G. Smith
Keyword(s):  
Species Diversity ◽  
Aquatic Invertebrates ◽  
Spatial Scales ◽  
Null Model ◽  
Biodiversity Loss ◽  
Species Loss ◽  
Fish Removal ◽  
Regional Diversity ◽  
Local Species ◽  
One Year

The effects of disturbance on local species diversity have been well documented, but less recognized is the possibility that disturbances can alter diversity at regional spatial scales. Since regional diversity can dictate which species are available for recolonization of degraded sites, the loss of diversity at regional scales may impede the recovery of biodiversity following a disturbance. To examine this we used a chemical disturbance of rotenone, a piscicide commonly used for fish removal in aquatic habitats, on small fishless freshwater ponds. We focused on the non-target effects of rotenone on aquatic invertebrates with the goal of assessing biodiversity loss and recovery at both local (within-pond) and regional (across ponds) spatial scales. We found that rotenone caused significant, large, but short-term losses of species at both local and regional spatial scales. Using a null model of random extinction, we determined that species were selectively removed from communities relative to what would be expected if species loss occurred randomly. Despite this selective loss of biodiversity, species diversity at both local and regional spatial scales recovered to reference levels one year after the addition of rotenone. The rapid recovery of local and regional diversity in this study was surprising considering the large loss of regional species diversity, however many aquatic invertebrates disperse readily or have resting stages that may persist through disturbances. We emphasize the importance of considering spatial scale when quantifying the impacts of a disturbance on an ecosystem, as well as considering how regional species loss can influence recovery from disturbance.

The relationship between proportion of endemics and species diversity on islands: expectations from a null model

Ecography ◽  
2008 ◽  
Vol 0 (0) ◽  
pp. 080227084236895-0
Author(s):  
Ayşegül Birand ◽  
Daniel J. Howard
Keyword(s):  
Species Diversity ◽  
Null Model ◽  
The Relationship

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Counter culture: Causes, extent and solutions of systematic bias in the analysis of behavioural counts

2019 ◽  
Author(s):  
Joel L Pick ◽  
Nyil Khwaja ◽  
Michael A. Spence ◽  
Malika Ihle ◽  
Shinichi Nakagawa
Keyword(s):  
Recent Literature ◽  
Null Model ◽  
Mechanistic Explanation ◽  
Effect Sizes ◽  
Systematic Bias ◽  
Intra Class Correlation ◽  
Counter Culture ◽  
Provisioning Rate ◽  
Parental Provisioning ◽  
Observation Period

We often quantify a behaviour by counting the number of times it occurs within a specific, short observation period. Measuring behaviour in such a way is typically unavoidable but induces error. This error acts to systematically reduce effect sizes, including metrics of particular interest to behavioural and evolutionary ecologists such as R2, repeatability (intra-class correlation, ICC) and heritability. Through introducing a null model, the Poisson process, for modelling the frequency of behaviour, we give a mechanistic explanation of how this problem arises and demonstrate how it makes comparisons between studies and species problematic, because the magnitude of the error depends on how frequently the behaviour has been observed (e.g. as a function of the observation period) as well as how biologically variable the behaviour is. Importantly, the degree of error is predictable and so can be corrected for. Using the example of parental provisioning rate in birds, we assess the applicability of our null model for modelling the frequency of behaviour. We then review recent literature and demonstrate that the error is rarely accounted for in current analyses. We highlight the problems that arise from this and provide solutions. We further discuss the biological implications of deviations from our null model, and highlight the new avenues of research that they may provide. Adopting our recommendations into analyses of behavioural counts will improve the accuracy of estimated effect sizes and allow meaningful comparisons to be made between studies.

Species diversity, abundance, biomass, size and trophic structure of fish on coral reefs in relation to shark abundance

2017 ◽  
Vol 565 ◽  
pp. 163-179 ◽  
Author(s):  
SC Barley ◽  
MG Meekan ◽  
JJ Meeuwig
Keyword(s):  
Species Diversity ◽  
Coral Reefs ◽  
Trophic Structure

Diatoms in the Early Valdai (Weichselian) sediments in Lake Ladoga basin

2019 ◽  
pp. 225-228
Author(s):  
Anna V. Ludikova
Keyword(s):  
Species Diversity ◽  
High Energy ◽  
Lake Ladoga ◽  
Diatom Assemblages ◽  
Marine Diatoms ◽  
Selective Preservation

The pioneer diatom study of the Early Weichselian (Valdai) sediments in Lake Ladoga basin was performed. The specifics of the diatom assemblages (co-occurrence of ecologically incompatible taxa, poor species diversity, low diatom concentration and selective preservation) suggest that during the Early Weichselian time intense erosion of previously deposited marine Eemian (Mikulino) sediments prevailed, which resulted in re-deposition of marine diatoms. The sedimentation took place in high-energy environments unfavorable for diatom accumulation and preservation.

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