The Experts below are selected from a list of 5916 Experts worldwide ranked by ideXlab platform
Werner Ulrich - One of the best experts on this subject based on the ideXlab platform.
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On the meanings of Nestedness: back to the basics
Ecography, 2012Co-Authors: Werner Ulrich, Mário Almeida-netoAbstract:The ecological concepts of Nestedness and b-diversity first appeared more than five decades ago, but there is still controversy over their precise meaning and application. Here, we focus on the concept of Nestedness, the ordered loss of species along environmental or ecological gradients. Because there is no species replacement if the distribution of species among a number of sites is perfectly nested, some studies have defined Nestedness as the inverse of species turnover. We argue that such a redefinition relies on a misinterpretation of the original concept of Nestedness as the inverse of species replacement. Such a narrow interpretation might result in misleading conclusions about the mechanisms regulating species distribution patterns. We argue, in particular, that any quantification of Nestedness must be as explicit as possible about the gradient to be analyzed.
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Rethinking the relationship between Nestedness and beta diversity: a comment on Baselga (2010)
Global Ecology and Biogeography, 2011Co-Authors: Mário Almeida-neto, Daniella M. B. Frensel, Werner UlrichAbstract:Baselga [Partitioning the turnover and Nestedness components of beta diversity. Global Ecology and Biogeography, 19, 134–143, 2010] proposed pairwise (βnes) and multiple-site (βNES) beta-diversity measures to account for the Nestedness component of beta diversity. We used empirical, randomly created and idealized matrices to show that both measures are only partially related to Nestedness and do not fit certain fundamental requirements for consideration as true Nestedness-resultant dissimilarity measures. Both βnes and βNES are influenced by matrix size and fill, and increase or decrease even when Nestedness remains constant. Additionally, we demonstrate that βNES can yield high values even for matrices with no Nestedness. We conclude that βnes and βNES are not true measures of the Nestedness-resultant dissimilarity between sites. Actually, they quantify how differences in species richness that are not due to species replacement contribute to patterns of beta diversity. Finally, because Nestedness is a special case of dissimilarity in species composition due to ordered species loss (or gain), the extent to which differences in species composition is due to Nestedness can be measured through an index of Nestedness.
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A straightforward computational approach for measuring Nestedness using quantitative matrices
Environmental Modelling & Software, 2011Co-Authors: Mário Almeida-neto, Werner UlrichAbstract:Nestedness has been one of the most reported patterns of species distribution in metacommunities as well as of species interactions in bipartite networks. We propose here a straightforward approach for quantifying Nestedness using quantitative instead of presence–absence data. We named our estimator WNODF because it is a simple modification of the Nestedness index called NODF. We also introduce the NODF-Program that calculates the above described Nestedness metrics as well as metrics for idiosyncratic species and sites. Statistical inference is done through a null model approach, in which the user can choose among five null models commonly used for presence–absence matrices as well as three randomization algorithms for matrices that contain quantitative data. The program performs multiple analyses using many matrices. Finally, the NODF-Program provides four sorting options that, together with the null algorithms, cover a range of possibilities to test hypotheses on the possible mechanisms producing nested patterns. By using a set of model matrices, we showed that WNODF differentiates nested matrices with distinct structures and correctly identifies matrices with no nested pattern as having zero degree of Nestedness.
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A consumer's guide to Nestedness analysis
Oikos, 2009Co-Authors: Werner Ulrich, Mário Almeida-neto, Nicholas J GotelliAbstract:Nestedness analysis has become increasingly popular in the study of biogeographic patterns of species occurrence. Nested patterns are those in which the species composition of small assemblages is a nested subset of larger assemblages. For species interaction networks such as plantpollinator webs, Nestedness analysis has also proven a valuable tool for revealing ecological and evolutionary constraints. Despite this popularity, there has been substantial controversy in the literature over the best methods to define and quantify Nestedness, and how to test for patterns of Nestedness against an appropriate statistical null hypothesis. Here we review this rapidly developing literature and provide suggestions and guidelines for proper analyses. We focus on the logic and the performance of different metrics and the proper choice of null models for statistical inference. We observe that traditional ‘gap-counting’ metrics are biased towards species loss among columns (occupied sites) and that many metrics are not invariant to basic matrix properties. The study of Nestedness should be combined with an appropriate gradient analysis to infer possible causes of the observed presence absence sequence. In our view, statistical inference should be based on a null model in which row and columns sums are fixed. Under this model, only a relatively small number of published empirical matrices are significantly nested. We call for a critical reassessment of previous studies that have used biased metrics and unconstrained null models for statistical inference.
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a consistent metric for Nestedness analysis in ecological systems reconciling concept and measurement
Oikos, 2008Co-Authors: Mario Almeidaneto, Rafael Loyola, Gleb Wataghin, Werner UlrichAbstract:Nestedness has been widely reported for both metacommunities and networks of interacting species. Even though the concept of this ecological pattern has been well-defined, there are several metrics by which it can be quantified. We noted that current metrics do not correctly quantify two major properties of Nestedness: (1) whether marginal totals (i.e. fills) differ among columns and/or among rows, and (2) whether the presences (1’s) in less-filled columns and rows coincide, respectively, with those found in the more-filled columns and rows. We propose a new metric directly based on these properties and compare its behavior with that of the most used metrics, using a set of model matrices ranging from highly-nested to alternative structures in which no Nestedness should be detected. We also used an empirical dataset to explore possible biases generated by the metrics as well as to evaluate correlations between metrics. We found that Nestedness has been quantified by metrics that inappropriately detect this pattern, even for matrices in which there is no Nestedness. In addition, the most used metrics are prone to type I statistical errors while our new metric has better statistical properties and consistently rejects a nested pattern for different types of random matrices. The analysis of the empirical data showed that two Nestedness metrics, matrix temperature and the discrepancy measure, tend to overestimate the degrees of Nestedness in metacommunities. We emphasize and discuss some implications of these biases for the theoretical understanding of the processes shaping species interaction networks and metacommunity structure.
Mario Almeidaneto - One of the best experts on this subject based on the ideXlab platform.
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a consistent metric for Nestedness analysis in ecological systems reconciling concept and measurement
Oikos, 2008Co-Authors: Mario Almeidaneto, Rafael Loyola, Gleb Wataghin, Werner UlrichAbstract:Nestedness has been widely reported for both metacommunities and networks of interacting species. Even though the concept of this ecological pattern has been well-defined, there are several metrics by which it can be quantified. We noted that current metrics do not correctly quantify two major properties of Nestedness: (1) whether marginal totals (i.e. fills) differ among columns and/or among rows, and (2) whether the presences (1’s) in less-filled columns and rows coincide, respectively, with those found in the more-filled columns and rows. We propose a new metric directly based on these properties and compare its behavior with that of the most used metrics, using a set of model matrices ranging from highly-nested to alternative structures in which no Nestedness should be detected. We also used an empirical dataset to explore possible biases generated by the metrics as well as to evaluate correlations between metrics. We found that Nestedness has been quantified by metrics that inappropriately detect this pattern, even for matrices in which there is no Nestedness. In addition, the most used metrics are prone to type I statistical errors while our new metric has better statistical properties and consistently rejects a nested pattern for different types of random matrices. The analysis of the empirical data showed that two Nestedness metrics, matrix temperature and the discrepancy measure, tend to overestimate the degrees of Nestedness in metacommunities. We emphasize and discuss some implications of these biases for the theoretical understanding of the processes shaping species interaction networks and metacommunity structure.
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a consistent metric for Nestedness analysis in ecological systems reconciling concept and measurement
Oikos, 2008Co-Authors: Mario Almeidaneto, Rafael Loyola, Paulo R. Guimarães, Paulo Guimaraes, Werner UlrichAbstract:Nestedness has been widely reported for both metacommunities and networks of interacting species. Even though the concept of this ecological pattern has been well-defined, there are several metrics by which it can be quantified. We noted that current metrics do not correctly quantify two major properties of Nestedness: (1) whether marginal totals (i.e. fills) differ among columns and/or among rows, and (2) whether the presences (1’s) in less-filled columns and rows coincide, respectively, with those found in the more-filled columns and rows. We propose a new metric directly based on these properties and compare its behavior with that of the most used metrics, using a set of model matrices ranging from highly-nested to alternative structures in which no Nestedness should be detected. We also used an empirical dataset to explore possible biases generated by the metrics as well as to evaluate correlations between metrics. We found that Nestedness has been quantified by metrics that inappropriately detect this pattern, even for matrices in which there is no Nestedness. In addition, the most used metrics are prone to type I statistical errors while our new metric has better statistical properties and consistently rejects a nested pattern for different types of random matrices. The analysis of the empirical data showed that two Nestedness metrics, matrix temperature and the discrepancy measure, tend to overestimate the degrees of Nestedness in metacommunities. We emphasize and discuss some implications of these biases for the theoretical understanding of the processes shaping species interaction networks and metacommunity structure.
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on Nestedness analyses rethinking matrix temperature and anti Nestedness
Oikos, 2007Co-Authors: Mario Almeidaneto, Paulo R. Guimarães, Thomas M. LewinsohnAbstract:The analysis of nested structures in sets of species assemblages across different sites or in networks of interspecific interactions has become common practice in ecological studies. Although new analyses and metrics have been proposed, few studies have scrutinized the concepts that subtend Nestedness analysis. We note two important conceptual problems that can lead to terminological inconsistencies and flawed interpretations. First, the thermodynamic analogy that underlies the most common metric of Nestedness, matrix temperature, is flawed and has led some authors to incorrect interpretations. Second, the term ‘‘anti-Nestedness’’ is a potential source of confusion and inconsistencies. We review four concepts for anti-Nestedness and examine how distinct they are. ‘‘Anti-nested’’ matrices, i.e. less nested than expected by chance, may result from different ecological processes and show distinct structural patterns. Thus, there is no single unequivocal opposite of Nestedness to be represented as ‘‘anti-Nestedness’’. A more profitable approach is to designate and test each distinct non-nested pattern according to its specific assumptions and mechanistic hypotheses.
Serdar Yüksel - One of the best experts on this subject based on the ideXlab platform.
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stochastic Nestedness and the belief sharing information pattern in decentralized control
American Control Conference, 2009Co-Authors: Serdar YükselAbstract:In a dynamic decentralized control problem, a common information state supplied to each of the Decision Makers leads to a tractable dynamic programming recursion. However, communication requirements for such conditions require exchange of very large data noiselessly, hence these assumptions are generally impractical. We present a weaker notion of Nestedness, which we term as stochastic Nestedness, which is characterized by a sequence of Markov chain conditions. It is shown that if the information structure is stochastically nested, then an optimization problem is tractable, and in particular for LQG problems, the team optimal solution is linear, despite the lack of deterministic Nestedness or partial Nestedness. One other contribution of this paper is that, by regarding the multiple decision makers as a single decision maker and using Witsenhausen's equivalent model for discrete-stochastic control, it is shown that the common state required need not consist of observations and it suffices to share beliefs on the state and control actions; a pattern we refer to as k-stage belief sharing pattern. We evaluate a precise expression for the minimum amount of information required to achieve such an information pattern for k = 1. The information exchange needed is generally strictly less than the information exchange needed for deterministic Nestedness and is zero whenever stochastic Nestedness applies.
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Stochastic Nestedness and the Belief Sharing Information Pattern
IEEE Transactions on Automatic Control, 2009Co-Authors: Serdar YükselAbstract:Solutions to decentralized stochastic optimization problems lead to recursions in which the state space enlarges with the time-horizon, thus leading to non-tractability of classical dynamic programming. A common joint information state supplied to each of the agents leads to a tractable recursion, as is evident in the one-step-delayed information sharing structure case or when deterministic Nestedness in information holds when there is a causality relationship as in the case of partially nested information structure. However, communication requirements for such conditions require exchange of very large data noiselessly, hence these assumptions are generally impractical. In this paper, we present a weaker notion of Nestedness, which we term as stochastic Nestedness, which is characterized by a sequence of Markov chain conditions. It is shown that if the information structure is stochastically nested, then an optimization problem is tractable, and in particular for LQG problems, the team optimal solution is linear, despite the lack of deterministic Nestedness or partial Nestedness. One other contribution of this paper is that, by regarding the multiple decision makers as a single decision maker and using Witsenhausen's equivalent model for discrete-stochastic control, it is shown that the common state required need not consist of observations and it suffices to share beliefs on the state and control actions; a pattern we refer to as k-stage belief sharing pattern. We discuss the minimum amount of information exchange required to achieve such an information pattern for k =1. The information exchange needed is generally strictly less than what is needed for deterministic Nestedness and is zero whenever stochastic Nestedness applies. In view of Nestedness, we present a discussion on the monotone values of information channels.
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ACC - Stochastic Nestedness and the belief sharing information pattern in decentralized control
2009 American Control Conference, 2009Co-Authors: Serdar YükselAbstract:In a dynamic decentralized control problem, a common information state supplied to each of the Decision Makers leads to a tractable dynamic programming recursion. However, communication requirements for such conditions require exchange of very large data noiselessly, hence these assumptions are generally impractical. We present a weaker notion of Nestedness, which we term as stochastic Nestedness, which is characterized by a sequence of Markov chain conditions. It is shown that if the information structure is stochastically nested, then an optimization problem is tractable, and in particular for LQG problems, the team optimal solution is linear, despite the lack of deterministic Nestedness or partial Nestedness. One other contribution of this paper is that, by regarding the multiple decision makers as a single decision maker and using Witsenhausen's equivalent model for discrete-stochastic control, it is shown that the common state required need not consist of observations and it suffices to share beliefs on the state and control actions; a pattern we refer to as k-stage belief sharing pattern. We evaluate a precise expression for the minimum amount of information required to achieve such an information pattern for k = 1. The information exchange needed is generally strictly less than the information exchange needed for deterministic Nestedness and is zero whenever stochastic Nestedness applies.
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Stochastic Nestedness and information analysis of tractability in decentralized control
2008 46th Annual Allerton Conference on Communication Control and Computing, 2008Co-Authors: Serdar YükselAbstract:Communication requirements for Nestedness conditions require exchange of very large data noiselessly, hence these assumptions are generally impractical. In this paper, we present a weaker notion of Nestedness, which we term as stochastic Nestedness. Stochastic Nestedness is characterized with a sequence of Markov chain conditions. It is shown that if the information structure of two decision makers satisfy a stochastically nested structure, then the optimization admits a dynamic programming recursion and the optimization is tractable; and in particular for the LQG problems, the team optimal solution is linear, despite the lack of deterministic Nestedness or partial Nestedness. It is also shown that the common state required need not be consisting of observations and it suffices to share beliefs on the state and applied control actions; a pattern we refer to as k-step belief sharing pattern. In case stochastic Nestedness is absent, we can evaluate a precise expression for the minimum amount of information required to achieve belief sharing. The information exchange needed is generally strictly less than the information exchange needed for deterministic Nestedness (even under optimal coders) and is zero whenever stochastic Nestedness applies. We provide explicit examples of stochastically nested information structures and exhibit the benefit of belief sharing on information exchange requirements and discuss the monotone value of information channels.
Yanping Wang - One of the best experts on this subject based on the ideXlab platform.
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Nestedness and underlying processes of bird assemblages in Nanjing urban parks
Current Zoology, 2020Co-Authors: Xinwei Tan, Xueru Yang, Chuanwu Chen, Yanping WangAbstract:Abstract Nestedness is an important pattern frequently reported for species assemblages on islands or fragmented systems. However, to date, there are few studies that comprehensively investigated faunal Nestedness and underlying processes in urbanized landscapes. In this study, we examined the Nestedness of bird assemblages and its underlying causal mechanisms in 37 urban parks in Nanjing, China. We used the line-transect method to survey birds from April 2019 to January 2020. We used the Weighted Nestedness metric based on Overlap and Decreasing Fill (WNODF) to estimate the Nestedness of bird assemblages. We applied spearman partial correlation test to examine the relationships between Nestedness ranks of sites and park characteristics (area, isolation, anthropogenic noise, number of habitat types, and building index), as well as between Nestedness ranks of species and their ecological traits (body size, geographic range size, clutch size, minimum area requirement, dispersal ratio, and habitat specificity). We found that bird assemblages in urban parks were significantly nested. Park area, habitat diversity, building index, habitat specificity, and minimum area requirement of birds were significantly correlated with Nestedness. Therefore, the Nestedness of bird assemblages was caused by selective extinction, habitat Nestedness, and urbanization. However, the Nestedness of bird assemblages did not result from passive sampling, selective colonization, or human disturbance. Overall, to maximize the number of species preserved in our system, conservation priority should be given to parks with large area, rich habitat diversity, and less building index. From a species perspective, we should focus on species with large area requirement and high habitat specificity for their effective conservation.
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Nestedness of waterbird assemblages in the subsidence wetlands recently created by underground coal mining.
Current zoology, 2018Co-Authors: Binbin Zhao, Yanping WangAbstract:Nestedness has been a research focus in fields of island biogeography and community ecology in recent decades. Although Nestedness of faunal assemblages has been investigated in natural wetlands, it remains largely unknown whether and why waterbird communities in artificial wetlands follow nested patterns. We examined the existence of Nestedness and underlying drivers in waterbird communities in subsidence wetlands that are recently created by large-scale underground coal mining in the North China Plain. Twelve point-count surveys for waterbirds were undertaken approximately every 2 weeks in 55 subsidence wetlands from September 2016 to April 2017. We used the metric WNODF to estimate Nestedness of the assemblages. Partial Spearman rank correlations were performed to examine the association between the Nestedness and habitat variables (wetland area, landscape connectivity, wetland age, and habitat diversity) as well as life-history traits (body size, clutch size, dispersal ratio, geographical range size, and migrant status) related to species extinction risk and colonization rate. Waterbird assemblages in the subsidence wetlands were significantly nested. After controlling for other independent variables, the magnitude of Nestedness was significantly and negatively correlated with wetland area and species trait linked to extinction risk (i.e., geographical range size). Our results indicate that selective extinction may be the main driver of the Nestedness of waterbird assemblages in our study system. However, the Nestedness was not due to passive sampling, selective colonization, or habitat diversity. From a conservation viewpoint, both large wetlands and waterbirds with a small geographic range should be protected to maximize the preserved species richness.
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Nestedness of butterfly assemblages in the zhoushan archipelago china area effects life history traits and conservation implications
Biodiversity and Conservation, 2017Co-Authors: Xufang Han, Xuemei Zhang, Virginie Millien, Yanping WangAbstract:The nested subset pattern (Nestedness) of faunal assemblages has been a research focus in the fields of island biogeography and conservation biology in recent decades. However, relatively few studies have described Nestedness in butterfly assemblages in oceanic archipelago systems. Moreover, previous studies often quantified Nestedness using inappropriate Nestedness metrics and random fill algorithms with high Type I errors. The aims of this study are to examine the existence of Nestedness and underlying causal mechanisms of butterfly assemblages in the Zhoushan Archipelago, China. We used the line-transect method to determine butterfly occupancy and abundance on 42 study islands from July to August 2014. We obtained butterfly life-history traits (wingspan, body weight and minimum area requirement) by field work and island geographical features (area and isolation) from the literature. We used the recently developed metric WNODF to estimate Nestedness. Partial Spearman rank correlation was used to evaluate the associations of Nestedness and island geographical features as well as butterfly life-history traits related to species extinction risk and colonization ability. The butterfly assemblages were significantly nested. Island area and minimum area requirement of butterflies were significantly correlated with Nestedness after controlling for other independent variables. In contrast, the Nestedness of butterflies did not appear to result from passive sampling or selective colonization. However, multi-year studies are needed to confirm that target effects are not muddling these results. Our results indicate that selective extinction may be the main driver of Nestedness of butterfly assemblages in our study system. From a conservation viewpoint, we should protect both large islands and species with large area requirement to maximize the number of species preserved.
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Nestedness of bird assemblages on urban woodlots: Implications for conservation
Landscape and Urban Planning, 2013Co-Authors: Yanping Wang, Ping Ding, Shuihua Chen, Guangmei ZhengAbstract:Abstract Nestedness is a pattern frequently observed in fragmented systems and has important implications for conservation. The few existing Nestedness studies in urban landscapes have focused on the resident and breeding birds, while little attention has been paid to the wintering birds. Using distribution data of 60 bird species collected on 20 urban woodlots in Hangzhou, China, we tested for the existence of the Nestedness and the underlying mechanisms for breeding birds and wintering species separately. We used the line-transect method to survey bird occupancy and abundance on 20 woodlots. We used two recently developed metrics, WNODF and NODF, to estimate Nestedness. We used partial Spearman rank correlations to examine the associations of Nestedness and habitat variables (area, isolation, habitat richness and human disturbance). We also used information-theoretic methods based on Akaike Information Criterion (AIC) to determine ecological processes underlying Nestedness. The community compositions of breeding birds and wintering species were all significantly nested. Habitat Nestedness is the main driver of species Nestedness for all the bird assemblages. Human disturbance played an important role in the development of species Nestedness for breeding birds, but not for wintering species. Nestedness of all the bird assemblages was not due to passive sampling, selective extinction or selective colonization. From a conservation viewpoint, our results indicate that we should protect woodlots with diverse habitats priorly and refrain from using breeding birds and wintering species as surrogates for each other in developing conservation planning.
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Nestedness of snake assemblages on islands of an inundated lake
Current Zoology, 2012Co-Authors: Yanping Wang, Xi Wang, Ping DingAbstract:Nestedness is a pattern frequently reported for faunal assemblages in fragmented systems. Although Nestedness has been documented for a wide range of taxa, it is rarely tested in snake assemblages. To arrive at robust generalizations about proce- sses and mechanisms structuring island biotas, it is important to examine under-represented taxa such as snakes for the insights they may offer. We tested for the existence of Nestedness and underlying causal mechanisms using snake data collected on islands in the Thousand Island Lake, China. We used the line-transect method to survey snake occupancy and abundance on 20 islands during two breeding seasons in 2009 and 2010. We used the recently developed metric WNODF to estimate Nestedness. We used Spearman rank correlations to examine the associations of Nestedness and habitat variables (area, isolation, and habitat diversity) as well as life-history traits (body size, clutch size, geographical range size and area requirement) related to species extinction and immigration tendencies. Snake assemblages were significantly nested and were shaped by extinction processes mediated through area effects and habitat Nestedness. The Nestedness of snake assemblages was not due to passive sampling or selective coloniza- tion. From a conservation viewpoint, our results indicate that we should protect both the largest island with the most species-rich community and habitat-rich islands to maximize the number of species preserved (Current Zoology 58 (6): 828-836, 2012). Keywords Habitat fragmentation, Habitat Nestedness, Nestedness, Selective extinction, Snake, Thousand Island Lake
Mário Almeida-neto - One of the best experts on this subject based on the ideXlab platform.
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On the meanings of Nestedness: back to the basics
Ecography, 2012Co-Authors: Werner Ulrich, Mário Almeida-netoAbstract:The ecological concepts of Nestedness and b-diversity first appeared more than five decades ago, but there is still controversy over their precise meaning and application. Here, we focus on the concept of Nestedness, the ordered loss of species along environmental or ecological gradients. Because there is no species replacement if the distribution of species among a number of sites is perfectly nested, some studies have defined Nestedness as the inverse of species turnover. We argue that such a redefinition relies on a misinterpretation of the original concept of Nestedness as the inverse of species replacement. Such a narrow interpretation might result in misleading conclusions about the mechanisms regulating species distribution patterns. We argue, in particular, that any quantification of Nestedness must be as explicit as possible about the gradient to be analyzed.
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Rethinking the relationship between Nestedness and beta diversity: a comment on Baselga (2010)
Global Ecology and Biogeography, 2011Co-Authors: Mário Almeida-neto, Daniella M. B. Frensel, Werner UlrichAbstract:Baselga [Partitioning the turnover and Nestedness components of beta diversity. Global Ecology and Biogeography, 19, 134–143, 2010] proposed pairwise (βnes) and multiple-site (βNES) beta-diversity measures to account for the Nestedness component of beta diversity. We used empirical, randomly created and idealized matrices to show that both measures are only partially related to Nestedness and do not fit certain fundamental requirements for consideration as true Nestedness-resultant dissimilarity measures. Both βnes and βNES are influenced by matrix size and fill, and increase or decrease even when Nestedness remains constant. Additionally, we demonstrate that βNES can yield high values even for matrices with no Nestedness. We conclude that βnes and βNES are not true measures of the Nestedness-resultant dissimilarity between sites. Actually, they quantify how differences in species richness that are not due to species replacement contribute to patterns of beta diversity. Finally, because Nestedness is a special case of dissimilarity in species composition due to ordered species loss (or gain), the extent to which differences in species composition is due to Nestedness can be measured through an index of Nestedness.
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A straightforward computational approach for measuring Nestedness using quantitative matrices
Environmental Modelling & Software, 2011Co-Authors: Mário Almeida-neto, Werner UlrichAbstract:Nestedness has been one of the most reported patterns of species distribution in metacommunities as well as of species interactions in bipartite networks. We propose here a straightforward approach for quantifying Nestedness using quantitative instead of presence–absence data. We named our estimator WNODF because it is a simple modification of the Nestedness index called NODF. We also introduce the NODF-Program that calculates the above described Nestedness metrics as well as metrics for idiosyncratic species and sites. Statistical inference is done through a null model approach, in which the user can choose among five null models commonly used for presence–absence matrices as well as three randomization algorithms for matrices that contain quantitative data. The program performs multiple analyses using many matrices. Finally, the NODF-Program provides four sorting options that, together with the null algorithms, cover a range of possibilities to test hypotheses on the possible mechanisms producing nested patterns. By using a set of model matrices, we showed that WNODF differentiates nested matrices with distinct structures and correctly identifies matrices with no nested pattern as having zero degree of Nestedness.
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A consumer's guide to Nestedness analysis
Oikos, 2009Co-Authors: Werner Ulrich, Mário Almeida-neto, Nicholas J GotelliAbstract:Nestedness analysis has become increasingly popular in the study of biogeographic patterns of species occurrence. Nested patterns are those in which the species composition of small assemblages is a nested subset of larger assemblages. For species interaction networks such as plantpollinator webs, Nestedness analysis has also proven a valuable tool for revealing ecological and evolutionary constraints. Despite this popularity, there has been substantial controversy in the literature over the best methods to define and quantify Nestedness, and how to test for patterns of Nestedness against an appropriate statistical null hypothesis. Here we review this rapidly developing literature and provide suggestions and guidelines for proper analyses. We focus on the logic and the performance of different metrics and the proper choice of null models for statistical inference. We observe that traditional ‘gap-counting’ metrics are biased towards species loss among columns (occupied sites) and that many metrics are not invariant to basic matrix properties. The study of Nestedness should be combined with an appropriate gradient analysis to infer possible causes of the observed presence absence sequence. In our view, statistical inference should be based on a null model in which row and columns sums are fixed. Under this model, only a relatively small number of published empirical matrices are significantly nested. We call for a critical reassessment of previous studies that have used biased metrics and unconstrained null models for statistical inference.
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On Nestedness analyses: rethinking matrix temperature and anti‐Nestedness
Oikos, 2007Co-Authors: Mário Almeida-neto, Paulo R. Guimarães, Thomas M. LewinsohnAbstract:The analysis of nested structures in sets of species assemblages across different sites or in networks of interspecific interactions has become common practice in ecological studies. Although new analyses and metrics have been proposed, few studies have scrutinized the concepts that subtend Nestedness analysis. We note two important conceptual problems that can lead to terminological inconsistencies and flawed interpretations. First, the thermodynamic analogy that underlies the most common metric of Nestedness, matrix temperature, is flawed and has led some authors to incorrect interpretations. Second, the term ‘‘anti-Nestedness’’ is a potential source of confusion and inconsistencies. We review four concepts for anti-Nestedness and examine how distinct they are. ‘‘Anti-nested’’ matrices, i.e. less nested than expected by chance, may result from different ecological processes and show distinct structural patterns. Thus, there is no single unequivocal opposite of Nestedness to be represented as ‘‘anti-Nestedness’’. A more profitable approach is to designate and test each distinct non-nested pattern according to its specific assumptions and mechanistic hypotheses.
