Self–organized instability in complex ecosystems

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application to both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they cannot be used to detect different mechanisms of community assembly. A solution is to search for more sensitive patterns, for example by extending the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but to date there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study SAD scaling using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to examine the relationship of $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$, however, had a better fit to data and allowed comparisons between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be interesting methods to study community or macroecological patterns.

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A new method to analyze species abundances in space using generalized dimensions

10.7287/peerj.preprints.745v3 ◽

2014 ◽

Author(s):

Leonardo A Saravia

Keyword(s):

Species Abundance ◽

Abundance Distribution ◽

Community Patterns ◽

Information Dimension ◽

Spatially Explicit Models ◽

Generalized Dimension ◽

Species Abundances ◽

Species Abundance Distributions ◽

Species Area ◽

Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study scaling of SAD using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to relate both $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$ had a better fit to data and a strong ability to compare between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be an interesting addition to study community or macroecological patterns.

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A new method to analyze species abundances in space using generalized dimensions

10.7287/peerj.preprints.745v1 ◽

2014 ◽

Author(s):

Leonardo A Saravia

Keyword(s):

Species Abundance ◽

Abundance Distribution ◽

Community Patterns ◽

Information Dimension ◽

Spatially Explicit Models ◽

Generalized Dimension ◽

Species Abundances ◽

Species Abundance Distributions ◽

Species Area ◽

Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study scaling of SAD using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to relate both $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$ had a better fit to data and a strong ability to compare between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be an interesting addition to study community or macroecological patterns.

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A new method to analyze species abundances in space using generalized dimensions

10.7287/peerj.preprints.745v5 ◽

2015 ◽

Author(s):

Leonardo A Saravia

Keyword(s):

Species Abundance ◽

Abundance Distribution ◽

Community Patterns ◽

Information Dimension ◽

Generalized Dimension ◽

Species Abundances ◽

Species Abundance Distributions ◽

Species Area ◽

Generalized Dimensions ◽

Relationship Of

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application to both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they cannot be used to detect different mechanisms of community assembly. A solution is to search for more sensitive patterns, for example by extending the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but to date there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study SAD scaling using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to examine the relationship of $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$, however, had a better fit to data and allowed comparisons between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be interesting methods to study community or macroecological patterns.

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Ecological-coenotic features of rare flora species of pine-oak stands of Volyn Polissya

Ukrainian Journal of Ecology ◽

10.15421/2020_9 ◽

2020 ◽

Vol 10 (1) ◽

pp. 55-61

Author(s):

S. O. Glinska ◽

S. S. Shtokalo ◽

D. V. Lyko ◽

Ya. V. Stepaniuk ◽

L. K. Savchuk

Keyword(s):

Endangered Species ◽

Rare Species ◽

Species Abundance ◽

Field Studies ◽

Asparagus Officinalis ◽

Natural Habitats ◽

Rare And Endangered Species ◽

Wild Fauna ◽

Rare And Endangered ◽

Epipactis Helleborine

Anthropogenic influence on the natural vegetation of Volyn Polissya threatens the existence of habitats of rare and endangered species of flora. Therefore, the region, unique in botanical and geographical terms, is gradually losing its specific vegetation characteristics. Having analyzed the literature data, herbarium data and materials of our own field studies in 2016-2019, we have compiled a list of rare and endangered species of pine-oak stands. In the habitat of pine-oak stands 89 rare species were found, 29 of which are listed in the Red Data Book of Ukraine, while Silene lithuanica is included in the European Red List. 3 species (Cypripedium calceolus, Trapa natans та Caldesia parnassifolia) are included into appendices of “The Convention on International Trade in Endangered Species of Wild Fauna and Flora”. 10 species are subject to protection according to the appendix of “Convention on the Conservation of European Wildlife and Natural Habitats” 56 species are regionally rare species for the flora of the Volyn region, 4 species are rare species of pine-oak stands. In our research we have analyzed the age range, density and recovery index for the species studied. The study found that for 63 rare species the dynamics of species abundance and distribution are satisfactory. The area of distribution and the number of 7 species is increasing: Allium ursinum, Galanthus nivalis, Platanthera chlorantha, Anemone sylvestris, Campanula persicifolia, Corydalis cava, Isopyrum thalictroides In the study area 14 species grow sporadically: Juniperus communis, Potentilla alba, Digitalis grandiflora, Gymnocarpium dryoptheris, Daphne mezereum, Neottia nidus-avis, Epipactis helleborine, Scorzonera purpurea, Asparagus officinalis, Iris sibirica, Adonis vernalis, Cephalanthera damasonium, Gentiana cruciate, Gentiana pneumonanthe. Dissemination information for Caldesia parnassifolia, Succisella inflexa, Genistella sagittalis, Salix myrtilloides, Ophioglossum vulgatum is insufficient for establishing species dynamics and needs further investigation. The conservation of pine-oak stands in Volyn Polissya will help to create the conditions for the growth of rare and endangered species of flora.

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A new method to analyze species abundances in space using generalized dimensions

10.7287/peerj.preprints.745v2 ◽

2014 ◽

Author(s):

Leonardo A Saravia

Keyword(s):

Species Abundance ◽

Abundance Distribution ◽

Community Patterns ◽

Information Dimension ◽

Spatially Explicit Models ◽

Generalized Dimension ◽

Species Abundances ◽

Species Abundance Distributions ◽

Species Area ◽

Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study scaling of SAD using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to relate both $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$ had a better fit to data and a strong ability to compare between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be an interesting addition to study community or macroecological patterns.

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Distribution of the native earthworm fauna of the Perth metropolitan sector of the Swan Coastal Plain

Pacific Conservation Biology ◽

10.1071/pc020196 ◽

2002 ◽

Vol 8 (3) ◽

pp. 196

Author(s):

Ian Abbott ◽

Allan Wills

Keyword(s):

Coastal Plain ◽

Native Species ◽

Species Abundance ◽

Common Species ◽

Habitat Diversity ◽

Remnant Vegetation ◽

Invertebrate Diversity ◽

Swan Coastal Plain ◽

Species Abundances ◽

Species Area

Assessment of areas suitable for inclusion in a comprehensive, adequate and representative (CAR) reserve system has been based primarily on distribution of original native vegetation and occurrence of vertebrates, particularly birds and mammals. However, reliable predictors of vertebrate and floristic diversity are not necessarily adequate predictors of invertebrate diversity. We sampled the earthworm fauna of the Perth metropolitan Swan Coastal Plain (SCP) to examine whether vegetation-based criteria are sufficient for identifying a conservation estate for native earthworms. Twenty-one native species were collected from 136 sample localities. All five previously described native species from the region and three native species previously collected but not formally described were again collected, while 13 previously uncollected species were found. Species abundances of native earthworms were uneven, in common with species-abundance relationships for many other invertebrate assemblages, with 10 singleton occurrences of species and few common species. Species diversity increased away from the coast across the sandy geomorphic units Quindalup, Spearwood and Bassendean. Our study did not resolve whether dlifferences in earthworm faunas reflect the gradient in soil qualities across these units, gradients in species-area effects, habitat diversity effects or a combination of these. Blocks of remnant vegetation identified in the Western Australian Government's Bush Forever plan as containing natural areas of regional conservation value are also likely to support at least one native earthworm species. However, many of the blocks of remnant vegetation so identified are not within the formal conservation estate. Two species identified in this survey fortuitously persist only in remnant vegetation patches not considered regionally significant. Actual regional diversity was estimated to be 38 native species, indicating many uncollected relatively rare species. Although earthworms are a low diversity group compared with other invertebrates, the localized distributions of most species indicate that the formal conservation estate does not provide adequate protection. Ongoing degradation of unprotected remnant vegetation will result in extinctions of localized invertebrate species.

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A new method to analyze species abundances in space using generalized dimensions

10.7287/peerj.preprints.745v4 ◽

2015 ◽

Author(s):

Leonardo A Saravia

Keyword(s):

Species Abundance ◽

Abundance Distribution ◽

Community Patterns ◽

Information Dimension ◽

Spatially Explicit Models ◽

Generalized Dimension ◽

Species Abundances ◽

Species Abundance Distributions ◽

Species Area ◽

Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study scaling of SAD using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to relate both $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$ had a better fit to data and a strong ability to compare between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be an interesting addition to study community or macroecological patterns.

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Duplex DNA barcoding allows accurate species determination of morphologically similar limpets (Patella spp.) from non-destructive sampling

Journal of the Marine Biological Association of the United Kingdom ◽

10.1017/s0025315416000813 ◽

2016 ◽

Vol 97 (7) ◽

pp. 1479-1482 ◽

Cited By ~ 1

Author(s):

Thomas J. Ashton ◽

Meriem Kayoueche-Reeve ◽

Andrew J. Blight ◽

Jon Moore ◽

David M. Paterson

Keyword(s):

Dna Barcoding ◽

Species Abundance ◽

Microscopic Analysis ◽

Cost Effective ◽

Field Studies ◽

Similar Species ◽

Species Determination ◽

Destructive Sampling ◽

Species Specific ◽

Non Destructive

Accurate discrimination of two morphologically similar species of Patella limpets has been facilitated by using qPCR amplification of species-specific mitochondrial genomic regions. Cost-effective and non-destructive sampling is achieved using a mucus swab and simple sample lysis and dilution to create a PCR template. Results show 100% concurrence with dissection and microscopic analysis, and the technique has been employed successfully in field studies. The use of highly sensitive DNA barcoding techniques such as this hold great potential for improving previously challenging field assessments of species abundance.

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The commonness of rarity: Global and future distribution of rarity across land plants

10.32942/osf.io/qfpa9 ◽

2019 ◽

Author(s):

Brian Joseph Enquist ◽

Xiao Feng ◽

Bradley Boyle ◽

Brian Maitner ◽

Erica A. Newman ◽

...

Keyword(s):

Plant Species ◽

Rare Species ◽

Large Fraction ◽

Neutral Theory ◽

Species Abundance ◽

Land Plant ◽

Observation Data ◽

Heavy Tailed Distributions ◽

Species Abundance Distributions ◽

Heavy Tailed

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant species observation data in order to quantify the fraction of Earth’s extant land plant biodiversity that is common versus rare. Tests of different hypotheses for the origin of species commonness and rarity indicates that sampling biases and prominent models such as niche theory and neutral theory cannot account for the observed prevalence of rare species. Instead, the distribution of commonness is best approximated by heavy-tailed distributions like the Pareto or Poisson-lognormal distributions. As a result, a large fraction, ~36.5% of an estimated ~435k total plant species, are exceedingly rare. We also show that rare species tend to cluster in a small number of ‘hotspots’ mainly characterized by being in tropical and subtropical mountains and areas that have experienced greater climate stability. Our results indicate that (i) non-neutral processes, likely associated with reduced risk of extinction, have maintained a large fraction of Earth’s plant species but that (ii) climate change and human impact appear to now and will disproportionately impact rare species. Together, these results point to a large fraction of Earth’s plant species are faced with increased chances of extinction. Our results indicate that global species abundance distributions have important implications for conservation planning in this era of rapid global change.

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