Stochastic species abundance models involving special copulas

2018 ◽  
Vol 490 ◽  
pp. 77-91 ◽  
Author(s):  
Thierry E. Huillet
Keyword(s):  
Species Abundance ◽  
Species Abundance Models

scholarly journals The fish community of the Sorocaba River Basin in different habitats (State of São Paulo, Brazil)

2009 ◽  
Vol 69 (4) ◽  
pp. 1015-1025 ◽  
Author(s):  
WS. Smith ◽  
M. Petrere Jr. ◽  
W. Barrella
Keyword(s):  
River Basin ◽  
Fish Assemblage ◽  
Standard Length ◽  
Fish Community ◽  
Species Abundance ◽  
Sao Paulo ◽  
Abundance Distribution ◽  
Abiotic Variables ◽  
Species Abundance Models ◽  
Dry And Rainy Seasons

A fish assemblage study was accomplished in different habitats of the Sorocaba River Basin. Fish were caught with gillnets, were weighed (weight total - g) and measured (standard length - mm). Several abiotic variables of selected sampling sites were measured in order to characterise their habitats in order to attempt establishing correlations with fish community traits. Fish numbers per species were adjusted to the lognormal and logseries species/abundance models The fish community totaled 38 species, distributed in 28 genera, 14 families and 4 orders. Diversity was calculated both in number and in weight and both presented higher values in better preserved sites. We did not detect any statistical differences between dry and rainy seasons. We also concluded that the abundance distribution was not influenced by abiotic variables.

Species abundance models and patterns in dragonfly communities: effects of fish predators

Oikos ◽  
2006 ◽  
Vol 114 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Frank Johansson ◽  
Göran Englund ◽  
Tomas Brodin ◽  
Hans Gardfjell
Keyword(s):  
Species Abundance ◽  
Fish Predators ◽  
Species Abundance Models

scholarly journals Towards combining occurrence and abundance distribution models of Great Bustard for conservation: A global research template from Bohai Bay?

2017 ◽  
Author(s):  
Chunrong Mi ◽  
Falk Huettmann ◽  
Rui Sun ◽  
Yumin Guo
Keyword(s):  
Species Abundance ◽  
Distribution Patterns ◽  
Bohai Bay ◽  
Abundance Distribution ◽  
Great Bustard ◽  
Distribution Models ◽  
A Priority ◽  
Species Abundance Models ◽  
Combine Information ◽  
Protection Index

Species distribution models (SDMs) have become important and essential tools in conservation and management. However, SDMs built with count data, commonly referred to as species abundance models (SAMs), are still less used so far. SDMs are increasingly used now in conservation decisions, whereas SAMs are still not widely employed. Species occurrence and abundance do not frequently display similar patterns, often they are not even well correlated. This leads to an insufficient or misleading conservation. How to combine information from SDMs and SAMs all together for unified conservation remains a challenge. In this study, we put forward for the first time a priority protection index (PI). The PI combines the prediction results of occurrence and abundance models. We used the best-available presence and count records for an endangered farmland species, Great Bustard (Otis tarda dybowskii) in Bohai Bay, China, as a case study. We then applied the advanced Random Forest algorithm (Salford Systems Ltd. implementation), a powerful machine learning method, with eleven predictor variables to forecast the spatial occurrence as well as the abundance distribution. The results show that the occurrence model had a decent performance (ROC: 0.77) and the abundance model had a RMSE 26.54. It is of note that environmental variables influenced bustard occurrence and abundance differently. We found that occurrence and abundance models display different spatial distribution patterns. Still, combining occurrence and abundance indices to produce a priority protection index (PI) used for conservation could guide the protection of the areas with high occurrence and high abundance (e.g. in Strategic Conservation Planning). Due to the widespread use of SDMs and the rel. easy subsequent employment of SAMs these findings have a wide relevance and applicability, worldwide. We promote and strongly encourage to further test, apply and update the priority protection index (PI) elsewhere in order to explore the generality of these findings and methods readily available now for researchers.

scholarly journals Testing species abundance models: a new bootstrap approach applied to Indo-Pacific coral reefs

Ecology ◽  
2009 ◽  
Vol 90 (11) ◽  
pp. 3138-3149 ◽  
Author(s):  
Sean R. Connolly ◽  
Maria Dornelas ◽  
David R. Bellwood ◽  
Terence P. Hughes
Keyword(s):  
Coral Reefs ◽  
Species Abundance ◽  
Bootstrap Approach ◽  
Species Abundance Models

scholarly journals Comments about some species abundance patterns: classic, neutral, and niche partitioning models

2008 ◽  
Vol 68 (4 suppl) ◽  
pp. 1003-1012 ◽  
Author(s):  
FC. Ferreira ◽  
M. Petrere-Jr.
Keyword(s):  
Niche Partitioning ◽  
Species Abundance ◽  
Experimental Tests ◽  
Biological Communities ◽  
Abundance Patterns ◽  
Logarithmic Series ◽  
Neutral Models ◽  
Log Normal ◽  
Species Abundance Models ◽  
Tokeshi Models

The literature on species abundance models is extensive and a great deal of new and important contributions have been published in the last three decades. Broadly speaking, one can recognize five families of species abundance models: i) purely statistical or classic models (Broken-stick, Log-normal, Logarithmic and Geometric series); ii) branching process (Zipf-Mandelbrot and Fractal branching models); iii) population dynamics (Neutral models included); iv) spatial distribution of individuals (Multifractal and HEAP models) and v) niche partitioning (Sugihara's breakage and Tokeshi models). Among these the neutral, the classic and the niche partitioning models have been the most applied to natural communities, the former having been more extensively discussed than the others in the last years. The objective of this paper is to comment some aspects of the classic, neutral and niche partitioning models in a way that the proposed distributions may contribute to the analysis of the empirical patterns of species abundance. In spite of the variety of models, the distributions in general vary between the log-normal and the logarithmic series. From these models the Power-Fraction, together with independent niche dimensions measures, are amenable to experimental tests and may offer answers on which resources are important in the structuring of biological communities.

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