scholarly journals Efficient algorithms for sampling feasible sets of abundance distributions

2014 ◽  
Author(s):  
Kenneth J. Locey ◽  
Daniel J. McGlinn
Keyword(s):  
Species Abundance ◽  
Discrete Distributions ◽  
Ecological Communities ◽  
Feasible Set ◽  
As Species ◽  
Random Samples ◽  
Ecological Patterns ◽  
Feasible Sets ◽  
Sampling Algorithms ◽  
Zero Values

Ecological variables such as species richness (S) and total abundance (N) can strongly influence ecological patterns. For example, the general form of the species abundance distribution (SAD) can often be explained by the majority of possible forms having the same N and S, i.e. the SAD feasible set. The feasible set reveals how variables determine observable variation, whether empirical patterns are exceptional to the majority of possible forms, and provides a constraint-based explanation for the ubiquity of hollow-curve SADs in nature. However, use of the feasible set has been limited to inefficient sampling algorithms that prevent large ecological communities and ecologically realistic combinations of N and S from being examined. This is the primary hindrance to using this otherwise novel perspective and theoretical framework. We developed efficient computational algorithms to generate random samples of the feasible set for the SAD and similar discrete distributions of abundance, including those that allow for zero-values, e.g., absences. We provide Python and R based implementations of our algorithms and tools for testing and using them. Our algorithms are often several orders of magnitude faster than a long-standing and recently used approach. This greatly increases the size and diversity of communities that can be examined with the feasible set approach and thus advances progress using constraint-based approaches to decipher ecological patterns.

scholarly journals Efficient algorithms for sampling feasible sets of abundance distributions

2014 ◽  
Author(s):  
Kenneth J. Locey ◽  
Daniel J. McGlinn
Keyword(s):  
Species Abundance ◽  
Discrete Distributions ◽  
Ecological Communities ◽  
Feasible Set ◽  
As Species ◽  
Random Samples ◽  
Ecological Patterns ◽  
Feasible Sets ◽  
Sampling Algorithms ◽  
Zero Values

Ecological variables such as species richness (S) and total abundance (N) can strongly influence ecological patterns. For example, the general form of the species abundance distribution (SAD) can often be explained by the majority of possible forms having the same N and S, i.e. the SAD feasible set. The feasible set reveals how variables determine observable variation, whether empirical patterns are exceptional to the majority of possible forms, and provides a constraint-based explanation for the ubiquity of hollow-curve SADs in nature. However, use of the feasible set has been limited to inefficient sampling algorithms that prevent large ecological communities and ecologically realistic combinations of N and S from being examined. This is the primary hindrance to using this otherwise novel perspective and theoretical framework. We developed efficient computational algorithms to generate random samples of the feasible set for the SAD and similar discrete distributions of abundance, including those that allow for zero-values, e.g., absences. We provide Python and R based implementations of our algorithms and tools for testing and using them. Our algorithms are often several orders of magnitude faster than a long-standing and recently used approach. This greatly increases the size and diversity of communities that can be examined with the feasible set approach and thus advances progress using constraint-based approaches to decipher ecological patterns.

scholarly journals Efficient algorithms for sampling feasible sets of macroecological patterns

2013 ◽  
Author(s):  
Kenneth J. Locey ◽  
Daniel J. McGlinn
Keyword(s):  
Species Abundance ◽  
Previous Method ◽  
Species Abundance Distribution ◽  
Abundance Distribution ◽  
Feasible Set ◽  
As Species ◽  
Random Samples ◽  
Feasible Sets ◽  
Sampling Algorithms ◽  
New Algorithms

Ecological variables such as species richness (S) and total abundance (N) can strongly influence the forms of macroecological patterns. For example, the majority of variation in the species abundance distribution (SAD) can often be explained by the majority of possible forms having the same N and S, i.e. the feasible set. The feasible set reveals how variables such as N and S determine observable variation and whether empirical patterns are exceptional to the majority of possible forms. However, this approach has currently only been applied to the SAD using relatively inefficient random sampling algorithms. We extend the use of the feasible set approach by developing new algorithms to efficiently generate random samples of the feasible set for the SAD and the intraspecific spatial abundance distribution (SSAD). These algorithms are often several orders of magnitude faster than a previous method, which greatly increases the size and diversity of communities that can be examined.

scholarly journals The prevalence and impact of transient species in ecological communities

2017 ◽  
Author(s):  
Sara Snell ◽  
Brian S. Evans ◽  
Ethan P. White ◽  
Allen H. Hurlbert
Keyword(s):  
Spatial Scales ◽  
Species Abundance ◽  
Careful Consideration ◽  
Ecological Communities ◽  
Transient Species ◽  
Ecological Patterns ◽  
Species Abundance Distributions ◽  
Species Area ◽  
Using Data ◽  
Taxonomic Groups

AbstractTransient species occur infrequently in a community over time and do not maintain viable local populations. Because transient species interact differently than non-transients with their biotic and abiotic environment, it is important to characterize the prevalence of these species and how they impact our understanding of ecological systems. We quantified the prevalence and impact of transient species in communities using data on over 17,000 community time series spanning an array of ecosystems, taxonomic groups, and spatial scales. We found that transient species are a general feature of communities regardless of taxa or ecosystem. The proportion of these species decreases with spatial scale leading to a need to control for scale in comparative work. Removing transient species from analyses influences the form of a suite of commonly studied ecological patterns including species-abundance distributions, species-energy relationships, species-area relationships, and temporal turnover. Careful consideration should be given to whether transient species are included in analyses depending on the theoretical and practical relevance of these species for the question being studied.

scholarly journals Inferring True Species Richness and Complete Abundance Distribution in Six Reef-fish Communities from Red-sea, Using the Numerical Extrapolation of Incomplete Samplings

2019 ◽  
pp. 1-21
Author(s):  
Jean Beguinot
Keyword(s):  
Reef Fish ◽  
Red Sea ◽  
Field Data ◽  
Full Range ◽  
Species Abundance ◽  
Fish Communities ◽  
Ecological Communities ◽  
Abundance Distribution ◽  
Internal Organization ◽  
Unrecorded Species

Even when ecological communities are incompletely sampled (which is most frequent in practice, at least for species-rich assemblages including many rare species), it remains possible to retrieve much more information than could be expected first, by applying numerical extrapolation to incomplete field data. Indeed, recently developed procedures of numerical extrapolation of partial samplings now allow to estimate, with fair accuracy, not only the number of the still unrecorded species but, moreover, the distribution of abundances of each of these unrecorded species, thereby making available the full range of the Species Abundance Distribution, despite dealing with incomplete data only. In turn, this allows to address a series of descriptive and functional aspects of the internal organization of species assemblages, which otherwise would have required disposing of truly exhaustive samplings. This approach is applied, here, to the previously reported partial samplings of six neighboring reef-fish communities from Tiran Island, Red Sea, with the goal of better understanding their internal organization in relation to their respective environments. In practice, the numerical completion contributes to avoid erroneous interpretations that would likely stem from considering only the incomplete field data. This point is especially relevant when studying reef-associated communities because accurate understanding of their organization will help guiding and refining at best the protective measures required by these particularly vulnerable communities.

Community Ecology

Ecology ◽  
2012 ◽  
Author(s):  
Herman A. Verhoef
Keyword(s):  
Community Ecology ◽  
Evolutionary Biology ◽  
Environmental Gradients ◽  
Functional Integration ◽  
Species Abundance ◽  
Functional Trait ◽  
Individual Species ◽  
Global Changes ◽  
Ecological Communities ◽  
Early 21St Century

At the beginning of the 20th century there was much debate about the “nature” of communities. The driving question was whether the community was a self-organized system of co-occurring species or simply a haphazard collection of populations with minimal functional integration. At that time, two extreme views dominated the discussion: one view considered a community as a superorganism, the member species of which were tightly bound together by interactions that contributed to repeatable patterns of species abundance in space and time. This concept led to the assumption that communities are fundamental entities, to be classified as the Linnaean taxonomy of species. Frederick E. Clements was one of the leading proponents of this approach, and his view became known as the organismic concept of communities. This assumes a common evolutionary history for the integrated species. The opposite view was the individualistic continuum concept, advocated by H. A. Gleason. His focus was on the traits of individual species that allow each to live within specific habitats or geographical ranges. In this view a community is an assemblage of populations of different species whose traits allow persisting in a prescribed area. The spatial boundaries are not sharp, and the species composition can change considerably. Consequently, it was discussed whether ecological communities were sufficiently coherent entities to be considered appropriate study objects. Later, consensus was reached: that properties of communities are of central interest in ecology, regardless of their integrity and coherence. From the 1950s and 1960s onward, the discussion was dominated by the deterministic outcome of local interactions between species and their environments and the building of this into models of communities. This approach, indicated as “traditional community ecology,” led to a morass of theoretical models, without being able to provide general principles about many-species communities. Early-21st-century approaches to bringing general patterns into community ecology concern (1) the metacommunity approach, (2) the functional trait approach, (3) evolutionary community ecology, and (4) the four fundamental processes. The metacommunity approach implicitly recognizes and studies the important role of spatiotemporal dynamics. In the functional trait approach, four themes are focused upon: traits, environmental gradients, the interaction milieu, and performance currencies. This functional, trait-focused approach should have a better prospect of understanding the effects of global changes. Evolutionary community ecology is an approach in which the combination of community ecology and evolutionary biology will lead to a better understanding of the complexity of communities and populations. The four fundamental processes are selection, drift, speciation, and dispersal. This approach concerns an organizational scheme for community ecology, based on these four processes to describe all existing specific models and frameworks, in order to make general statements about process–pattern connections.

scholarly journals On stability and stationary points in nonlinear optimization

1986 ◽  
Vol 28 (1) ◽  
pp. 36-56 ◽  
Author(s):  
J. Guddat ◽  
H. Th. Jongen ◽  
J. Rueckmann
Keyword(s):  
Stability Condition ◽  
Minimization Problem ◽  
Level Sets ◽  
Constraint Qualification ◽  
Stationary Points ◽  
Feasible Set ◽  
Manifold With Boundary ◽  
Feasible Sets ◽  
Constrained Minimization Problem ◽  
Image Position

This paper presents three theorems concerning stability and stationary points of the constrained minimization problem:In summary, we provethat, given the Mangasarian-Fromovitz constraint qualification (MFCQ), the feasible setM[H, G] is a topological manifold with boundary, with specified dimension; (ℬ) a compact feasible setM[H, G] is stable (perturbations ofHandGproduce homeomorphic feasible sets) if and only if MFCQ holds;under a stability condition, two lower level sets offwith a Kuhn-Tucker point between them are homotopically related by attachment of ak-cell (kbeing the stationary index in the sense of Kojima).

Phytophthora cinnamomi and Australia's biodiversity: impacts, predictions and progress towards control

2008 ◽  
Vol 56 (4) ◽  
pp. 279 ◽  
Author(s):  
David M. Cahill ◽  
James E. Rookes ◽  
Barbara A. Wilson ◽  
Lesley Gibson ◽  
Keith L. McDougall
Keyword(s):  
Management Practices ◽  
Phytophthora Cinnamomi ◽  
Species Abundance ◽  
Ecological Communities ◽  
Complete Control ◽  
Natural Systems ◽  
Limited Effectiveness ◽  
Federal Initiatives ◽  
Serious Disease ◽  
Made In

Phytophthora cinnamomi continues to cause devastating disease in Australian native vegetation and consequently the disease is listed by the Federal Government as a process that is threatening Australia’s biodiversity. Although several advances have been made in our understanding of how this soil-borne pathogen interacts with plants and of how we may tackle it in natural systems, our ability to control the disease is limited. The pathogen occurs widely across Australia but the severity of its impact is most evident within ecological communities of the south-west and south-east of the country. A regional impact summary for all states and territories shows the pathogen to be the cause of serious disease in numerous species, a significant number of which are rare and threatened. Many genera of endemic taxa have a high proportion of susceptible species including the iconic genera Banksia, Epacris and Xanthorrhoea. Long-term studies in Victoria have shown limited but probably unsustainable recovery of susceptible vegetation, given current management practices. Management of the disease in conservation reserves is reliant on hygiene, the use of chemicals and restriction of access, and has had only limited effectiveness and not provided complete control. The deleterious impacts of the disease on faunal habitat are reasonably well documented and demonstrate loss of individual animal species and changes in population structure and species abundance. Few plant species are known to be resistant to P. cinnamomi; however, investigations over several years have discovered the mechanisms by which some plants are able to survive infection, including the activation of defence-related genes and signalling pathways, the reinforcement of cell walls and accumulation of toxic metabolites. Manipulation of resistance and resistance-related mechanisms may provide avenues for protection against disease in otherwise susceptible species. Despite the advances made in Phytophthora research in Australia during the past 40 years, there is still much to be done to give land managers the resources to combat this disease. Recent State and Federal initiatives offer the prospect of a growing and broader awareness of the disease and its associated impacts. However, awareness must be translated into action as time is running out for the large number of susceptible, and potentially susceptible, species within vulnerable Australian ecological communities.

scholarly journals Pleistocene megafaunal interaction networks became more vulnerable after human arrival

2015 ◽  
Vol 282 (1814) ◽  
pp. 20151367 ◽  
Author(s):  
Mathias M. Pires ◽  
Paul L. Koch ◽  
Richard A. Fariña ◽  
Marcus A. M. de Aguiar ◽  
Sérgio F. dos Reis ◽  
...  
Keyword(s):  
Structural Changes ◽  
Ecological Communities ◽  
Ecological Interactions ◽  
Ecological Data ◽  
The Past ◽  
As Species ◽  
Extinction Events ◽  
Almost All ◽  
The Impact ◽  
Unstable Dynamics

The end of the Pleistocene was marked by the extinction of almost all large land mammals worldwide except in Africa. Although the debate on Pleistocene extinctions has focused on the roles of climate change and humans, the impact of perturbations depends on properties of ecological communities, such as species composition and the organization of ecological interactions. Here, we combined palaeoecological and ecological data, food-web models and community stability analysis to investigate if differences between Pleistocene and modern mammalian assemblages help us understand why the megafauna died out in the Americas while persisting in Africa. We show Pleistocene and modern assemblages share similar network topology, but differences in richness and body size distributions made Pleistocene communities significantly more vulnerable to the effects of human arrival. The structural changes promoted by humans in Pleistocene networks would have increased the likelihood of unstable dynamics, which may favour extinction cascades in communities facing extrinsic perturbations. Our findings suggest that the basic aspects of the organization of ecological communities may have played an important role in major extinction events in the past. Knowledge of community-level properties and their consequences to dynamics may be critical to understand past and future extinctions.

scholarly journals The concerted emergence of well-known spatial and temporal ecological patterns in an evolutionary food web model in space

2019 ◽  
Author(s):  
Michaela Hamm ◽  
Barbara Drossel
Keyword(s):  
Food Web ◽  
Trophic Position ◽  
Species Abundance ◽  
Trophic Levels ◽  
Geographic Ranges ◽  
Space And Time ◽  
Spatially Extended ◽  
Ecological Patterns ◽  
Species Abundance Distributions ◽  
Food Web Model

ABSTRACTEcological systems show a variety of characteristic patterns of biodiversity in space and time. It is a challenge for theory to find models that can reproduce and explain the observed patterns. Since the advent of island biogeography these models revolve around speciation, dispersal, and extinction, but they usually neglect trophic structure. Here, we propose and study a spatially extended evolutionary food web model that allows us to study large spatial systems with several trophic layers. Our computer simulations show that the model gives rise simultaneously to several biodiversity patterns in space and time, from species abundance distributions to the waxing and waning of geographic ranges. We find that trophic position in the network plays a crucial role when it comes to the time evolution of range sizes, because the trophic context restricts the occurrence and survival of species especially on higher trophic levels.

scholarly journals A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities

2020 ◽  
Author(s):  
Isaac Overcast ◽  
Megan Ruffley ◽  
James Rosindell ◽  
Luke Harmon ◽  
Paulo A. V. Borges ◽  
...  
Keyword(s):  
Community Assembly ◽  
Island Biogeography ◽  
Spatial Scales ◽  
Mechanistic Model ◽  
Species Abundance ◽  
Real Data ◽  
Current Theory ◽  
Supervised Machine Learning ◽  
Ecological Communities ◽  
Trait Variation

AbstractBiodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Reconciling the relative importance of these processes is hindered by current theory, which tends to focus on a single spatial, temporal or taxonomic scale. We introduce a mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. We demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. We combine our massive eco-evolutionary synthesis simulations (MESS) with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of spatial scales.

Sign in / Sign up

Export Citation Format

Share Document