, Pages 222-229
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Intricacy of biotic interactions (predator-prey relationship, strength of food web links and other type of intra- and inter-specific relationships), as well as shifts in species functions in ecosystems, could affect the accuracy of predictions derived from the theory of redundancy of species, when applied to ecosystems assessment.
This opinion paper is based on three main considerations: 1) some fundamental differences between ecological and engineering definition of “redundancy”, underlying the main concerns related to the use frameworks derived from economical or engineering disciplines, as the ecosystems services paradigm; 2) presence of empirical obstacles to establish whether two different species are fully or partially redundant. When species redundancy in a particular community is estimated using a matrix with species-specific functional traits, often forgetting potential biotic interactions not directly related to the trophic chains or neglecting the variability in strengths of the links connecting these species; and 3) recent evidence offered by studies that shed doubts on the validity of the ecological redundancy hypothesis.
Finally, we claim that more attention must to be paid to intrinsic ecological aspects of ecosystem components (per se values rather than derived values), and a precautionary principle is necessary for decisions related to the assessment of ecosystems.
Ecological complexity: not only a question of numbers
In this note, we underline some issues related to the use (and abuse) of a framework derived from disciplines such as economics or engineering, in ecological studies. We highlight how the complexity of biotic interactions could make the predictions derived from the theory of redundancy less effective (Walker, 1992), when applied to ecosystem assessment. We claim that more attention must to be paid to the intrinsic ecological aspects of ecosystem components (per se values rather than derived
Diversity and ecosystems stability: persistence, resistance and resilience
The relationship between diversity and stability of ecosystems has fascinated ecologists for many years (Borrelli et al., 2015, McCann, 2000, Namba, 2015, Schleuning et al., 2015). The diversity-stability-hypothesis has a long history from its initial proposition (Elton, 1958, MacArthur, 1955, Odum, 1953), with a temporary disappearance of consensus (May, 1973), to more recent evidence suggesting that diversity begets stability (Kinzig et al., 2002, McCann, 2000). Currently, more evidence
Ecological redundancy: is there an “insurance” for ecosystem services?
In ecosystem assessments, ecological redundancy is defined as functional compensation due to different drivers (species or organism) performing similar functions in an ecosystem (Walker, 1992). In this way, particular species can cause aggregate stability in an ecosystem, enhancing ecosystem “resilience”. In a given assemblage, the loss of a few ecologically unique species is expected to have a larger ecological impact than the loss of species sharing very similar functional traits (
Are species replaceable like gears?
Some researchers recently focused on the relationships between functional redundancy and functional diversity, developing several indices useful for studying communities (de Bello et al., 2007, Petchey et al., 2007). The functional diversity within each species assemblage is assessed based on the functional traits of the species present and the combination of functional traits values in the community (Maire et al., 2015, Petchey and Gaston, 2006). The same species traits are the elements used
Engineering redundancy vs. ecological redundancy: so close, so far away
Some recent studies showed how living organisms and life in general can be conceived as an integrated information processing system (Farnsworth et al., 2013). Traditionally, biotic systems are considered more complex than abiotic counterpart, with more predictable interactions among components. However, also engineered − or abiotic − systems could become complex. Some researchers argue that the critical difference between abiotic complex systems and biotic ones is the phenomenon of downward
In summary, a limited approach, as suggested by the assessment of species redundancy focusing only on species traits or function traits (currently the most used approach), neglecting or minimizing the importance of interaction strengths in food webs, multiple-interactions (Møller, 2008) or even other types of biotic interactions, can constitute further evidence of a too anthropocentric approach (science is made by humans, after all), but capable of distorting the vision or paradigm on which
We thank A. P. Møller, M. Moretti, Y. Benedetti and L. Brotons for their valuable contributions during the writing of this manuscript. We are also grateful to J. Kolasa and the anonymous reviewers for their important suggestions, that were very useful in order to clarify difficult concepts. Finally, we are very grateful to the prof. Emma Nelson, University of Liverpool, for the final English proof reading service.
- G. Bogliani et al.
Woodpigeons nesting in association with hobby falcons: advantages and choice rules
- C. Bondavalli et al.
How interaction strength affects the role of functional and redundant connections in food webs
- J.J. Borrelli et al.
Selection on stability across ecological scales
Trends Ecol. Evol.
- C.P. Carmona et al.
Traits without borders: integrating functional diversity across scales
Trends Ecol. Evol.
- R.S. De Groot et al.
A typology for the classification, description and valuation of ecosystem functions
Goods Serv. Ecol. Econ.
- K.D. Farnsworth et al.
Functional complexity: the source of value in biodiversity
- C. Gascon et al.
The importance and benefits of species
- J. Kolasa
Complexity, system integration, and susceptibility to change: biodiversity connection
- L.M.O. Laureto et al.
Functional diversity: an overview of its history and applicability
Nat. e Conserv.
- F. Morelli et al.
Associations between species can influence the goodness of fit of species distribution models: the case of two passerine birds
Failure prediction of dotcom companies using neural network-genetic programming hybrids
Inf. Sci. (Ny)
What do we mean by biological complexity?
C. R. Biol.
Threshold models in restoration and conservation: a developing framework
Trends Ecol. Evol.
Social-ecological resilience to coastal disasters
Stability criteria for complex ecosystems
The stability complexity relationship at age 40: a random matrix perspective
Food web stability and weighted connectance: the complexity-stability debate revisited
Hierarchical organization via a facilitation cascade in intertidal cordgrass bed communities
East versus West: contrasts in phenological patterns?
Glob. Ecol. Biogeogr.
Top-down causation by information control: from a philosophical problem to a scientific research programme
J. R. Soc. Interface
Phys. Rev. A
The effect of range changes on the functional turnover, structure and diversity of bird assemblages under future climate scenarios
Glob. Chang. Biol.
Front. Ecol. Environ.
Toward principles for enhancing the resilience of ecosystem services
Annu. Rev. Environ. Resour.
Linking multidimensional functional diversity to quantitative methods: a graphical hypothesis-evaluation framework
Taxonomical and functional diversity turnover in Mediterranean grasslands: interactions between grazing, habitat type and rainfall
J. Appl. Ecol.
Science for managing ecosystem services: beyond the millennium ecosystem assessment
Proc. Natl. Acad. Sci. U. S. A.
More of the same: high functional redundancy in stream fish assemblages from tropical agroecosystems
Hutchinson’s duality: the once and future niche
Proc. Natl. Acad. Sci. U. S. A.
Units of nature or processes across scales? The ecosystem concept at age 75
The epigenome and top-down causation
Importance of species abundance for assessment of trait composition: an example based on pollinator communities
The partitioning of diversity: showing Theseus a way out of the labyrinth
J. Veg. Sci.
Ecosystem consequences of species richness and composition in pond food webs
The functional role of biodiversity in ecosystems: incorporating trophic complexity
The dimensionality of ecological networks
Top-down causation and emergence: some comments on mechanisms
The Ecology of Invasions by Animals and Plants
Living is information processing: from molecules to global systems
Resilience thinking: integrating resilience, adaptability and transformability
Species functional redundancy, random extinctions and the stability of ecosystems
Multiple functions increase the importance of biodiversity for overall ecosystem functioning
Intraguild predation reduces redundancy of predator species in multiple predator assemblage
J. Anim. Ecol.
Panarchy: Understanding Transformations in Human and Natural Systems
Biotic interactions improve prediction of boreal bird distributions at macro-scales
Glob. Ecol. Biogeogr.
Command and control and the pathology of natural resource management
Resilience and stability of ecological systems
Annu. Rev. Ecol. Syst.
Engineering resilience versus ecological resilience
Settling decisions and heterospecific social information use in shrikes
Fungal genetic biodiversity and metabolic activity as an indicator of potential biological weathering and soil formation – Case study of towards a better understanding of Earth system dynamics
2022, Ecological Indicators
Citation Excerpt :
However, biodiversity characterisation that takes into account only taxonomic aspects based on molecular data (e.g. 16S rRNA for bacteria and ITS for fungi) as a measure of soil biota structure and stability is under discussion (Ros et al., 2008; Grządziel and Gałązka, 2019). On the basis of the ecological hypothesis of redundancy (redundant hypothesis), which has existed for many years, a new one is being built, investigating functional groups (a group of organisms that performs the same function in the ecosystem), rather than species, which play an important role in the functioning of the ecosystems (Morelli and Tryjanowski, 2016). Therefore, we aim to use metagenomics (NGS) and metabolic analysis (e.g. with the use of Biolog FFPlates) simultaneously to examine plant performance parameters and ecosystem functions, which should allow verification of hypotheses based on the identification of fungi and evaluation of their functional activity.
Terrestrial plants act as ecosystem engineers modifying the flow of energy and matter and creating new habitats for other organisms. This vital concept also encompasses plants' effects on landforms and soils, crucial components of forested landscapes worldwide. In the present study, we investigate how trees through their roots and symbiotic organisms influence soil-weathering processes. The aim of the study was to answer one of the big questions in Earth sciences: how do biological agents, including fungi, acting at the critical interface between the biosphere and the abiotic environment, shape soil and landscape evolution? Within the present study we ask what is the level of fungal activity within root systems of trees and how can it influence biological weathering. The area of interest is in the Poprad River gorge in the southern part of the Sącz Beskidy Mountains, the Outer Western Carpathians. We applied the following analyses: 1) determination of the structural diversity of fungi (ITS1) and 2) assessment of the metabolic profile of soils (Biolog FFPlates). The highest average number of classified genera were fungi which simultaneously carried out pathotrophic, saprotrophic and symbiotrophic functions. Boletales, Agaricales, Cantharellales and Archaeorhizomycetales were the most abundant orders, but in one sample we also found a particularly high proportion of the order Mortierellales. The order Boletales and its family Boletaceae were significantly enriched in rock crack samples, whereas the highest number of differentially abundant taxa was observed in reference samples. The most frequently utilised substrates by fungi were: glycyl-L-glutamic acids, L-ornithine, L-phenylalanine, L-proline, D-galacturonic acid, fumaric acids, D-saccharic acids, succinic acids and N-acetyl-D-glucosamine. Our study demonstrates that the fungal community in the root zone is geochemically active and the organic acids secreted by plant roots in oligotrophic conditions and nutrient limitations significantly affect soil weathering.
Ecological state evaluation of lake ecosystems revisited: Latent variables with kSVM algorithm approach for assessment automatization and data comprehension
2021, Ecological Indicators
Citation Excerpt :
One of the main goals for ecological status assessment is the intercalibration of classification models for the sake of common lake management objectives (Birk et al., 2013a, 2013b; Poikane et al., 2014; Søndergaard et al., 2016). However, according to some researchers, obstacles towards achieving consistent classification methods can lie in data quality, the uncertainty indicators, temporal variations (year-to-year variability), and data redundancy in the ecological assessment of water ecosystems (Baho et al., 2015; Kelly et al., 2016; Morelli and Tryjanowski, 2016). These shortcomings negatively affect the achievement of the necessary compromise between science and management (Navarro et al., 2009).
Automated and reproducible methodology for assessing the ecological condition of lakes is essential for effective monitoring and facilitating the decision-making process aimed at achieving the stated environmental goals. At the same time, multidimensional measurement datasets are often an obstacle to drawing insightful conclusions, thus becoming an incentive for overly simplified analyzes. In this article, a set of measurements and ecological status assessment results for a collection of 499 lakes in Poland was used. Expert assessment process was recreated using the supervised kernel Support Vector Machine algorithm on dataset with reduced dimensionality, thus a model that automates the ecological assessment process was obtained. The use of the explanatory skill of latent variables made it possible to present the assessed objects along with their position in individual classes. The visualization of the results in reduced dimensionality increased, without interfering with the size of the classes, the informative evaluation potential, which should be considered as an acompanying assessment parameter in the future. The primary target of this paper is the ecological expert coping with automatization of assessment process and obtaining latent information for sense-making visual comprehension during consultations regarding ecosystem-oriented ecological decision making.
Advancing approaches for understanding the nature-people link
2020, Ecological Complexity
Citation Excerpt :
Ecosystem complexity is a consequence of diversity and strength of interactions between ecosystem components often involving multiple scales of space and time. Ecosystem complexity, although an inherent attribute of ecosystems multifunctionality, often limits our ability to understand ecosystem dynamics (Kolasa 2005; Morelli & Tryjanowski 2016; Dakos & Soler-Toscano 2017). Several methods have been developed to quantify ecosystem multifunctionality, including a single function approach, a turnover approach, an averaging approach, a threshold (or multiple thresholds) approach and a multivariate diversity-interaction framework (Byrnes et al. 2014; Gamfeldt & Roger 2017; Manning et al. 2018).
Acknowledging complexity within relationships between fundamental ecology and societal research is critical in improving our current understanding of how natural ecosystems work and how they could be managed to achieve set management goals. Specifically, this challenge is linked to the multifunctional nature of ecosystems. We develop the Bayesian Belief Multifunctionality Framework to studying nature-people links that allows a holistic and transparent analysis of the relationships between species, their functional traits, multiple ecosystem functions and multiple nature's contributions to people (NCPs). We assess seven ecosystem functions common in marine soft-sediments (secondary production, metal sequestration, denitrification, N-release, sediment stability, primary production and sediment formation) and nine NCPs (food and feed, supporting services, climate regulation, regulation of coastal water quality, physical and psychological experience, habitat creation, learning, materials and erosion control). We use a case study based on an extensive and diverse intertidal sandflat macrofaunal community within Kaipara Harbour, New Zealand. By testing different scenarios in which we identify the set of traits responsible for the highest function performance for every function, we show that functional redundancy (i.e., the presence of multiple species that deliver the maximum performance for a specific function) was high for some functions but low for others. In our model, functional redundancy was the lowest for denitrification and secondary production, while primary production exhibited high functional redundancy. The network analysis also allowed us to gain insight into functional synergies and trade-offs, resulting from maximising individual function to a trait set. The trait set that maximised secondary production contributes to higher sediment stability; the trait set that maximised metal sequestration contributes to higher N-release; and the trait set that maximised denitrification contributes to high rates of metal sequestration and N-release. Negative effects were also apparent, e.g., the trait set that maximised metal sequestration resulted in a lower probability in sediment stability and secondary production. Finally, the scenario testing feature of the framework allowed for exploration of the changes in NCPs from changes in macrofauna density. High density of species with a trait set identified as important to individual functions generated an increase in the provision of the majority of considered NCPs. Thanks to its clear and transparent result presentation and flexible analysis, the BN Multifunctionality Framework can deliver insightful messages into multifunctionality links helping to reveal the multifunctional nature of diverse and complex natural ecosystems.
Combining the potential resilience of avian communities with climate change scenarios to identify areas of conservation concern
2020, Ecological Indicators
Citation Excerpt :
We are convinced that any index or measure developed to quantify the hypothetical resilience of a given ecosystem or species assemblage needs to be handled cautiously. Ecological resilience is a very complex and multifaceted concept, still debated in science, and far different from mechanical resilience (Cumming et al., 2005; Morelli and Tryjanowski, 2016; Spears et al., 2015). For this reason, it is so difficult to identify a reliable surrogate for this term.
This study aimed to investigate the match between breeding bird communities’ potential resilience and projections of climate change in Europe.
Here we identified European regions with the most substantial projected impacts of climate change based on Δ temperature and Δ precipitation in the next 60years, assessing the overlap with maps of potential bird community resilience. We combined data on the number of species and functional redundancy of avian communities, to calculate an index of potential community resilience. Finally, combining these three layers of information, we obtained unique large-scale evidence of differences in potential conservation threats in the continent. Approximately 3% of the continent could be exposed to a maximum risk of conservation concern (areas characterized by more significant changes in precipitation and temperatures and simultaneously by avian communities with the lower functional redundancy) by 2070, with a 31% exposed to high risks, and 23% of the continent facing potentially moderate risk.
Our findings provide important information on the potential capacity of European breeding bird communities to reduce the negative impact of changes in climate (temperature and precipitation), as well as identifying those regions potentially facing higher conservation risks (e.g. Southern part of Western Europe and the Ural Mountains in Russia).
The Holy Grail is just a myth! Response to Haest 2019
2019, Ecological Indicators
Assessment of ecosystem functioning from space: Advancements in the Habitats Directive implementation
2018, Ecological Indicators
Citation Excerpt :
Additionally, habitat dynamism over time offers multiple possibilities for conservation status monitoring by analysing the trajectory of the centroids. If we consider the centroid to be representative of the average functional behaviour of habitat patches, the analysis of their movements, trajectories and attractors (Morelli and Tryjanowski, 2016) may provide new metrics for assessing and monitoring conservation status. When the centroids were observed in a sequence generated as a movie by integrating one chart per year (see Videos 1a, 1b and 1c in the Supplementary material), the direction of movement and distances covered were different in the three habitats analysed.
The Habitats Directive (HD) and the Natura 2000 network establish a common framework for maintaining European natural habitats in a favourable conservation status and represent the main instrument used by conservation decision makers in the European Union. Habitat conservation status depends on the sum of the influences acting upon the habitat and its typical species that may affect its long-term natural distribution, structure and functions. Thus, ecosystem functioning is influenced by the diversity, number and functional traits of the species occurring in a habitat. Although the HD establishes that representative species should be selected to reflect favourable structure and functioning of the habitat type, it would not be realistic to associate species with all aspects of structure and functioning given the variability of Annex I habitats. This constraint led us to seek new approaches that allow a more direct assessment of the ecosystem functioning for natural habitats in space and time. We propose a remote sensing-based approach to characterize and assess the ecosystem functioning of habitats. As a case study, we applied our approach to three Mediterranean natural habitat types from the Iberian Peninsula included in Annex I of the Habitats Directive, i.e., Mediterranean sclerophyllous forest, Mediterranean deciduous forest and Sub-Mediterranean and temperate scrub. First, we estimated two key descriptors of ecosystem functioning derived from the Enhanced Vegetation Index and related them to primary production dynamics by using satellite images captured by the MODIS sensor for each year between 2001 and 2012. Second, we arranged these functional descriptors in two-dimensional space and calculated the distances from the habitats assessed to the reference sites, i.e., habitat patches that showed an optimal conservation status of composition and structure. Then, the distances were averaged over the period, and the habitats were categorized according to their mean distances as favourable or unfavourable-inadequate or unfavourable-bad, as outlined in the reporting guidelines under Article 17 of the Directive. Our approach provides new procedures to assess ecosystem functions across space and time, while complying with reporting obligations derived from the HD.
Stability, sensitivity and uncertainty rates in the flow equations of ecological models
Ecological Complexity, Volume 28, 2016, pp. 62-68
In previous work by the authors about dynamic system modeling, basic ecosystems concepts and their application to ecological modeling theory were formalized. Measuring how a variable effects certain processes leads to improvements in dynamic systems modelling and facilitates the author’s study of system diversity in which model sensitivity is a key theme. Initially, some variables and their numeric data are used for modeling. Predictions from the constructed models depend on these data. Generic study of sensitivity aims to show to what degree model behavior is altered by modification of some specific data. If small variations cause important modifications in the model’s global behavior then the model is very sensitive in relation to the variables used. If uncertain systems are considered, then it is important to submit the system to extreme situations and analyze its behavior. In this article, some indexes of uncertainty will be defined in order to determine the variables' influence in the case of extreme changes. This will permit analysis of the system’s sensitivity in relation to several simulations.
Simulation of the digestive process in the evaluation of radionuclide availability in pharmaceutical clays for internal use
Microchemical Journal, Volume 124, 2016, pp. 111-115
The occurrence and mobility of natural radioactive elements such as polonium, uranium and thorium isotopes in six pharmaceutical clays for internal use (as found on the Italian market) were determined because the effects on human health must take into account the availability of these elements. The simulation of gastrointestinal digestion was divided into two stages and was accomplished using two different solutions: a synthetic stomach solution and a synthetic bile–pancreas solution. The same sample was treated in two different ways: (a) only gastric digestion and (b) gastrointestinal digestion (stomach solution+bile–pancreas solution). Very significant differences were found for uranium with respect to those found for thorium, and for polonium with regard to either gastric or gastrointestinal digestion. On the contrary, the differences between the polonium mobility and that of thorium are not very pronounced for either gastric or gastrointestinal digestion. Gastric digestions present no differences with respect to complete gastrointestinal digestion for uranium, thorium and polonium mobility.
Discriminant sparse label-sensitive embedding: Application to image-based face pose estimation
Engineering Applications of Artificial Intelligence, Volume 50, 2016, pp. 168-176
In this letter, the authors propose a new embedding scheme for image-based continuous face pose estimation. The main contributions are as follows. First, it is shown that the concept of label-sensitive Locality Preserving Projections, proposed for age estimation, can be used for model-less face pose estimation. Second, the authors propose a linear embedding by exploiting the connections between facial features and pose labels via a sparse coding scheme. The resulting technique is called Sparse Label sensitive Locality Preserving Projections (Sp-LsLPP). Third, for enhancing the discrimination between poses, the projections obtained by Sp-LsLPP are fed to a Discriminant Embedding that exploits the continuous labels. The resulting framework has less parameters compared to related works. It has been applied to the problem of model-less face yaw angle estimation (person independent 3D face pose estimation). It was tested on three databases: FacePix, Taiwan, and Columbia. It was conveniently compared with other linear and non-linear techniques. The experimental results confirm that the proposed framework can outperform, in general, the existing ones.
Identifying stability conditions and Hopf bifurcations in a consumer resource model using a consumption threshold
Ecological Complexity, Volume 28, 2016, pp. 212-217
The existence, or not, of cyclic dynamics is one of the pivotal aspects of ecological populations. This work considers a consumer resource model found in ecology that can describe both cyclic and non-cyclic dynamics depending on parameter conditions. A threshold consumption number C0 is introduced, similar to the basic reproduction in epidemiological models. It is shown that consumer survival requires C0>1 and that a Hopf bifurcation occurs at , where is defined here and is greater than 1. This result is discussed with an example and extensions to other more complicated models.
Colonization rules and spatial distributions in ecology
Ecological Complexity, Volume 28, 2016, pp. 218-221
Because they are intuitive and mathematically straight-forward, colonization rules are often used to model spatial patterns in ecology. Colonization rules assign individuals to categories according to the locations of previous colonists. In this note, a compact introduction to colonization rules in ecology is presented with implications for autocorrelation and spatial distributions. I use the colonization rule approach to unify a diverse set of spatial and species diversity analyses, exploring future extensions to incorporate greater realism.
Simple assumptions predicts prey selection by piscivorous fishes
Ecological Complexity, Volume 28, 2016, pp. 158-162
Studies on trophic interactions permits the use of community-wide network analyses to evaluate the consequences of human interventions in natural communities. In this paper, we aimed to get insights into the underlying mechanism of prey selection for four piscivorous species, and evaluate behavioral responses to prey selection after an impoundment. We assemble six food web models to search for the hypothesis that best predict observed prey selection pattern of piscivorous fishes combining the following assumptions: (i) predation window, defined as the size range of prey species consumed by a piscivorous fish; (ii) prey strategies to avoid predation (iii) and prey abundance. We tested the probability of each hypothesis to reproduce two empirical data, one before and one after an impoundment with minimum assumptions. Before impoundment, we found that predators presented switching behavior, preying preferably on abundant prey; while after impoundment, predators consumed prey within its predation window. Those results explained better than the null hypotesis and all other assumptions; and corroborate with both theoretical and empirical studies. We conclude that different assumptions drives piscivorous fish behavior in different environments; and modelling procedures can be used to assess gaps in trophic interactions of fish communities.
© 2016 Elsevier B.V. All rights reserved.
The concept of functional redundancy implies that species loss is compensated by other species contributing similarly to functioning. Functional redundancy can be revealed by the relationship between biodiversity and ecosystem functioning (e.g., biomass growth).What is the redundancy hypothesis in biodiversity? ›
The redundancy hypothesis predicts that the species redundancy in a plant community enhances community stability. However, numerous studies in recent years questioned the positive correlation between redundancy and stability.How does redundancy lead to stability in an ecosystem? ›
Higher functional redundancy therefore provides a form of insurance against stochastic population fluctuations or species loss, resulting in stability in community structure or ecosystem function. Stability can be realized as either resistance to change or resilience in recovering from disturbance.What is the concept of ecosystem assessment? ›
Ecosystem assessment takes many forms, but most commonly it involves documenting factors that affect the health and functioning of natural ecosystems. This could include documenting how much of an ecosystem type has been converted to intensive land uses; like for agriculture or urban development.What are the negative effects of redundancy? ›
Whether expected or sudden, redundancy can cause huge uncertainty, stress and anxiety, and can make existing mental health problems worse. On this page, you'll find some ways to look after your mental health during the redundancy process.What is the problem of redundancy problem? ›
In international finance, the redundancy problem, also known as the n − 1 problem, is a problem of inequality of the number of policy instruments and the number of targets at the international level, suggested by Robert Mundell in Robert Mundell (1969).How is the redundancy beneficial to organisms? ›
Gene redundancy may increase gene expression level. The process of gene duplication has an immediate effect on gene dosage and this feature can be beneficial for the organism, which in turn drives the conservation of functionally overlapping pairs of genes.Why is redundancy important in biology? ›
Pathway redundancy is common across all life and evolved to protect against perturbations that could disrupt vital processes, such as mutations and environmental changes.What does redundancy mean in environment? ›
A redundant environment is one in which there is no single point of failure. The second OpenSwitch server protects the replication environment from the failure of the first OpenSwitch server by assuming control of the failover sequence in case the subsequent active database fails or Replication Server fails.What is the main weakness of redundancy in a system? ›
Data Redundancy Disadvantages
Allows for data corruption caused by damage or errors sustained during the process of storage and transfer of data across multiple locations. Increases data maintenance costs by requiring multiple copies of the same content to be maintained with costly data management programs.
Redundancy causes insertion, deletion, and updation anomalies. Redundancy can be avoided by normalizing the database, maintaining master data, etc.Is redundancy causing stress? ›
Experiencing a redundancy can be a deeply personal and emotionally challenging experience that can significantly impact your mental health. It can involve multiple blows such as the loss of income, status, daily routine, social support, self-esteem, and identity.What are the components of ecosystem assessment? ›
- Ecosystem Function.
- Natural Capital.
- Provisioning Service.
The immediate goal of ecosystem analysis studies is to understand ecosystems and ecosystem processes ; many of these goals are directly related to such applied problems as organic matter production or the influence of management practices on various ecosystem parameters.What is the importance of carrying out an ecosystem assessment and management? ›
It analyses the effects of climate change, for example, on ecosystems and on their ability to provide people with the goods that they are used to. Thereby, it gives decision makers the information they need to improve the conservation and sustainable use of ecosystems and to minimize negative impacts of water use.Why redundancy should be avoided? ›
Redundancy is the enemy of clear and concise writing. It results in poor flow and impedes understanding, and it might be keeping you from writing effective technical reports. Utilize these three simple tips to eliminate redundancy from your writing: leave out unnecessary words, avoid repetition, and be direct.What are examples of redundancy effect? ›
Examples of the Redundancy Effect include: Too many words on a PowerPoint slide. Excessive PowerPoint animations. The teacher talking about something else whilst students do a task.How can redundancy affect you socially? ›
Although losing your job isn't always a negative event, for some people it can bring up feelings of rejection, low self-esteem and loss. Feeling less productive and a loss of social contact can also leave people feeling isolated.Is redundancy a bad thing in terms of the Internet Why or why not? ›
Redundancy is a good thing, in case some routers fail because then packets will be rerouted and still successfully send. It is a method for ensuring network availability in case of a network device or path failure and unavailability.What is an error of redundancy? ›
Redundancy means that the same data has been repeated twice, but just by using different words. The sentences which have redundant data don't necessarily mean are grammatically incorrect, but they have unnecessary words, which need to be avoided at all costs.
- Cost savings. ...
- Avoiding compulsory redundancies. ...
- More positive for morale. ...
- You risk losing the best employees. ...
- Higher costs. ...
- Risk of discrimination claims. ...
- Negative effect on those not selected.
Redundancy—Biology's Contingency Plan
Genetic redundancy describes two copies of the same gene whereby the protein encoded by one can function in place of the other. A classic example of genetic redundancy occurs in metabolism, where two genes encode proteins that catalyze the same reaction (Toda et al., 1987).
The Selective Advantage of Redundancy
From an evolutionary perspective, redundancy is thought to buffer phenotypes from genomic variations by reducing the phenotypic cost of mutations, consequently increasing an organism's ability to evolve (evolvability) (Kirschner and Gerhart, 2005).
Abstract. Genetic redundancy means that two or more genes are performing the same function and that inactivation of one of these genes has little or no effect on the biological phenotype.What does redundancy mean and what is it important? ›
Redundancy is an engineering term which means “the duplication of critical components or functions of a system with the intention of increasing reliability of the system, usually in the form of a backup or fail-safe, or to improve actual system performance”What do you mean by redundancy how this can be avoided? ›
It is a process in which data is efficiently organized in a database so that duplication can be avoided. It ensures that the data across all the records provide a similar look and can be read in a particular manner.How do you overcome redundancy? ›
- keep calm.
- stay positive, see redundancy as an opportunity for change.
- focus on moving on, rather than looking back.
- take stock of your situation and look at your options.
- get advice from professional advisers.
- talk to your friends and family.
- The Work is No Longer Needed. ...
- New Processes Have Been Introduced. ...
- Other Employees Are Completing the Work. ...
- The Business is Closing. ...
- The Business is Relocating. ...
- Automatically Unfair Reasons for Redundancy.
When you let go of your job and start to think about the future, you may feel an initial period of depression when the reality sets in. You may experience a sense of loss from your job – even if it was a job that you didn't enjoy. This can lead to feelings of sadness, which can sometimes feel intense.What is ecosystem risk assessment? ›
Ecological Risk Assessment (EcoRA) involves the assessment of the risks posed by the presence of substances released to the environment by man, in theory, on all living organisms in the variety of ecosystems which make up the environment.
Ecological vulnerability assessment is a useful tool to help decision makers understand the various impacts of natural and factitious elements on eco-system. Under this circumstance, evaluating the ecological vulnerability is necessary to make implications for ecological conservation and environmental management.What are the 3 main components of an ecosystem? ›
Ecosystems have lots of different living organisms that interact with each other. The living organisms in an ecosystem can be divided into three categories: producers, consumers and decomposers. They are all important parts of an ecosystem.What are the 4 goals of ecosystem management? ›
Advocates glowingly describe ecosystem management as an approach that will protect the environment, maintain healthy ecosystems, preserve biological diversity, and ensure sustainable development.What is the conclusion of ecosystem? ›
Ecosystems are created by the interrelationships between living organisms and the physical environments they inhabit (land, water, air). Ecosystems require a source of energy to make them work and for most, although not all, this is light from the sun.What are the benefits of ecosystem valuation? ›
Ecosystem valuation can help resource managers deal with the effects of market failures, by measuring their costs to society, in terms of lost economic benefits.What should we do to improve ecosystem management? ›
To achieve these goals, ecosystem managers can be appointed to balance natural resource extraction and conservation over a long-term timeframe. Partnerships between ecosystem managers, natural resource managers, and stakeholders should be encouraged in order to promote the sustainable use of limited natural resources.Why is it crucial to understand the carrying capacity of an ecosystem? ›
If a population exceeds carrying capacity, the ecosystem may become unsuitable for the species to survive. If the population exceeds the carrying capacity for a long period of time, resources may be completely depleted. Populations may die off if all of the resources are exhausted.Why is monitoring ecosystem changes important? ›
It is important to monitor the natural environment in order to document how crucial characteristics of nature changes over time, both due to natural and man-made influences. NINA monitors both wildlife and ecosystems and contributes to the knowledge base for more sustainable management of nature.What is redundancy in ecology? ›
Redundancy hypothesis refer to the enhancement of species that can compensate each other if some species loss due to harsh conditions such particular species has the ability to recover from environmental disturbances.What is redundancy in protein function? ›
Genetic redundancy describes two copies of the same gene whereby the protein encoded by one can function in place of the other. A classic example of genetic redundancy occurs in metabolism, where two genes encode proteins that catalyze the same reaction (Toda et al., 1987).
Second, we used measures of functional redundancy, which can be defined as the number of species performing similar roles in an ecosystem, for example nutrient cycling, sediment fixation or climate regulation.Is redundancy a good or bad thing and why? ›
Is data redundancy good or bad? Depending on the application, data redundancy can be both advantageous and damaging. On the one hand, data redundancy can increase the data's reliability and availability by providing many copies that can be used if one copy becomes unavailable or lost.What is redundancy and why is it important? ›
Data redundancy is a common approach to improve the reliability and availability of a system. Adding redundancy increases the cost and complexity of designing a system. However, the rule to follow is that if the cost of failure is high enough, redundancy is an attractive option.What are examples of redundancy in systems? ›
Redundancy in IT systems means having the ability to duplicate your system components, whether on hardware, VMs, or the cloud. At the user level, a simple example is making a copy of the user's PC system and storing it on another PC as a spare in case the user's PC fails.How does gene redundancy affect organisms? ›
Genetic redundancy is potentially of great relevance to organismal evolution, since it may (i) 'protect' organisms from potentially harmful mutations, and (ii) maintain pools of functionally similar, yet diverse gene products, and thus represent a source of evolutionary novelty at the biochemical level.How do functions eliminate redundancy? ›
Besides simplifying long sections of code, functions are also regularly used to reduce redundancy in code, similar to loops. Using functions, we can take code that is repeated in multiple locations, and keep it in one centralized location.What is redundancy of the genetic code in biology? ›
Redundancy in the genetic code means that most amino acids are specified by more than one mRNA codon. For example, the amino acid phenylalanine (Phe) is specified by the codons UUU and UUC, and the amino acid leucine (Leu) is specified by the codons CUU, CUC, CUA, and CUG.What are the 5 types of redundancy? ›
What is redundancy, you might ask. Well, the act of using a word, phrase, etc., that repeats something else and is therefore unnecessary. The five most common types of redundancy are: the pleonasm, redundant abbreviations, intensifiers, plague words, and platitudes and cliches.What are examples of redundancy in the real world? ›
Your GPS system is an example of an active redundancy system, so if you get lost, your GPS already has a route home. Another example might be a backup generator in a hospital, where life-saving equipment is kept on and functioning during power outages or natural disasters.What is the difference between functional redundancy and functional diversity? ›
In this trait space, we examine the global patterns of functional diversity (the range of unique trait combinations) and functional redundancy (the number of species sharing similar sets of traits), testing the relationship of each with species richness.