Competitive ability: definitions, contingency and correlated traits

1996 ◽  
Vol 351 (1345) ◽  
pp. 1377-1385 ◽  
Keyword(s):  
Competitive Ability ◽  
Plant Traits ◽  
A Priori ◽  
Population Level ◽  
Model Systems ◽  
Individual Plant ◽  
Competitive Effect ◽  
Competitive Response ◽  
Individual Level ◽  
Competitive Success

Although the relationship between individual plant traits and competitive success in communities is an essential component of comprehensive models of the role of competition in structuring plant communities, three obstacles have stymied efforts to empirically examine such relationships. First, definitions of competitive ability are often inconsistent among bodies of theory and between theoretical predictions and empirical research. Much of the theoretical literature is for populations and often at equilibrium, while experimental work has been largely on individuals and short term. This situation is likely to continue, except for a few model systems, and therefore it is critical that individual-level surrogates for population level phenomena be found. I suggest that competitive response of seedlings to established vegetation may be an effective surrogate for estimating competitive success of populations at equilibrium and that competitive response of individuals with more similar-sized neighbours may be an effective surrogate for competitive success of populations earlier in succession or in non-equilibrium systems. Second, competitive ability may be contingent on many factors, such that it may not be an identifiable characteristic of any particular taxon and thus no broadly applicable relationships between traits and competitive ability may exist. However, a literature survey shows that both competitive response and competitive effect are generally, but not always, consistent regardless of identity of competing species, making the search for relationships with traits reasonable, at least within environments. Among environments, both competitive effect and competitive response are consistent in only about half the studies, making it unreasonable to assume a priori that competitive hierarchies will be similar under different conditions. The third obstacle is logistical; competitive ability is necessarily measured experimentally, and preferably in the field, making it difficult to obtain sufficient sample sizes (numbers of taxa) for rigorous analysis of relationships with traits. I suggest several simplifying assumptions and experimental approaches that could enable much more efficient assaying of competitive abilities of many species.

Causation and laws in biology

2018 ◽  
Author(s):  
Mohan Matthen
Keyword(s):  
Natural Selection ◽  
Evolutionary Theory ◽  
A Priori ◽  
Population Level ◽  
Subject Area ◽  
Structural Determinants ◽  
Individual Level ◽  
Philip Kitcher ◽  
Biological Laws ◽  
Physical Laws

Physicalism appears to undermine the autonomy of ‘special sciences’ such as biology, and to leave little room for proprietary biological laws or causation. Mendel’s ‘Laws’ are so-called because they are fundamental to the subject-area, but since they describe causal processes that are wholly physical in nature, they seem to reduce to physical laws, given certain propositions about the composition of DNA. The same goes for other principles of the biological sciences. This argument has been challenged by Hilary Putnam, on the grounds that good explanations, for instance in mathematical terms, could range more widely than any given physical realization. Putnam argues that mathematics could thus have an autonomous role in science despite physicalism. Putnam’s insight has been applied to classical genetics by Philip Kitcher. A gene is a unit of inheritance that passes unchanged from parent to offspring according to certain rules. It is these rules that are essential to understanding inheritance, not details of interaction in the DNA substrate. Putnam and Kitcher here employ a notion similar to Aristotle’s ‘formal causes’ – functional and structural determinants of biological characteristics that are somewhat independent of material constitution. There are other conceptions of laws to be found in philosophy of science. Some think that they are propositions with the capacity to impart axiomatic structure to what is known about a domain. The principle of natural selection plays this role in biology, though it is a priori. Again, some think that laws are necessary truths: on cladistic systems of classification, the proposition that the common raven is a bird is arguably a law under this understanding. The nature of causal patterns in natural selection has been a matter of some discussion recently. The view that individual-level causes are sufficient to explain selection-outcomes is tempting to the reductionist, but distorts the explanatory aims of evolutionary theory. Clearly, evolutionary theory requires population-level causes. On the other hand, it has been questioned whether natural selection itself should be understood as a ‘force’ acting on a population, somewhat in the same manner as gravitation acts on a body. Statistical views of natural selection seek alternatives to this way of understanding selection. Finally, what are biological entities? Some ontologies admit no priority among collections of atoms – the argument is that an organism, for instance, is nothing more than such a collection. Many biologists, however, treat of composite entities as internally organized complex systems. On this view, cells, organisms, populations, and ecosystems have privileged ontological status.

scholarly journals Shared behavioral mechanisms underlie C. elegans aggregation and swarming

2018 ◽  
Author(s):  
S Serena Ding ◽  
Linus J. Schumacher ◽  
Avelino E. Javer ◽  
Robert G. Endres ◽  
André EX Brown
Keyword(s):  
A Priori ◽  
Population Level ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Individual Level ◽  
C Elegans ◽  
Behavioral Rules ◽  
Level Statistics ◽  
Approximate Bayesian ◽  
Behavioral Mechanisms

AbstractIn complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While such collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescent multi-worm tracking, we quantify aggregation behavior in terms of individual dynamics and population-level statistics. Based on our quantification, we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules that give rise to aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation. Hence, mesoscopic C. elegans uses mechanisms familiar from microscopic systems for aggregation, but implemented via more complex behaviors characteristic of macroscopic organisms.

scholarly journals Shared behavioral mechanisms underlie C. elegans aggregation and swarming

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Siyu Serena Ding ◽  
Linus J Schumacher ◽  
Avelino E Javer ◽  
Robert G Endres ◽  
André EX Brown
Keyword(s):  
A Priori ◽  
Population Level ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Individual Level ◽  
C Elegans ◽  
Behavioral Rules ◽  
Level Statistics ◽  
Approximate Bayesian ◽  
Behavioral Mechanisms

In complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescence multi-worm tracking, we quantify aggregation in terms of individual dynamics and population-level statistics. Then we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules for aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation.

scholarly journals Blood Pressure Trajectories Across the Life Course

2021 ◽  
Vol 34 (3) ◽  
pp. 234-241
Author(s):  
Norrina B Allen ◽  
Sadiya S Khan
Keyword(s):  
Blood Pressure ◽  
Measurement Errors ◽  
Clinical Care ◽  
Population Level ◽  
Cumulative Exposure ◽  
Older Adulthood ◽  
Individual Level ◽  
The Life Course ◽  
Level Group ◽  
Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

scholarly journals Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

2021 ◽  
Vol 13 (1) ◽  
pp. 368
Author(s):  
Dillon T. Fitch ◽  
Hossain Mohiuddin ◽  
Susan L. Handy
Keyword(s):  
Travel Behavior ◽  
Regression Models ◽  
Population Level ◽  
Panel Survey ◽  
Multilevel Regression ◽  
Combine Data ◽  
Cross Sectional ◽  
Individual Level ◽  
Before And After ◽  
Bike Share

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

Medication Adherence: Expanding the Conceptual Framework

2021 ◽  
Author(s):  
Marie Krousel-Wood ◽  
Leslie S Craig ◽  
Erin Peacock ◽  
Emily Zlotnick ◽  
Samantha O’Connell ◽  
...  
Keyword(s):  
Older Adults ◽  
Medication Adherence ◽  
Conceptual Framework ◽  
Clinical Outcomes ◽  
Implicit Attitudes ◽  
Explanatory Power ◽  
Population Level ◽  
Time Preferences ◽  
Adherence Behavior ◽  
Individual Level

Abstract Interventions targeting traditional barriers to antihypertensive medication adherence (AHMA) have been developed and evaluated, with evidence of modest improvements in adherence. Translation of these interventions into population-level improvements in adherence and clinical outcomes among older adults remains suboptimal. From the Cohort Study of Medication Adherence among Older adults (CoSMO), we evaluated traditional barriers to AHMA among older adults with established hypertension (N=1544; mean age=76.2 years, 59.5% women, 27.9% Black, 24.1% and 38.9% low adherence by proportion of days covered (i.e., PDC<0.80) and the 4-item Krousel-Wood Medication Adherence Scale (i.e., K-Wood-MAS-4≥1), respectively), finding that they explained 6.4% and 14.8% of variance in pharmacy refill and self-reported adherence, respectively. Persistent low adherence rates, coupled with low explanatory power of traditional barriers, suggest that other factors warrant attention. Prior research has investigated explicit attitudes toward medications as a driver of adherence; the roles of implicit attitudes and time preferences (e.g., immediate versus delayed gratification) as mechanisms underlying adherence behavior are emerging. Similarly, while associations of individual-level social determinants of health (SDOH) and medication adherence are well-reported, there is growing evidence about structural SDOH and specific pathways of effect. Building on published conceptual models and recent evidence, we propose an expanded conceptual framework that incorporates implicit attitudes, time preferences and structural SDOH, as emerging determinants that may explain additional variation in objectively and subjectively measured adherence. This model provides guidance for design, implementation and assessment of interventions targeting sustained improvement in implementation medication adherence and clinical outcomes among older women and men with hypertension.

scholarly journals Estimating individual level plant traits at scale

2021 ◽  
Author(s):  
Sergio Marconi ◽  
Sarah J. Graves ◽  
Ben.G. Weinstein ◽  
Stephanie Bohlman ◽  
Ethan P. White
Keyword(s):  
Plant Traits ◽  
Individual Level

scholarly journals Urine Spot Samples Can Be Used to Estimate 24-Hour Urinary Sodium Excretion in Children

2018 ◽  
Vol 148 (12) ◽  
pp. 1946-1953 ◽  
Author(s):  
Magali Rios-Leyvraz ◽  
Pascal Bovet ◽  
René Tabin ◽  
Bernard Genin ◽  
Michel Russo ◽  
...  
Keyword(s):  
Sodium Excretion ◽  
Salt Intake ◽  
Sodium Intake ◽  
Population Level ◽  
Urinary Sodium Excretion ◽  
Cross Sectional Study ◽  
Urinary Sodium ◽  
Cross Sectional ◽  
High Sodium ◽  
Individual Level

ABSTRACT Background The gold standard to assess salt intake is 24-h urine collections. Use of a urine spot sample can be a simpler alternative, especially when the goal is to assess sodium intake at the population level. Several equations to estimate 24-h urinary sodium excretion from urine spot samples have been tested in adults, but not in children. Objective The objective of this study was to assess the ability of several equations and urine spot samples to estimate 24-h urinary sodium excretion in children. Methods A cross-sectional study of children between 6 and 16 y of age was conducted. Each child collected one 24-h urine sample and 3 timed urine spot samples, i.e., evening (last void before going to bed), overnight (first void in the morning), and morning (second void in the morning). Eight equations (i.e., Kawasaki, Tanaka, Remer, Mage, Brown with and without potassium, Toft, and Meng) were used to estimate 24-h urinary sodium excretion. The estimates from the different spot samples and equations were compared with the measured excretion through the use of several statistics. Results Among the 101 children recruited, 86 had a complete 24-h urine collection and were included in the analysis (mean age: 10.5 y). The mean measured 24-h urinary sodium excretion was 2.5 g (range: 0.8–6.4 g). The different spot samples and equations provided highly heterogeneous estimates of the 24-h urinary sodium excretion. The overnight spot samples with the Tanaka and Brown equations provided the most accurate estimates (mean bias: −0.20 to −0.12 g; correlation: 0.48–0.53; precision: 69.7–76.5%; sensitivity: 76.9–81.6%; specificity: 66.7%; and misclassification: 23.0–27.7%). The other equations, irrespective of the timing of the spot, provided less accurate estimates. Conclusions Urine spot samples, with selected equations, might provide accurate estimates of the 24-h sodium excretion in children at a population level. At an individual level, they could be used to identify children with high sodium excretion. This study was registered at clinicaltrials.gov as NCT02900261.

scholarly journals Predicting the duration of sickness absence spells due to back pain: a population-based study from Sweden

2019 ◽  
Vol 77 (2) ◽  
pp. 115-121
Author(s):  
Annina Ropponen ◽  
Katalin Gémes ◽  
Paolo Frumento ◽  
Gino Almondo ◽  
Matteo Bottai ◽  
...  
Keyword(s):  
Back Pain ◽  
Sickness Absence ◽  
A Priori ◽  
Population Based ◽  
Final Model ◽  
Individual Level ◽  
Discriminatory Accuracy ◽  
C Statistic ◽  
International Statistical Classification ◽  
The Individual

ObjectivesWe aimed to develop and validate a prediction model for the duration of sickness absence (SA) spells due to back pain (International Statistical Classification of Diseases and Related Health Problems 10th Revision: M54), using Swedish nationwide register microdata.MethodsInformation on all new SA spells >14 days from 1 January 2010 to 30 June 2012 and on possible predictors were obtained. The duration of SA was predicted by using piecewise constant hazard models. Nine predictors were selected for the final model based on a priori decision and log-likelihood loss. The final model was estimated in a random sample of 70% of the SA spells and later validated in the remaining 30%.ResultsOverall, 64 048 SA spells due to back pain were identified during the 2.5 years; 74% lasted ≤90 days, and 9% >365 days. The predictors included in the final model were age, sex, geographical region, employment status, multimorbidity, SA extent at the start of the spell, initiation of SA spell in primary healthcare and number of SA days and specialised outpatient healthcare visits from the preceding year. The overall c-statistic (0.547, 95% CI 0.542 to 0.552) suggested a low discriminatory capacity at the individual level. The c-statistic was 0.643 (95% CI 0.634 to 0.652) to predict >90 days spells, 0.686 (95% CI 0.676 to 0.697) to predict >180 spells and 0.753 (95% CI 0.740 to 0.766) to predict >365 days spells.ConclusionsThe model discriminates SA spells >365 days from shorter SA spells with good discriminatory accuracy.

scholarly journals Measuring social networks in primates: wearable sensors versus direct observations

2020 ◽  
Vol 476 (2236) ◽  
pp. 20190737
Author(s):  
Valeria Gelardi ◽  
Jeanne Godard ◽  
Dany Paleressompoulle ◽  
Nicolas Claidiere ◽  
Alain Barrat
Keyword(s):  
Data Collection ◽  
Wearable Sensors ◽  
A Priori ◽  
Population Level ◽  
Sensor Data ◽  
Collection Method ◽  
Data Collection Method ◽  
The Social ◽  
Different Types ◽  
Data Yield

Network analysis represents a valuable and flexible framework to understand the structure of individual interactions at the population level in animal societies. The versatility of network representations is moreover suited to different types of datasets describing these interactions. However, depending on the data collection method, different pictures of the social bonds between individuals could a priori emerge. Understanding how the data collection method influences the description of the social structure of a group is thus essential to assess the reliability of social studies based on different types of data. This is however rarely feasible, especially for animal groups, where data collection is often challenging. Here, we address this issue by comparing datasets of interactions between primates collected through two different methods: behavioural observations and wearable proximity sensors. We show that, although many directly observed interactions are not detected by the sensors, the global pictures obtained when aggregating the data to build interaction networks turn out to be remarkably similar. Moreover, sensor data yield a reliable social network over short time scales and can be used for long-term studies, showing their important potential for detailed studies of the evolution of animal social groups.

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