Consequences of spatial patterns for coexistence in species-rich plant communities

AbstractEcology cannot yet fully explain why so many tree species coexist in natural communities such as tropical forests. A major difficulty is linking individual-level processes to community dynamics. We propose a combination of tree spatial data, spatial statistics and dynamical theory to reveal the relationship between spatial patterns and population-level interaction coefficients and their consequences for multispecies dynamics and coexistence. Here we show that the emerging population-level interaction coefficients have, for a broad range of circumstances, a simpler structure than their individual-level counterparts, which allows for an analytical treatment of equilibrium and stability conditions. Mechanisms such as animal seed dispersal, which result in clustering of recruits that is decoupled from parent locations, lead to a rare-species advantage and coexistence of otherwise neutral competitors. Linking spatial statistics with theories of community dynamics offers new avenues for explaining species coexistence and calls for rethinking community ecology through a spatial lens.

Download Full-text

Walking behaviour in the ground beetle, Poecilus cupreus: dispersal potential, intermittency and individual variation

Bulletin of Entomological Research ◽

10.1017/s0007485320000565 ◽

2020 ◽

pp. 1-10

Author(s):

Joseph D. Bailey ◽

Carly M. Benefer ◽

Rod P. Blackshaw ◽

Edward A. Codling

Keyword(s):

Individual Variation ◽

Community Dynamics ◽

Ground Beetle ◽

Management Strategies ◽

Population Level ◽

Poecilus Cupreus ◽

Individual Level ◽

Dispersal Potential ◽

Simple Movement ◽

Dispersal Distances

Abstract Dispersal is a key ecological process affecting community dynamics and the maintenance of populations. There is increasing awareness of the need to understand individual dispersal potential to better inform population-level dispersal, allowing more accurate models of the spread of invasive and beneficial insects, aiding crop and pest management strategies. Here, fine-scale movements of Poecilus cupreus, an important agricultural carabid predator, were recorded using a locomotion compensator and key movement characteristics were quantified. Net displacement increased more rapidly than predicted by a simple correlated random walk model with near ballistic behaviour observed. Individuals displayed a latent ability to head on a constant bearing for protracted time periods, despite no clear evidence of a population level global orientation bias. Intermittent bouts of movement and non-movement were observed, with both the frequency and duration of bouts of movement varying at the inter- and intra-individual level. Variation in movement behaviour was observed at both the inter- and intra- individual level. Analysis suggests that individuals have the potential to rapidly disperse over a wider area than predicted by simple movement models parametrised at the population level. This highlights the importance of considering the role of individual variation when analysing movement and attempting to predict dispersal distances.

Download Full-text

Measuring The Impact of Spatial Perturbations on The Relationship Between Data Privacy and Validity of Descriptive Statistics

10.21203/rs.3.rs-77449/v1 ◽

2020 ◽

Author(s):

Kelly Broen ◽

Rob Trangucci ◽

Jon Zelner

Keyword(s):

Spatial Statistics ◽

Spatial Patterns ◽

Spatial Data ◽

Data Privacy ◽

Perturbation Methods ◽

Descriptive Statistics ◽

Moran’S I ◽

Mortality Data ◽

Moran's I ◽

The Impact

Abstract Background: Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods: We analyzed the impact of perturbation on spatial patterns in the full set of address- level mortality data from Lawrence, MA during the period from 1911-1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and the its compliance with HIPAA privacy standards. Results: Random perturbation at 50 meters, donut masking between 5 and 50 meters, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100x100 and 250x250 meter cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions: Using the set of published perturbation methods applied in this analysis, HIPAA- compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

Download Full-text

Measuring the impact of spatial perturbations on the relationship between data privacy and validity of descriptive statistics

International Journal of Health Geographics ◽

10.1186/s12942-020-00256-8 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Kelly Broen ◽

Rob Trangucci ◽

Jon Zelner

Keyword(s):

Spatial Statistics ◽

Spatial Patterns ◽

Spatial Data ◽

Data Privacy ◽

Perturbation Methods ◽

Descriptive Statistics ◽

Moran’S I ◽

Mortality Data ◽

Moran's I ◽

The Impact

Abstract Background Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods We analyzed the impact of perturbation on spatial patterns in the full set of address-level mortality data from Lawrence, MA during the period from 1911 to 1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and its compliance with HIPAA and GDPR privacy standards. Results Random perturbation at 50 m, donut masking between 5 and 50 m, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100 × 100 and 250 × 250 m cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions Using the set of published perturbation methods applied in this analysis, HIPAA and GDPR compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

Download Full-text

Resource supply drives even spacing of individuals along multiple trait axes in light-limited phytoplankton populations

10.1101/338129 ◽

2018 ◽

Author(s):

Simone Fontana ◽

Mridul K. Thomas ◽

Marta Reyes ◽

Francesco Pomati

Keyword(s):

Community Dynamics ◽

Species Coexistence ◽

Resource Limitation ◽

Pseudokirchneriella Subcapitata ◽

Field Pattern ◽

Multiple Trait ◽

Individual Level ◽

Phytoplankton Communities ◽

Wide Range ◽

Trait Space

AbstractIndividual-level variation arising from responses to environmental gradients influences population and community dynamics. How such responses empirically relate to the mechanisms that govern species coexistence is however not well understood. Previous results from lake phytoplankton communities suggested that the evenness of organisms in multidimensional trait space increases with resource limitation, possibly due to resource partitioning at the individual level. Here we experimentally tested the emergence of this pattern by growing two phytoplankton species (Pseudokirchneriella subcapitata, Microcystis aeruginosa) under a gradient of light intensity, in monoculture and jointly. Under low light (resource) conditions, the populations diversified into a wide range of phenotypes, which were evenly distributed in multidimensional trait space (defined by four pigment-related trait dimensions), confirming the observed field pattern. Our results provide prime experimental evidence that resource limitation induces even spacing of conspecific and heterospecific microbial phenotypes along trait axes, and advances our understanding of trait-based coexistence.

Download Full-text

A spatially explicit Bayesian framework for cognitive schooling behaviours

Interface Focus ◽

10.1098/rsfs.2012.0027 ◽

2012 ◽

Vol 2 (6) ◽

pp. 738-745 ◽

Cited By ~ 4

Author(s):

Daniel Grünbaum

Keyword(s):

Spatial Memory ◽

Spatial Data ◽

Evolutionary Dynamics ◽

Spatial Information ◽

Empirical Studies ◽

Population Level ◽

Cognitive State ◽

Cognitive Responses ◽

Individual Level ◽

Social Animals

Social aggregations such as schools, swarms, flocks and herds occur across a broad diversity of animal species, strongly impacting ecological and evolutionary dynamics of these species and their predators, prey and competitors. The mechanisms through which individual-level responses to neighbours generate group-level characteristics have been extensively investigated both experimentally and using mathematical models. Models of social groups typically adopt a ‘zone’ approach, in which individuals’ movement responses to neighbours are functions of instantaneous relative position. Empirical studies have demonstrated that most social animals such as fish exhibit well-developed spatial memory and other advanced cognitive capabilities. However, most models of social grouping do not explicitly include spatial memory, largely because a tractable framework for modelling acquisition of and response to historical spatial information has been lacking. Using fish schooling as a focal example, this study presents a framework for including cognitive responses to spatial memory in models of social aggregation. The framework utilizes Bayesian estimation parameters that are continuously distributed in time and space as proxies for animals’ spatial memory. The result is a hybrid Lagrangian–Eulerian model in which the effects of cognitive state and behavioural responses to historical spatial data on individual-, group- and population-level distributions of social animals can be explicitly investigated.

Download Full-text

Blood Pressure Trajectories Across the Life Course

American Journal of Hypertension ◽

10.1093/ajh/hpab009 ◽

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.

Download Full-text

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

Sustainability ◽

10.3390/su13010368 ◽

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.

Download Full-text

Medication Adherence: Expanding the Conceptual Framework

American Journal of Hypertension ◽

10.1093/ajh/hpab046 ◽

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.

Download Full-text

Spatial patterns and species coexistence in mixed Abies marocana-Cedrus atlantica forest in Talassemtane National Park

Forest Ecology and Management ◽

10.1016/j.foreco.2021.119967 ◽

2022 ◽

Vol 506 ◽

pp. 119967

Author(s):

Mariem Ben-Said ◽

Juan Carlos Linares ◽

José Antonio Carreira ◽

Lahcen Taïqui

Keyword(s):

Spatial Patterns ◽

National Park ◽

Species Coexistence ◽

Cedrus Atlantica

Download Full-text

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

Journal of Nutrition ◽

10.1093/jn/nxy211 ◽

2018 ◽

Vol 148 (12) ◽

pp. 1946-1953 ◽

Cited By ~ 6

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.

Download Full-text