Negative density-dependent dispersal in tsetse (Glossina spp): An artefact of inappropriate analysis

Published analysis of genetic material from field-collected tsetse (Glossina spp, primarily from the Palpalis group) has been used to predict that the distance (δ) dispersed per generation increases as effective population densities (De) decrease, displaying negative density-dependent dispersal (NDDD). Using the published data we show this result is an artefact arising primarily from errors in estimates of S, the area occupied by a subpopulation, and thereby in De. The errors arise from the assumption that S can be estimated as the area (S^) regarded as being covered by traps. We use modelling to show that such errors result in anomalously high correlations between δ^ and S^ and the appearance of NDDD, with a slope of -0.5 for the regressions of log(δ^) on log(D^e), even in simulations where we specifically assume density-independent dispersal (DID). A complementary mathematical analysis confirms our findings. Modelling of field results shows, similarly, that the false signal of NDDD can be produced by varying trap deployment patterns. Errors in the estimates of δ in the published analysis were magnified because variation in estimates of S were greater than for all other variables measured, and accounted for the greatest proportion of variation in δ^. Errors in census population estimates result from an erroneous understanding of the relationship between trap placement and expected tsetse catch, exacerbated through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations and between tsetse species. Claims of support in the literature for NDDD are spurious. There is no suggested explanation for how NDDD might have evolved. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control.

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Apparent negative density-dependent dispersal in tsetse (Glossina spp) is an artefact of inappropriate analysis

10.1101/2020.12.17.423205 ◽

2020 ◽

Author(s):

John W. Hargrove ◽

John Van Sickle ◽

Glyn A. Vale ◽

Eric R. Lucas

Keyword(s):

Genetic Material ◽

Population Estimates ◽

Effective Population ◽

Population Densities ◽

Density Dependent ◽

Rate Of Increase ◽

Fundamental Misunderstanding ◽

Geographic Separation ◽

Density Dependent Dispersal

AbstractAnalysis of genetic material from field-collected tsetse (Glossina spp) in ten study areas has been used to predict that the distance (δ) dispersed per generation increases as effective population densities (De) decrease, displaying negative density dependent dispersal (NDDD). This result is an artefact arising primarily from errors in estimates of S, the area occupied by a subpopulation, and thereby in De, the effective subpopulation density. The fundamental, dangerously misleading, error lies in the assumption that S can be estimated as the area (Ŝ) regarded as being covered by traps. Errors in the estimates of δ are magnified because variation in estimates of S is greater than for all other variables measured, and accounts for the greatest proportion of variation in δ. The errors result in anomalously high correlations between δ and S, and the appearance of NDDD, with a slope of −0.5 for the regressions of log(δ) on log(e), even in simulations where dispersal has been set as density independent. A complementary mathematical analysis confirms these findings. Improved error estimates for the crucial parameter b, the rate of increase in genetic distance with increasing geographic separation, suggest that three of the study areas should have been excluded because b is not significantly greater than zero. Errors in census population estimates result from a fundamental misunderstanding of the relationship between trap placement and expected tsetse catch. These errors are exacerbated through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations and between tsetse species. Claims of support in the literature for NDDD are spurious. There is no suggested explanation for how NDDD might have evolved. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control.Author summaryGenetic analysis of field-sampled tsetse (Glossina spp) has been used to suggest that, as tsetse population densities decrease, rates of dispersal increase – displaying negative density dependent dispersal (NDDD). It is further suggested that NDDD might apply to all tsetse species and that, consequently, tsetse control operations might unleash enhanced invasion of areas cleared of tsetse, prejudicing the long-term success of control campaigns. We demonstrate that NDDD in tsetse is an artefact consequent on multiple errors of analysis and interpretation. The most serious of these errors stems from a fundamental misunderstanding of the way in which traps sample tsetse, resulting in huge errors in estimates of the areas sampled by the traps, and occupied by the subpopulations being sampled. Errors in census population estimates are made worse through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations, and between tsetse species. The errors result in the appearance of NDDD, even in modelling situations where rates of dispersal are expressly assumed independent of population density. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control.

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Variation in space and time: a long-term examination of density-dependent dispersal in a woodland rodent

10.1101/536144 ◽

2019 ◽

Author(s):

Simon T. Denomme-Brown ◽

Karl Cottenie ◽

J. Bruce Falls ◽

E. Ann Falls ◽

Ronald J. Brooks ◽

...

Keyword(s):

Time Series ◽

Population Density ◽

Local Density ◽

Spatial Scales ◽

Deer Mice ◽

Population Densities ◽

Density Dependent ◽

Regional Population ◽

The Relationship ◽

Density Dependent Dispersal

AbstractDispersal is a fundamental ecological process that can be affected by population density, yet studies report contrasting effects of density on propensity to disperse. Additionally, the relationship between dispersal and density is seldom examined using densities measured at different spatial scales or over extensive time-series. We used 51-years of trapping data to examine how dispersal by wild deer mice (Peromyscus maniculatus) was affected by changes in both local and regional population densities. We examined these patterns over both the entire time-series and also in ten-year shifting windows to determine whether the nature and strength of the relationship changed through time. Probability of dispersal decreased with increased local and regional population density, and the negative effect of local density on dispersal was more pronounced in years with low regional densities. Additionally, the strength of negative density-dependent dispersal changed through time, ranging from very strong in some decades to absent in other periods of the study. Finally, while females were less likely to disperse, female dispersal was more density-dependent than male dispersal. Our study shows that the relationship between density and dispersal is not temporally static and that investigations of density-dependent dispersal should consider both local and regional population densities.

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The use of Biologically Realistic Equations to Describe the Effects of Weed Density and Relative Time of Emergence on Crop Yield

Weed Science ◽

10.1017/s0043174500060872 ◽

1987 ◽

Vol 35 (5) ◽

pp. 720-725 ◽

Cited By ~ 143

Author(s):

Roger Cousens ◽

Philip Brain ◽

John T. O'Donovan ◽

P. Ashley O'Sullivan

Keyword(s):

Seedling Emergence ◽

Multiple Regression Model ◽

Regression Coefficients ◽

Published Data ◽

Wild Oat ◽

Relative Time ◽

Yield Increase ◽

Weed Density ◽

Image Position ◽

The Relationship

A model, based on a rectangular hyperbola, has been developed to describe the relationship between population density and relative time of seedling emergence of wild oat (Avena fatuaL. # AVEFA) and yield of barley (Hordeum vulgareL.) and wheat (Triticum aestivumL.). The equation iswhere yLis percent yield loss, D is weed density, T is relative time of emergence of weed and crop, and a, b, and c are nonlinear regression coefficients. Significant differences in fitted equations were found between years. From the values of regression coefficients it was concluded that barley is a better competitor than wheat and is less affected by late-emerging wild oat. The model was tested on previously published data. It provided only a slightly better description of the data than a multiple-regression model, but avoided a number of undesirable, implausible properties inherent in the more frequently used approach. In particular, the model does not predict a loss in yield when no weeds are present or a yield increase from late-emerging weeds.

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The estimation of the metabolizable energy of forage from its cell-wall content and digestible cell wall

The Journal of Agricultural Science ◽

10.1017/s0021859600051303 ◽

1974 ◽

Vol 82 (3) ◽

pp. 423-426 ◽

Cited By ~ 2

Author(s):

K. W. Moir

Keyword(s):

Cell Wall ◽

Organic Matter ◽

Cell Walls ◽

Metabolizable Energy ◽

Published Data ◽

Energy Value ◽

Image Position ◽

The Relationship

SUMMARYPublished data are used in support of a hypothesis that equal amounts of digestible cell walls and digestible non-cell walls do not contribute equally to the energy value of forages. The relationship between the concentration in the organic matter of metabolizable energy (kcal/g organic matter) determined at the maintenance level of feeding, and the percentages of cell wall and digestible cell wall in the forage organic matter is defined by:This equation derived from published data on 12 grasses appears to be applicable to both grasses and legumes.

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Assessing the relationship of ancient and modern populations

10.1101/113779 ◽

2017 ◽

Cited By ~ 2

Author(s):

Joshua G. Schraiber

Keyword(s):

Genetic Material ◽

Sequencing Error ◽

Effective Population ◽

Ancient Sample ◽

Snp Data ◽

Two Samples ◽

Low Coverage ◽

Relationship Of ◽

Modern Population ◽

The Relationship

AbstractGenetic material sequenced from ancient samples is revolutionizing our understanding of the recent evolutionary past. However, ancient DNA is often degraded, resulting in low coverage, error-prone sequencing. Several solutions exist to this problem, ranging from simple approach such as selecting a read at random for each site to more complicated approaches involving genotype likelihoods. In this work, we present a novel method for assessing the relationship of an ancient sample with a modern population while accounting for sequencing error and post-mortem damage by analyzing raw read from multiple ancient individuals simultaneously. We show that when analyzing SNP data, it is better to sequence more ancient samples to low coverage: two samples sequenced to 0.5x coverage provide better resolution than a single sample sequenced to 2x coverage. We also examined the power to detect whether an ancient sample is directly ancestral to a modern population, finding that with even a few high cover-age individuals, even ancient samples that are very slightly diverged from the modern population can be detected with ease. When we applied our approach to European samples, we found that no ancient samples represent direct ancestors of modern Europeans. We also found that, as shown previously, the most ancient Europeans appear to have had the smallest effective population sizes, indicating a role for agriculture in modern population growth.

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Urbanization impacts on production and recruitment of Fundulus heteroclitus in salt marsh creeks

Marine Ecology Progress Series ◽

10.3354/meps13378 ◽

2020 ◽

Vol 645 ◽

pp. 187-204

Author(s):

PJ Rudershausen ◽

JA Buckel

Keyword(s):

Salt Marsh ◽

Salt Marshes ◽

Fundulus Heteroclitus ◽

Multiple Factor Analysis ◽

Southeastern Usa ◽

Density Dependent ◽

Dependent Relationship ◽

Juvenile Abundance ◽

The Relationship ◽

Throw Trap

It is unclear how urbanization affects secondary biological production in estuaries in the southeastern USA. We estimated production of larval/juvenile Fundulus heteroclitus in salt marsh areas of North Carolina tidal creeks and tested for factors influencing production. F. heteroclitus were collected with a throw trap in salt marshes of 5 creeks subjected to a range of urbanization intensities. Multiple factor analysis (MFA) was used to reduce dimensionality of habitat and urbanization effects in the creeks and their watersheds. Production was then related to the first 2 dimensions of the MFA, month, and year. Lastly, we determined the relationship between creek-wide larval/juvenile production and abundance from spring and abundance of adults from autumn of the same year. Production in marsh (g m-2 d-1) varied between years and was negatively related to the MFA dimension that indexed salt marsh; higher rates of production were related to creeks with higher percentages of marsh. An asymptotic relationship was found between abundance of adults and creek-wide production of larvae/juveniles and an even stronger density-dependent relationship was found between abundance of adults and creek-wide larval/juvenile abundance. Results demonstrate (1) the ability of F. heteroclitus to maintain production within salt marsh in creeks with a lesser percentage of marsh as long as this habitat is not removed altogether and (2) a density-dependent link between age-0 production/abundance and subsequent adult recruitment. Given the relationship between production and marsh area, natural resource agencies should consider impacts of development on production when permitting construction in the southeastern USA.

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