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

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.

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

2021 ◽  
Vol 15 (3) ◽  
pp. e0009026
Author(s):  
John W. Hargrove ◽  
John Van Sickle ◽  
Glyn A. Vale ◽  
Eric R. Lucas
Keyword(s):  
Genetic Material ◽  
Published Data ◽  
Effective Population ◽  
Density Dependent ◽  
False Signal ◽  
Image Position ◽  
The Relationship ◽  
Suggested Explanation ◽  
Density Dependent Dispersal ◽  
Trap Placement

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.

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

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.

scholarly journals Estimation of Population-Specific Genetic Parameters Important for Long-Term Optimum Contribution Selection—Case Study on a Dairy Istrian Sheep Breed

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2356
Author(s):  
Ante Kasap ◽  
Jelena Ramljak ◽  
Marija Špehar
Keyword(s):  
Sheep Breed ◽  
Effective Population ◽  
Term Survival ◽  
Self Sufficiency ◽  
Dairy Traits ◽  
Rate Of Increase ◽  
Estimated Breeding Values ◽  
National Selection ◽  
Window Approach

The Istrian sheep breed has been subjected to selection for dairy traits for more than two decades. However, a detailed study of some important population-specific parameters such as effective population size (Ne) and connectedness between flocks has never been carried out. The aim of the study was to examine the above parameters in dairy Istrian sheep subjected to a national selection program. The Ne was estimated as the mean rate of increase in coancestry, and connectedness was determined using four different statistics. The Ne was estimated at 73 animals with pedigree constraints imposed on 4 equivalent generations and 3 full generations. Analysis of ΔNe (“sliding window approach”) revealed a negative ΔNe indicating a progressive loss of genetic variability (ΔNeNEG≥4 = −6.6, p < 0.01; ΔNeNFG≥3 = −4.9, p > 0.05). The overall connectedness (r¯ ~ 0.0001) was below the acceptable level for unbiased ranking of the animals belonging to different flocks (ri,j  = 0.05). OCS appears to be the best option for the long-term survival (self-sufficiency) of the breed, but genetic links between flocks need to be strengthened to allow unbiased ranking of the animals based on the estimated breeding values.

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

Oecologia ◽  
2020 ◽  
Vol 193 (4) ◽  
pp. 903-912
Author(s):  
Simon T. Denomme-Brown ◽  
Karl Cottenie ◽  
J. Bruce Falls ◽  
E. Ann Falls ◽  
Ronald J. Brooks ◽  
...  
Keyword(s):  
Density Dependent ◽  
Space And Time ◽  
Density Dependent Dispersal

scholarly journals Selection Response in Finite Populations

Genetics ◽  
1996 ◽  
Vol 144 (4) ◽  
pp. 1961-1974 ◽  
Author(s):  
Ming Wei ◽  
Armando Caballero ◽  
William G Hill
Keyword(s):  
Linkage Disequilibrium ◽  
Inbreeding Depression ◽  
Genetic Variance ◽  
Relative Rate ◽  
Selection Response ◽  
Rate Of Change ◽  
Effective Population ◽  
Short Term ◽  
Model Account

Formulae were derived to predict genetic response under various selection schemes assuming an infinitesimal model. Account was taken of genetic drift, gametic (linkage) disequilibrium (Bulmer effect), inbreeding depression, common environmental variance, and both initial segregating variance within families (σAW02) and mutational (σM2) variance. The cumulative response to selection until generation t(CRt) can be approximated asCRt≈R0[t−β(1−σAW∞2σAW02)t24Ne]−Dt2Ne,where Ne is the effective population size, σAW∞2=NeσM2 is the genetic variance within families at the steady state (or one-half the genic variance, which is unaffected by selection), and D is the inbreeding depression per unit of inbreeding. R  0 is the selection response at generation 0 assuming preselection so that the linkage disequilibrium effect has stabilized. β is the derivative of the logarithm of the asymptotic response with respect to the logarithm of the within-family genetic variance, i.e., their relative rate of change. R  0 is the major determinant of the short term selection response, but σM2, Ne and β are also important for the long term. A selection method of high accuracy using family information gives a small Ne and will lead to a larger response in the short term and a smaller response in the long term, utilizing mutation less efficiently.

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