Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Genetics and analysis of quantitative traits

Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro-organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade-offs, they give rise to covariation between dispersal and other life-history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life-history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.

Costs of dispersal

Life history biology sits on the interface between genetics and ecology, and both have made important theoretical and empirical contributions to our understanding. However, the connections between the disciplines have not always been as close as they might have been and this book takes some useful steps towards remedying this. It gives an excellent review of life history theory, and integrates this well with results from the empirical literature. After an 11-page introduction, Roff sets out ‘a framework for analysis’ in which he covers the necessary elements of quantitative and population genetics. This includes clear definitions of fitness in a range of circumstances, from density independent populations in constant environments through to the more complex situations of density and frequency dependence and environments that are spatially or temporally stochastic. Trade-offs are then examined, including a valuable analysis of potential pitfalls in studying them and ways that these can be avoided. The author then deals in turn with evolution in constant environments; stochastic environments and ‘predictable environments’. The last of these covers situations where there is environmental variation, but at least some information is available to allow individuals to make an adaptive response. The final chapter identifies 20 topics for future study. Some will find the book too dominated by theory. Others (but probably not readers of Heredity!) will find it contains too much genetics. But Roff does an excellent job of making the theory accessible, covering the essential issues and pointing to original sources for the details. Theory is related to a significant number of empirical studies, although there is room for another book reviewing the empirical literature on life histories in detail, and Roff’s book would provide a robust skeleton on which to hang this. To make my own assessment, I examined in detail Roff’s discussion of the question of fitness measures for density dependent populations in stochastic environments – an area in which I have been involved. I could not fault him – all the key references were there and the issues were made very clear without the more esoteric mathematics. I also examined some areas that I was less familiar with, and again the text was clear and easy to read. My only real criticism of the book would be that its very long chapters (more than 130 pages in one case) makes it difficult to find things. It would have been simple to address this by including the section headings on the contents pages. A minor personal quibble would be that the book usually expresses problems in terms of the intrinsic rate of increase, r, and the characteristic (Lotka) equation. A matrix formulation is often more tractable and is easier to generalise to density dependent populations and stochastic environments, so expanding on the relationship between the two would have been useful. But overall this is an excellent book. It brings together the key theory in a single place. It gives an invaluable route into the literature, with a bibliography of 1600 or so items. These features, and its identification of topics that need further study should make an important contribution to moving the field forward.

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Life History Evolution

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1365-2656.2006.01164.x

Effects of sampling regime on the mean and variance of home range size estimates

The Siberian flying squirrel (Pteromys volans) is a herbivorous, nocturnal, and arboreal rodent living in boreal coniferous forests. Home-range sizes, movements, and nest-use behavior of Pteromys were studied by radiotelemetry in southern Finland in 1996-1998. Thirty-seven animals were tracked. Average home-range size measured by 100% minimum convex polygons was 59.9 ha for males and 8.3 ha for females. Both sexes concentrated their activities in core areas that represented 9% and 11% of the home-range areas in males and females, respectively. Home ranges of males and females were several times larger than predicted according to body mass. Similarly, home ranges of Pteromys were much larger than in other gliding herbivores. Males especially showed great mobility; the average distance moved from the nest at night was 292 m, and the longest distances recorded were >2 km. A plausible explanation for the large home ranges and great mobility of Pteromys is its gliding ability; both sexes can reach distant parts of the home range for foraging, and males also can reach distant parts for receptive females. Pteromys had several nests, both cavities and dreys (nests in branches of trees), which they changed frequently.

Home-range size, movements, and nest-site use in the siberian flying squirrel, pteromys volans

Dispersal is a key determinant of the population dynamics of species. Thus, a better understanding of how dispersal is affected by the landscape structure and how animals make decisions about moving across different landscapes is needed. We studied the dispersal of 60 radio-collared juvenile Siberian flying squirrels (Pteromys volans) in southern Finland. The effect of landscape structure on selected dispersal direction, dispersal distance, and straightness of dispersal path was studied. Flying squirrels were capable of dispersing over long distances in fragmented forest landscapes. The patches used as temporary roosting sites during dispersal were of a lower quality than were those used as finally occupied patches. The patches used were larger than were patches on average in the study areas. There was a very clear directional bias in the dispersal path (i.e., it was nearly a straight line), which remained over a large scale, but wide-open areas obstructed the straightness of the path. As the distances between crossed patches increased, short-distance dispersers were found further away from their natal home range. However, there were no differences in the landscape that could explain the differences between individuals in decisions to remain philopatric or to become short- or long-distance dispersers. In addition, whereas short-distance dispersers dispersed in random directions, longdistance dispersers started to disperse in directions dominated by preferred habitat. Thus, there were behavioral differences between dispersers. Our results supported the hypotheses stating that individuals decide to disperse long or short distances before the onset of dispersal. Key words: dispersal path, dispersal direction, fragmentation, landscape structure, Pteromys volans, radio tracking, short- and long-distance. [Behav Ecol 15:564–571 (2004)]

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Young flying squirrels (Pteromys volans) dispersing in fragmented forests

Elements of the landscape, such as patches of preferred habitat, matrix between patches, and corridors linking patches, differ as movement habitat for animals. To understand how landscape structure influences the movement and thus, population dynamics of animals, clear empirical knowledge on patterns of movement is needed. The Siberian flying squirrel inhabits spruce-dominated boreal forests from Finland to eastern Siberia. Numbers of flying squirrels have declined severely in Finland in past decades, probably due to modern forestry. We studied the movement of radio-collared adult flying squirrels in preferred (spruce forest) and in matrix habitat (open areas and other habitats with trees) in Finland 1997-2000, and determined whether the woodland strips connecting patches of preferred habitat could function as ecological corridors for flying squirrels. Flying squirrels used woodland strips for inter-patch movements, but also used matrix with trees and were able to cross narrow open gaps. Males moved longer total distances and crossed edges more often than females. Males used matrix habitats for movement between spruce patches, and moved faster and more directly in the matrix than in the spruce forest. Females seldom changed spruce patches, but instead used the matrix for foraging. For both sexes probability of leaving the spruce forest patch correlated negatively with the size of the patch, but the type of connection the patch had to other patches did not affect the leaving probability. Due to efficient movement abilities of the flying squirrel and forest-dominated landscape structure of southern Finland, we suggest that conservation acts for maintaining viable populations of flying squirrels should focus on the quality of managed forest and the area of suitable breeding habitat (i.e. on habitat loss), but not necessarily on ecological corridors.

Movements of the flying squirrel Pteromys volans in corridors and in matrix habitat

1. Variation in behaviours involved in habitat selection is important for several evolutionary and ecological processes. For example, habitat use during dispersal may differ from breeding habitat use, and for dispersers the scale of habitat familiarity is determined by exploratory behaviour. We studied habitat use and exploration of 56 radio-collared juvenile flying squirrels Pteromys volans L. within natal home range and during dispersal, and compared habitat use between juveniles and 37 adults within breeding home range. 2. Before dispersal, young flying squirrels actively moved around the natal site. Surprisingly, long-distance dispersers explored less than short-distance dispersers, but philopatric individuals explored similar distances as dispersers. Females explored less than males, although females are the more dispersive sex in flying squirrels. 3. For most of the individuals the settlement area was unfamiliar due to long dispersal distance. Consequently, direction and distance of exploration were not very strong predictors of settlement location. However, individuals familiar with the settlement area concentrated exploration to that area. Exploration did not correlate with short-term survival. 4. Dispersers preferred breeding habitat while dispersing, but were found more often in matrix habitat than juveniles within natal, or adults within breeding, home ranges. 5. We conclude that familiarity does not determine settlement as much as, for example, availability of the habitat for flying squirrels. Based on our results, it also seems clear that data on adult habitat use are not enough to predict habitat use of dispersing individuals. In addition, our results support the recent view that short- and long-distance dispersers may need to be analysed separately in ecological and evolutionary analyses.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2656.2006.01168.x

Habitat exploration and use in dispersing juvenile flying squirrels.

Allozyme variation at the phosphoglucose isomerase (PGI) locus in the Glanville fritillary butterfly (Melitaea cinxia) is associated with variation in flight metabolic rate, dispersal rate, fecundity and local population growth rate. To map allozyme to DNA variation and to survey putative functional variation in genomic DNA, we cloned the coding sequence of Pgi and identified nonsynonymous variable sites that determine the most common allozyme alleles. We show that these single-nucleotide polymorphisms (SNPs) exhibit significant excess of heterozygotes in field-collected population samples as well as in laboratory crosses. This is in contrast to previous results for the same species in which other allozymes and SNPs were in Hardy–Weinberg equilibrium or exhibited an excess of homozygotes. Our results suggest that viability selection favours Pgi heterozygotes. Although this is consistent with direct overdominance at Pgi, we cannot exclude the possibility that heterozygote advantage is caused by the presence of one or more deleterious alleles at linked loci.

/pdf/fitness-differences-associated-with-pgi-snp-genotypes-in-the-2u1qjgo016.pdf

Ilpo K. Hanski

Papers

Home-range size, movements, and nest-site use in the siberian flying squirrel, pteromys volans

Young flying squirrels (Pteromys volans) dispersing in fragmented forests

Movements of the flying squirrel Pteromys volans in corridors and in matrix habitat

Habitat exploration and use in dispersing juvenile flying squirrels.

Fitness differences associated with Pgi SNP genotypes in the Glanville fritillary butterfly (Melitaea cinxia).