FLUCTUATING ASYMMETRY AS AN INDICATOR OF ENVIRONMENTAL STRESS IN SMALL MAMMALS.
INTRODUCTIONEnvironmental stress can have significant detrimental effects on animal populations (Lazic et al. 2013, 2015). Several authors have proposed that obtaining a sensitive indicator of stress is crucial for conservation biologists, since it can be used to detect signs of population disturbance before components of fitness have been affected and irreversible demographic damages have occurred (Leary & Allendorf, 1989; Teixeira et al., 2006; Delgado-Acevedo & Restrepo, 2008; Beasley et al., 2013; Lazic et al., 2013). Traditional biomarkers (molecular and cellular exams, heat shock proteins, hemoglobin adducts, etc.) may be reliable, but they are expensive and may not be applicable across species (Helle et al. 2011; Lazic et al. 2013). The developmental stability of an organism is reflected in its ability to produce an 'ideal' form under a particular set of conditions. The lower its stability, the greater the likelihood it will depart from this 'ideal' form. Ideal forms are rarely known a priori, but bilateral structures in bilaterally symmetrical organisms offer a precise expectation of symmetry against which departures may be compared. Thus, the study of bilateral traits provides a very convenient method for assessing deviations from the norm and studying the factors that may influence such deviations (Palmer & Strobeck 1986; Palmer 1994). The developmental precision that produces bilaterally symmetric structures may be negatively affected by a wide range of environmental and/or genetic stressors (Zakharov 1992).
Subtle departures from symmetry are most commonly described by frequency distributions of right-left sides of a trait (Palmer 1994). Such frequency distributions usually exhibit one of the following three patterns: directional asymmetry, antisymmetry and fluctuating asymmetry. Directional asymmetry is characterized by a normal distribution that is not centered around zero but is significantly biased towards larger traits either on the right or the left side (Fig. 1A). Examples include lateral placement of organs such as the heart and liver in humans and muscle-size asymmetries in birds (Markow 1995). Antisymmetry is distinguished by a platykurtic (broad peaked) or bimodal distribution of right-left differences around a zero mean (Palmer & Strobeck 2003) (Fig. 1B). A classic example is the claw size in male fiddler crabs. Fluctuating asymmetry is defined as small and random deviations from perfect bilaterally symmetrical traits (Ludwig 1932; Palmer & Strobeck 1986) (Fig. 1C). This asymmetry has normal distribution with zero mean. Of these three asymmetries, fluctuating asymmetry is considered as the only form of asymmetry that can serve as a useful indicator of environmental/genetic stress (Palmer & Strobeck 1986; Leary & Allendorf 1989; Leung & Forbes 1997; Polak & Taylor 2007).
The study of fluctuating asymmetry per se began with the work of a small group of researchers, including Ludwig (1932), Thoday (1953, 1956, 1958), Van Valen (1962), and Soule (1966, 1967). Early perceptions of the importance of fluctuating asymmetry were summarized by Jackson (1973), who pointed out that the level of fluctuating asymmetry can be considered as a measure of buffering capacity in development, since any non-consistent differences between paired structures could be developmental accidents. The attractiveness of fluctuating asymmetry as a potential biomarker stems from its broad application across biological systems and stressors. An additional advantage is the relative ease in taking trait measurements compared to other biomarkers that require more costly equipment or reagents (Leung et al. 2003). There are two general approaches to study fluctuating asymmetry: geometric morphometrics that provides information about traits morphology using shape and size, and linear measurements that include metrical measurements (lengths) or meristic traits, both on the left and right sides of organisms (Van Valen 1962; Palmer & Strobeck 1986). The geometric morphometrics methodology has been more recently developed and its fundamental advances over traditional approaches (linear measurements) are due to powerful statistical methods designed for the analysis of shape data rather than the use of standard multivariate methods (Rohlf & Corti 2000).
Small mammals have been widely used as model species in ecological studies to infer environmental disturbances because of their wide range of characteristics (Wolff & Sherman 2007). These organisms inhabit all continents except Antarctica and they occur in terrestrial, subterranean, arboreal, and aquatic habitats. They are crucial in their contribution to well-structured food webs (Salamolard et al. 2000; Michel et al. 2006; Baraibar et al. 2009), the consumption and dispersal of plant products (Carey et al. 1999) and mycorrhizal fungi (Maser et al. 1978) and the consumption and control of invertebrates (Elkinton et al. 1996). Most of them are very prolific, have a short life cycle and are relatively easy to capture (Steinmann & Priotto 2011; Korpimaki & Norrdahl 2013). Besides, they constitute a diverse group, with different degrees of habitat specialization, social and mating systems. All these characteristics make this group of mammals a very convenient model for ecological studies.
Currently, there is a challenge to identify vulnerable populations before irreversible demographic/genetic damage takes place. Obtaining of a reliable, general and easy-to-use biomarker of health and wellbeing of individuals that can be applied in ecological studies is therefore important. The aim of this study was to show the relevance of fluctuating asymmetry as a tool to measure environmental stress in ecological studies, with emphasis on small mammals. We summarized four decades of studies where this index was used to assess the effects of environmental disturbances on small mammals.
DATA AND METHODS
Data were compiled with Google Scholar (Mountain View, CA) using two keywords: "fluctuating asymmetry" and "small mammals". We also searched in the reference lists of selected articles additional studies that met our inclusion criteria. We applied other selection criteria to include the papers in this review. Due to the fact that the small mammals are not classified as a taxonomic group we included in this group any species of mammals with adult weights up to 1 kg. We selected only articles in English and with ecological objectives published from 1980 to 2017.
RESULTS AND DISCUSSION
We selected 27 articles (Table 1) that met our selection criteria. This small number of articles demonstrates that fluctuating asymmetry is not widely used in ecological studies of small mammal. The highest number of articles in this topic was registered between 2000-2004 (8 articles) and 2015-2017 (5 articles). We found studies carried out in several parts of the world, but most were developed in Europe (20 articles), six in the Americas and only one in Africa. In relation to those studies developed in the Americas, only two were carried out in the Neotropical region (Argentina and Brazil) and the others in United States and Canada (three and one articles respectively). The Neotropical region has suffered major transformations due to land use change and associated negative impacts on biodiversity in the last decades (Ceballos & Garcia 1995; Lowe et al. 2005; Bedano & Dominguez 2016); the lack of fluctuating asymmetry studies in small mammals in this region is remarkable.
Regardless of the approach used to analyze fluctuating asymmetry (linear measurements or geometric morphometrics) the dominant focal species were rodents and shrews. Of the total number of studies, 20 applied linear measurements, six geometric morphometrics and only one used both methodologies. Linear measurement studies used metrical o meristic measures indifferently. The oldest articles applied linear measurements and since 2002 some authors started to use geometric morphometrics. The results obtained from geometric morphometrics and linear measurements were similar with positive association between fluctuating asymmetry and environmental stress in more than 70% of the studies. Thus, both approaches would allow a proper analysis of fluctuating asymmetry in ecological studies of small mammal.
Several authors propose that multiple traits are necessary to test differences in developmental instability in linear measurement analyses (Leary & Allendorf, 1989; Palmer, 1994). Of the total of 21 linear measurement studies, 19 used more than five traits, 15 of which found a positive association between fluctuating asymmetry and environmental stress. On the other hand, Wauters et al. (1996) and Coda et al. (2016) used only one trait and found a positive association between environmental stress and developmental instability. In these studies, the authors used the length of right and left hind feet to assess fluctuating asymmetry in live red squirrels and cricetid rodents. The absence of fluctuating asymmetry could not be accurately established using only one trait.
The environmental stress factors were natural (9 studies) or anthropogenic (18 studies). The natural factors included differences in habitat suitability and only one study analyzed natural disasters (i.e., tornados) (Table 1). In relation to anthropogenic factors, most of the studies evaluated the effect of radiation emitted by nuclear power plants and waste from industries/ mining (five and eight articles respectively). We registered only two studies about the effect of agriculture on developmental instability in small mammals (Table 1), in spite of the fact that agriculture is among the predominant global changes of the last 100 years (Matson et al. 1997) and that it has led to a widespread decline in biodiversity (Benton et al. 2003).
The studies considered used measures obtained from samples of barn owl pellets, scientific collections and animals captured in field surveys that were sacrificed or not. We found only one study in which teeth obtained from barn owl pellets were used to assess fluctuating asymmetry (Amarena et al. 1993). Taking into account the small number of studies about fluctuating asymmetry in small mammals, scientific collections provide a large amount of information for studies of developmental instability (e.g. Sanchez-Char di et al. 2013; Askay et al. 2014; Maestri et al. 2015). Besides, it is possible to analyze the effects of environmental changes on individual development instability at greater spatial and time scales, which become important in populations that have undergone decreases in their abundances. Museum specimens allow the use of both geometric morphometrics and linear measurements. We found that most studies (19) used sacrificed individuals to take measurements for fluctuating asymmetry analyses, whereas only four used live animals (Table 1). Studies based on sacrificed animals used both geometric morphometrics and linear measurements, whereas only linear measurements were used with live animals. Regardless of whether measurements have been obtained from sacrificed or live animals, positive associations between developmental instability and environmental stress was observed in most studies (Table 1).
The use of exomorphological traits seem to be a useful tool to assess the relationship between developmental instability and environmental stress, since it can be used with live animals, is easy to obtain and shows similar results to those obtained from measurements of internal traits of sacrificed animals. However, to increase accuracy several measurement of each trait should be taken (repeatability of the measure) and as much traits as possible should be considered.
PERSPECTIVES
Few studies have evaluated the relationship between developmental instability (using fluctuating asymmetry as a proxy) and environmental stress in small mammals. These studies clearly show that fluctuating asymmetry is a tool to assess this relationship, allowing us to suggest that this approach will prove to be increasingly important in future ecological studies.
Fluctuating asymmetry of exomorphological traits may provide a valuable indicator of environmental stress in small mammals. Particularly, the use of non-invasive technique in live wild animals using these traits would be a valuable and inexpensive tool for studies in conservation biology as an alternative to sacrificing animals. To our knowledge, there are no studies that use geometric morphometrics with exomorphological measurements to evaluate fluctuating asymmetry. However, it would be possible to implement this approach with these traits, since they have been already used in studies of leg shape and locomotion in rodents (Rivas & Linares 2006).
This review shows the importance of including fluctuating asymmetry in ecological studies as a reliable, cheap and fast biological indicator of the effect of environmental stress on mammals, especially in the Neotropical region, where there is a noticeable absence of these kinds of studies.
Recibido 10 agosto 2016. Aceptado 20 de octubre 2017. Editor invitado: J. Priotto. Editor asociado: E. Lessa
ACKNOWLEDGMENTS
We are grateful to Enrique Lessa and the reviewers for their helpful comments and suggestions on improving this manuscript.
LITERATURE CITED
Amarena, C., L. CONTOLI, & M. Cristaldi. 1993. Coenotic structure, skull asymmetries and other morphological anomalies in small mammals near an electronuclear power plant. Hystrix 5:31-46.
Askay, M. A., J. C. Kostelnick, J. C. Kerbis Peterhans, & S. S. Loew. 2014. Environmental stress as an indicator of anthropogenic impact across the African Albertine Rift: a case study using museum specimens. Biodiversity and Conservation 23:2221-2237.
Badyaev, A. V, K. R. Foresman, & M. V Fernandes. 2000. Stress and developmental stability: vegetation removal causes increased fluctuating asymmetry in shrews. Ecological Society of America 81:336-345.
Baraibar, B., P. R. Westerman, E. Carrion, & J. Recasens. 2009. Effects of tillage and irrigation in cereal fields on weed seed removal by seed predators. Journal of Applied Ecology 46:380-387.
Beasley, D. A. E., A. Bonisoli-Alquati, & T. A. Mousseau. 2013. The use of fluctuating asymmetry as a measure of environmentally induced developmental instability: a meta-analysis. Ecological Indicators 30:218-226.
Bedano, J. C., & A. Dominguez. 2016. Large-scale agricultural management and soil meso--and macrofauna conservation in the Argentine Pampas. Sustainability 8:1-25.
Benton, T. G., J. A. Vickery, & J. D. Wilson. 2003. Farmland biodiversity: is habitat heterogeneity the key? Trends in Ecology and Evolution 18:182-188.
Carey, A. B., J. Kershner, B. Biswell, & L. D. de Toledo. 1999. Ecological scale and forest development: Squirrels, dietary fungi, and vascular plants in managed and unmanaged forest. Wildlife Monographs 142:1-71.
Ceballos, G., & A. Garcia. 1995. Conserving neotropical biodiversity: the role of dry forests in western Mexico. Conservation Biology 9:1349-1353.
Coda, J. A., D. Gomez, J. J. Martinez, A. R. Steinmann, & J. W. Priotto. 2016. The use of fluctuating asymmetry as a measure of farming practice effects in rodents: a species-specific response. Ecological Indicators 70:269-275.
Delgado-Acevedo, J., & C. Restrepo. 2008. The contribution of habitat loss to changes in body size, allometry, and bilateral asymmetry in two Eleutherodactylus frogs from Puerto Rico. Conservation Biology 22:773-782.
Elkinton, J. S. et al. 1996. Interactions among gypsy moths, white-footed mice, and acorns. Ecology 77:2332-2342.
Gileva, E. A., & D. Y. Nokhrin. 2001. Fluctuating asymmetry in cranial measurements of east European voles (Microtus rossiaemeridionalis Ognev, 1924) from the zone of radioactive contamination. Russian Journal of Ecology 32:44-49.
Helle, S., E. Huhta, P. Suorsa, & H. Hakkarainen. 2011. Fluctuating asymmetry as a biomarker of habitat fragmentation in an area-sensitive passerine, the Eurasian treecreeper (Certhia familiaris). Ecological Indicators 11:861-867.
Hopton, M. E., G. N. Cameron, M. J. Cramer, M. Polak, & G. W. Uetz. 2009. Live animal radiography to measure developmental instability in populations of small mammals after a natural disaster. Ecological Indicators 9:883-891.
Jackson, J. F. 1973. A search for the population asymmetry parameter. Systematic Zoology 22:166-170.
Knopper, L. D., & P. Mineau. 2004. Organismal effects of pesticide exposure on meadow voles (Microtus pennsylvanicus) living in golf course ecosystems: developmental instability, clinical hematology, body condition, and blood parasitology. Environmental Toxicology and Chemistry 23:1512-1519.
Korpimaki, E., & K. Norrdahl. 2013. Numerical and functional responses of kestrels, short-eared owls, and long-eared owls to vole densities. Ecology 72:814-826.
LaziC, M. M., M. A. Carretero, J. Crnobrnja-Isailovic, & A. Kaliontzopoulou. 2015. Effects of environmental disturbance on phenotypic variation: an integrated assessment of canalization, developmental stability, modularity, and allometry in lizard head shape. The American Naturalist 185:44-58.
Lazic, M. M., A. Kaliontzopoulou, M. A. Carretero, & J. Crnobrnja-Isailovic. 2013. Lizards from urban areas are more asymmetric: using fluctuating asymmetry to evaluate environmental disturbance. PloS one 8:e84190.
Leary, R. F., & F. W. Allendorf. 1989. Fluctuating asymmetry as an indicator of stress: implications for conservation biology. Trends in Ecology and Evolution 4:214-217.
Leung, B., & M. R. Forbes. 1997. Modelling fluctuating asymmetry in relation to stress and fitness. Oikos 78:397-405.
Leung, B., L. D. Knopper, & P. Mineau. 2003. A critical assessment of the utility of fluctuating asymmetry as a bioindicator of anthropogenic stress. Developmental instability: causes and consequences (M. Polak, ed.). Oxford University Press, New York.
Lowe, A. J., D. Boshier, M. Ward, C. F. E. Bacles, & C. Navarro. 2005. Genetic resource impacts of habitat loss and degradation; reconciling empirical evidence and predicted theory for neotropical trees. Heredity 95:255-273.
Ludwig, W. 1932. Das rechts-links problem im teirreich und beim menschen. Springer, Berlin.
Maestri, R., R. Fornel, D. Galiano, & T. R. O. de Freitas. 2015. Niche suitability affects development: skull asymmetry increases in less suitable areas. Plos One 10:e0122412.
Marchand, H., G. Paillat, S. Montuire, & A. Butet. 2003. Fluctuating asymmetry in bank vole populations (Rodentia, Arvicolinae) reflects stress caused by landscape fragmentation in the Mont-Saint-Michel Bay. Biological Journal of the Linnean Society 80:37-44.
Markow, T. A. 1995. Evolutionary ecology and developmental instability. Annual Review of Entomology 40:105-120.
Maser, C., J. M. Trappe, & R. A. Nussbaum. 1978. Fungal-small mammal interrelationships with emphasis on oregon coniferous forest. Ecology 59:799-809.
Matson, P. A., W. J. Parton, A. G. Power, & M. J. Swift. 1997. Agricultural intensification and ecosystem properties. Science 277:504-509.
Michel, N., F. G. Burel, & A. Butet. 2006. How does landscape use influence small mammal diversity, abundance and biomass in hedgerow networks of farming landscapes? Acta Oecologica 30:11-20.
Nunes, A. C., J. C. Auffray, & M. L. Mathias. 2001. Instability in a riparian population of the Algerian mouse (Mus spretus) associated with a heavy metal-polluted area in central Portugal. Environmental Contamination and Toxicology 41:515-521.
Oleksyk, T. K., J. M. Novak, J. R. Purdue, S. P. Gashchak, & M. H. Smith. 2004. High levels of fluctuating asymmetry in populations of Apodemus flavicollis from the most contaminated areas in Chornobyl. Journal of Environmental Radioactivity 73:1-20.
Oleksyk, T. K., M. H. Smith, J. M. Novak, & J. R. Purdue. 2002. Problems with developmental stability in two rodent species from Chornobyl. Radioprotection-Colloques 37:859-864.
Owen, R. D., & K. McBee. 1990. Analysis of asymmetry and morphometric. The Texas Journal of Science 42:319-332.
Palmer, A. R. 1994. Fluctuating asymmetry analyses: a primer. Developmental Instability: its origins and evolutionary implications (T. A. Markow, ed.). Kluwer, Netherlands.
Palmer, A. R., & C. Strobeck. 1986. Fluctuating asymmetry: measurement, analysis, patterns. Annual Review of Ecology and Systematics 17:391-421.
Palmer, A. R., & C. Strobeck. 2003. Fluctuating asymmetry analyses revisited. Developmental Instability (DI): Causes and Consequences (M. Polak, ed.). Oxford University Press, New York.
Pankakoski, E. 1985. Epigenetic asymmetry as an ecological indicator in muskrats. Journal of Mammalogy 66:52-57.
Polak, M., & P. W. Taylor. 2007. A primary role of developmental instability in sexual selection. Proceedings of the Royal Society B 274:3133-3140.
Rivas, B. A., & O. J. Linares. 2006. Cambios en la forma de la pata posterior entre roedores sigmodontinos segun su locomocion y habitat. Mastozoologia Neotropical 13:205-215.
Rohlf, F. J., & M. Corti. 2000. Use of two-block partial least-squares to study covariation in shape. Systematic Biology 49:740-753.
Salamolard, M., A. Butet, A. Leroux, & V. Bretagnolle. 2000. Responses of an avian predator to variations in prey density at a temperate latitude. Ecology 81:24282441.
Sanchez-Chardi, A., M. Garcia-Pando, & M. J. Lopez-Fuster. 2013. Chronic exposure to environmental stressors induces fluctuating asymmetry in shrews inhabiting protected mediterranean sites. Chemosphere 93:916-923.
Shadrina, E. G., & Y. Vol'pert. 2014. Developmental instability of the organism as a result of pessimization of environment under anthropogenic. Russian Journal of Developmental Biology 45:117-126.
Shadrina, E. G., & Y. Vol'pert. 2016. Fluctuating asymmetry of craniological features of small mammals as a reflection of heterogeneity of natural populations. Symmetry 8:1-16.
Soule, M. 1966. Trends in the insular radiation of a lizard. The American Naturalist 100:47-64.
Soule, M. 1967. Phenetics of natural populations. II. Asymmetry and evolution in a lizard. The American Naturalist 101:141-160.
Steinmann, A. R., & J. W. Priotto. 2011. El raton maicero y su comportamiento. Ciencia Hoy 20:53-60.
Teixeira, C. P., A. Hirsch, H. Perini, & R. J. Young. 2006. Marsupials from space: fluctuating asymmetry, geographical information systems and animal conservation. Proceedings of the Royal Society B 273:1007-1012.
Thoday, J. M. 1953. Components of fitness. Symposia of the Society for Experimental Biology 7:96-113.
Thoday, J. M. 1956. Balance, Heterozygosity and developmental stability. Cold Spring Harbor Symposia on Quantitative Biology 21:318-326.
Thoday, J. M. 1958. Homeostasis in a selection experiment. Heredity 12:401-415.
Van Valen, L. 1962. A study of fluctuating asymmetry. Evolution 16:125-142.
Vasil'ev, A. G., & I. A. Vasil'eva. 1995. Non-metric variation in red vole populations within the East-Ural Radioactive Track (EURT) zone. Acta Theriologica 3:55-64.
Vasil'ev, A. G., I. A. Vasil'eva, & V. N. Bol'shakov. 1996. Phenetic monitoring of populations of the northern red-backed vole (Clethrionomys rutilus Pall.) in the zone of the eastern Ural radioactive trace. Russian Journal of Ecology 27:117-124.
Velickovic, M. 2004. Chromosomal aberrancy and the level of fluctuating asymmetry in black-striped mouse (Apodemus agrarius): effects of disturbed environment. Hereditas 140:112-122.
Velickovic, M. 2007. Measures of the developmental stability, body size and body condition in the black-striped mouse (Apodemus agrarius) as indicators of a disturbed environment in northern Serbia. Belgian Journal of Zoology 137:147-156.
Wauters, L. A., A. A. Dhondt, H. Knothe, & D. T. Parkin. 1996. Fluctuating asymmetry and body size as indicators of stress in red squirrel populations in woodland fragments. The Journal of Applied Ecology 33:735-740.
Wojcik, J. M., P. D. Polly, A. M. Wojcik, & M. D. Sikorski. 2007. Morphometric variation of the common shrew, Sorex araneus, in different habitats. Russian Journal of Theriology 6:43-49.
Wolff, R. J., & P. W. Sherman. 2007. Rodent societies as model systems. Pp. 3-7 in Rodent societies: an ecological and evolutionary perspective (R. J. Wolff & P. W. Sherman, eds.). University of Chicago Press, Chicago, United States of America.
Yalkovskaya, L. E., M. A. Fominykh, S. V Mukhacheva, Y. A. Davydova, & A. V Borodin. 2016. Fluctuating asymmetry of rodent cranial structures in an industrial pollution gradient. Russian Journal of Ecology 47:281-288.
Zakharov, V. M. 1992. Population phenogenetics: analysis of developmental stability in natural populations. Acta Zoologica Fennica 191:17-30.
Zakharov, V. M., D. V Demin, A. S. Baranov, V. I. Borisov, A. V Valetsky, & B. I. Sheftel. 1997a. Developmental stability and population dynamics of shrews Sorex in central Siberia. Acta Theriologica 4:41-48.
Zakharov, V. M., E. Pankakoski, & B. I. Sheftel. 1997b. Phenotypic diversity and population dynamics: another look (with particular reference to the common shrew Sorex araneus). Acta Theriologica 4:57-66.
Zakharov, V. M., E. Pankakoski, B. I. Sheftel, A. Peltonen, & I. Hanski. 1991. Developmental stability and population dynamics in the common shrew, Sorex araneus. The American Naturalist 138:797-810.
Jose A. Coda (1), Juan Jose Martinez (2), Andrea R. Steinmann (1), Jose Priotto (1), and M. Daniela Gomez (1)
(1) Universidad Nacional de Rio Cuarto, Rio Cuarto, Argentina. CONICET (Consejo Nacional de Investigaciones Cientificas y Tecnicas), Argentina. [Correspondencia: <[email protected]>]
(2) Instituto de Ecorregiones Andinas (INECOA), Universidad Nacional de Jujuy, CONICET, San Salvador de Jujuy, Argentina.
Caption: Fig. 1. Three common distributions of right-left in bilateral traits: A) directional asymmetry, B) antisymmetry, C) fluctuating asymmetry. f: frequency of the measured trait.
Table 1
List of the articles selected to evaluate the use of fluctuating
asymmetry as a tool to measure environmental stress in ecological
studies on small mammals in chronological order.
Articles authors (Year) Animals source
Pankakoski (1985) Capture and sacrifice
Owen & McBee (1990) Capture and sacrifice
Zakharov et al. (1991) Capture and sacrifice
Amarena et al. (1993) Barn owls pellets
Vasil'ev & Vasil'eva (1995) Capture and sacrifice
Vasil'ev et al. (1996) Capture and sacrifice
Wauters et al. (1996) Capture without sacrifice
Zakharov et al. (1997a) Capture and sacrifice
Zakharov et al. (1997b) Capture and sacrifice
Badyaevet et al. (2000) Capture and sacrifice
Nunes et al. (2001) Capture and sacrifice
Gileva & Nokhrin (2001) Capture and sacrifice
Oleksyk et al. (2002) Capture and sacrifice
Marchand et al. (2003) Capture and sacrifice
Knopper & Mineau (2004) Capture without sacrifice
Oleksyk et al. (2004) Capture and sacrifice
VeliCkovic (2004) Capture and sacrifice
VeliCkovic (2007) Capture and sacrifice
Wojcik et al. (2007) Capture and sacrifice
Hopton et al. (2009) Capture without sacrifice
Sanchez-Chardi et al. (2013) Specimens from collections
Askay et al. (2014) Specimens from collections
Shadrina & Volpert (2014) Capture and sacrifice
Maestri et al. (2015) Specimens from collections
Coda et al. (2016) Capture without sacrifice
Shadrina & Volpert (2016) Capture and sacrifice
Yalkovskaya et al. (2016) Capture and sacrifice
Articles authors (Year) Approach
(trait) (a)
Pankakoski (1985) LM (meristic)
Owen & McBee (1990) LM (metrical)
Zakharov et al. (1991) LM (metrical and
meristic)
Amarena et al. (1993) LM (metrical)
Vasil'ev & Vasil'eva (1995) LM (meristic)
Vasil'ev et al. (1996) LM (meristic)
Wauters et al. (1996) LM (metrical)
Zakharov et al. (1997a) LM (meristic)
Zakharov et al. (1997b) LM (meristic)
Badyaevet et al. (2000) LM (metrical)
Nunes et al. (2001) LM (metrical)
Gileva & Nokhrin (2001) LM (metrical)
Oleksyk et al. (2002) GM
Marchand et al. (2003) GM and LM (metrical)
Knopper & Mineau (2004) LM (metrical)
Oleksyk et al. (2004) GM
VeliCkovic (2004) LM (metrical)
VeliCkovic (2007) LM (meristic)
Wojcik et al. (2007) LM (meristic)
Hopton et al. (2009) LM (metrical)
Sanchez-Chardi et al. (2013) GM
Askay et al. (2014) GM
Shadrina & Volpert (2014) LM (meristic)
Maestri et al. (2015) GM
Coda et al. (2016) LM (metrical)
Shadrina & Volpert (2016) LM (meristic)
Yalkovskaya et al. (2016) GM
Articles authors (Year) Stressor Results
(b)
Pankakoski (1985) Habitat suitability +
(natural causes)
Owen & McBee (1990) Industries/Mining -
Zakharov et al. (1991) Habitat suitability +
(natural causes)
Amarena et al. (1993) Industries/Mining +
Vasil'ev & Vasil'eva (1995) Radiation -
Vasil'ev et al. (1996) Radiation +
Wauters et al. (1996) Habitat suitability +
(human activities)
Zakharov et al. (1997a) Habitat suitability +
(natural causes)
Zakharov et al. (1997b) Habitat suitability -
(natural causes)
Badyaevet et al. (2000) Habitat suitability +
(human activities)
Nunes et al. (2001) Industries/Mining +
Gileva & Nokhrin (2001) Radiation +
Oleksyk et al. (2002) Radiation +
Marchand et al. (2003) Habitat suitability partial
(human activities)
Knopper & Mineau (2004) Pesticides -
Oleksyk et al. (2004) Radiation +
VeliCkovic (2004) Industries/Mining partial
VeliCkovic (2007) Industries/Mining +
Wojcik et al. (2007) Habitat suitability +
(natural causes)
Hopton et al. (2009) Natural disasters +
Sanchez-Chardi et al. (2013) Industries/Mining +
Askay et al. (2014) Habitat suitability -
Shadrina & Volpert (2014) Industries/Mining +
Maestri et al. (2015) Habitat suitability +
(natural causes)
Coda et al. (2016) Habitat suitability +
(human activities)
Shadrina & Volpert (2016) Habitat suitability +
(natural causes)
Yalkovskaya et al. (2016) Industries/Mining +
Articles authors (Year) Focal specie
group
Pankakoski (1985) Rodent
Owen & McBee (1990) Rodent
Zakharov et al. (1991) Shrew
Amarena et al. (1993) Rodent and shrew
Vasil'ev & Vasil'eva (1995) Rodent
Vasil'ev et al. (1996) Rodent
Wauters et al. (1996) Rodent
Zakharov et al. (1997a) Shrew
Zakharov et al. (1997b) Shrew
Badyaevet et al. (2000) Shrew
Nunes et al. (2001) Rodent
Gileva & Nokhrin (2001) Rodent
Oleksyk et al. (2002) Rodent
Marchand et al. (2003) Rodent
Knopper & Mineau (2004) Rodent
Oleksyk et al. (2004) Rodent
VeliCkovic (2004) Rodent
VeliCkovic (2007) Rodent
Wojcik et al. (2007) Shrew
Hopton et al. (2009) Rodent
Sanchez-Chardi et al. (2013) Shrew
Askay et al. (2014) Rodent
Shadrina & Volpert (2014) Rodent and shrew
Maestri et al. (2015) Rodent
Coda et al. (2016) Rodent
Shadrina & Volpert (2016) Rodent and shrew
Yalkovskaya et al. (2016) Rodent
Articles authors (Year) Study area
(country)
Pankakoski (1985) Finland
Owen & McBee (1990) EEUU
Zakharov et al. (1991) Russia, Finland
Amarena et al. (1993) Italy
Vasil'ev & Vasil'eva (1995) Russia
Vasil'ev et al. (1996) Russia
Wauters et al. (1996) Belgium
Zakharov et al. (1997a) Russia
Zakharov et al. (1997b) Russia
Badyaevet et al. (2000) EEUU
Nunes et al. (2001) Portugal
Gileva & Nokhrin (2001) Russia
Oleksyk et al. (2002) Ukraine
Marchand et al. (2003) France
Knopper & Mineau (2004) Canada
Oleksyk et al. (2004) Ukraine
VeliCkovic (2004) Serbia
VeliCkovic (2007) Serbia
Wojcik et al. (2007) Poland
Hopton et al. (2009) EEUU
Sanchez-Chardi et al. (2013) Spain
Askay et al. (2014) Africa (5 countries)
Shadrina & Volpert (2014) Russia
Maestri et al. (2015) Brazil
Coda et al. (2016) Argentina
Shadrina & Volpert (2016) Russia
Yalkovskaya et al. (2016) Russia
(a) Approaches to study FA: geometric morphometrics (GM) and linear
measurements (LM) that include metrical or meristic measurements.
(b) Positive and negative relationships between FA levels and
stressors are indicated with + (plus) and -(minus), respectively.
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