Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

Evans, Karl L.; Lennon, Jack J.; Gaston, Kevin J.

doi:10.5751/ace-00155-020207

Cited by 7 publications

(7 citation statements)

References 69 publications

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“…We can measure isolation as the distance between areas or as an isolation index (Hanski, 1994;Hanski & Thomas, 1994;Hanski & Kuussaari, 1995), which also takes into account the size of the closest area or island. Available energy or productivity, as measured by, say, climate (temperature and precipitation), photosynthesis or normalized difference vegetation index (NDVI) is probably the factor most regularly considered as a second predictor (see Wright, 1983;Dodson, 1992;Storch et al, 2005;Kalmar & Currie, 2006;Evans et al, 2007). A simple linear trivariate regression model is expressed as…”

Section: Trivariate Modelsmentioning

confidence: 99%

“…Multiple regressions assessing the effect of two or more independent variables (transformed or not) on species numbers are also very common (e.g. Dodson, 1992;Adler & Lauenroth, 2003;Triantis et al, 2003;Adler et al, 2005;Storch et al, 2005;Kalmar & Currie, 2006, 2007Ulrich, 2006;Evans et al, 2007).…”

Section: Trivariate Modelsmentioning

confidence: 99%

“…Both models are sigmoid, but the Archibald model, owing to its inflection point falling at the origin of the axes, represents an alternative to convex models rather than other sigmoid models. normalized difference vegetation index (NDVI) is probably the factor most regularly considered as a second predictor (see Wright, 1983;Dodson, 1992;Storch et al, 2005;Kalmar & Currie, 2006;Evans et al, 2007). A simple linear trivariate regression model is expressed as…”

Section: Trivariate Modelsmentioning

confidence: 99%

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Shapes and functions of species–area curves (II): a review of new models and parameterizations

Tjørve¹

2009

Journal of Biogeography

142

156

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This paper has extended and updated my earlier list and analysis of candidate models used in theoretical modelling and empirical examination of species–area relationships (SARs). I have also reviewed trivariate models that can be applied to include a second independent variable (in addition to area) and discussed extensively the justifications for fitting curves to SARs and the choice of model. There is also a summary of the characteristics of several new candidate models, especially extended power models, logarithmic models and parameterizations of the negative‐exponential family and the logistic family. I have, moreover, examined the characteristics and shapes of trivariate linear, logarithmic and power models, including combination variables and interaction terms. The choice of models according to best fit may conflict with problems of non‐normality or heteroscedasticity. The need to compare parameter estimates between data sets should also affect model choice. With few data points and large scatter, models with few parameters are often preferable. With narrow‐scale windows, even inflexible models such as the power model and the logarithmic model may produce good fits, whereas with wider‐scale windows where inflexible models do not fit well, more flexible models such as the second persistence (P2) model and the cumulative Weibull distribution may be preferable. When extrapolations and expected shapes are important, one should consider models with expected shapes, e.g. the power model for sample area curves and the P2 model for isolate curves. The choice of trivariate models poses special challenges, which one can more effectively evaluate by inspecting graphical plots.

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Section: Trivariate Modelsmentioning

confidence: 99%

Section: Trivariate Modelsmentioning

confidence: 99%

Section: Trivariate Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Shapes and functions of species–area curves (II): a review of new models and parameterizations

Tjørve¹

2009

Journal of Biogeography

142

156

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“…In so doing we take the effects of temperature, altitude, and area into account; however, we do not assess their influence as this is beyond the scope of this study and would duplicate existing research (Lennon et al 2000(Lennon et al , 2001Evans et al 2005Evans et al , 2007b. In so doing we take the effects of temperature, altitude, and area into account; however, we do not assess their influence as this is beyond the scope of this study and would duplicate existing research (Lennon et al 2000(Lennon et al , 2001Evans et al 2005Evans et al , 2007b.…”

Section: Analysesmentioning

confidence: 99%

Statutory protected areas and avian species richness in Britain

2009

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An effective portfolio of protected areas should, all else being equal, give rise to positive relationships between the amount of protected land in a region and the numbers of species present. Tests of this prediction are, however, extremely scarce, and most do not control for the potentially confounding effects of environmental factors that influence broad geographic trends in biodiversity. Here, we document the form of the relationship between species richness and coverage by protected areas using the British avifauna as a case study. We contrast relationships that arise for breeding and wintering assemblages, considering both all species collectively and threatened species only. We use spatially explicit multiple regression analyses that take into account environmental factors previously shown to exert a marked influence on avian species richness in Britain (temperature and altitude). Avian species richness and the amount of protected land are consistently positively correlated with each other, and the slopes of these relationships do not differ between assemblages (breeding/wintering and all species/threatened species). Explanatory power is, however, very weak which may be indicative of the ability of conservation measures in the wider landscape to maintain avian species richness, reducing any distinctive influence of protected areas.

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“…Therefore, the extent to which reported differences between urban and rural populations generalise is poorly understood and studies are required that include a greater number of sites spread throughout a species’ range. This would also give an opportunity to examine how urbanisation has influenced some of the classical patterns in ecology, such as spatial variation in assemblage structure and species traits (Evans et al 2006, Gaston et al 2008), and would complement increasing interest in wider issues concerning human influences on species traits and spatial ecological patterns (Millien et al 2006, Evans et al 2007).…”

mentioning

confidence: 99%

The effect of urbanisation on avian morphology and latitudinal gradients in body size

Evans¹,

Gaston²,

Sharp³

et al. 2009

Oikos

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Urban areas occupy a large and growing proportion of the earth. Such sites exhibit distinctive characteristics relative to adjacent rural habitats, and many species have colonised and now successfully exploit urban habitats. The change in selection pressures as a result of urbanisation has led to trait divergence in some urban populations relative to their rural counterparts, but studies have generally been local in scale and the generality of differentiation thus remains unknown. The European blackbird Turdus merula is one of the commonest urban bird species in the Western Palearctic, but populations vary substantially in the length of time they have been urbanised. Here we investigate patterns of morphological variation in European blackbirds occupying 11 paired urban and rural habitats across much of the urbanised range of this species and spanning 258 of latitude. First, we assessed the extent to which urban and rural blackbirds are differentiated morphologically and the consistency of any differentiation across the range. Paired urban and rural Blackbird populations frequently exhibited significant morphological differences, but the magnitude and direction of differentiation was site dependent. We then investigated whether the nature of latitudinal gradients in bodysize differed between urban and rural populations, as predicted by differences in the climatic regimes of urban and rural areas. Blackbird body-size exhibited strong latitudinal gradients, but their form did not differ significantly between urban and rural habitats. The latitudinal gradient in body size may be a consequence of Seebohm's rule, that more migratory populations occurring at high latitudes have longer wings. We conclude that while there can be substantial morphological variation between adjacent urban and rural bird populations, such differentiation may not apply across a species' range. Locality specific differentiation of urban and rural blackbirds may arise if the selection pressures acting on blackbird morphology vary in an inconsistent manner between urban and rural habitats. Alternatively, phenotypic divergence could arise in a stochastic manner depending on the morphological traits of colonists, through founder effects.

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Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

Cited by 7 publications

References 69 publications

Shapes and functions of species–area curves (II): a review of new models and parameterizations

Shapes and functions of species–area curves (II): a review of new models and parameterizations

Statutory protected areas and avian species richness in Britain

The effect of urbanisation on avian morphology and latitudinal gradients in body size

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