Determinants of the biogeographical distribution of butterflies in boreal regions

By Miska Luoto, Risto Heikkinen, J. Pöyry, K. Saarinen. 2006

150 citations recorded by the source corpus.

Aim We explored the relative contributions of climatic and land‐cover factors in explaining the distribution patterns of butterflies in a boreal region.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/0e2382116acadae81b95864ecf33c9994de0fc59

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France (2006, methodology): “Among existing techniques, generalized linear models (GLMs; McCullagh & Nelder, 1997) and generalized additive models (GAMs; Hastie & Tibshirani, 1997) are the most commonly used (e.g. Bio et al., 1998; Bio, 2000; Austin, 2002; Ferrier et al., 2002; Luoto et al., 2006).”
Species traits explain recent range shifts of Finnish butterflies (2009, background): “GDD5 was chosen as the temperature surrogate because it reflects the principal limitations on butterfly growth and survival (Hill et al., 2003), and it has been shown to be a good correlate of the distributional range of many butterfly species occurring in the boreal region (Luoto et al., 2006).”
Uses and requirements of ecological niche models and related distributional models (2006, background): “Several examples of this sort of study have been published (Austin and Meyers 1996; Costa et al. 2002; Guisan and Hofer 2003; Hirzel et al. 2002; Luoto et al. 2006; Peterson et al. 2004a; Ron 2005).”
Conservation of adaptive potential and functional diversity: integrating old and new approaches (2018, background): “2018) and highlight that climate change could also create new habitats, as species expand into climatically previously inaccessible locations (Luoto et al. 2006).”
The influences of landscape structure on butterfly distribution and movement: a review (2009, background): “…work in this area is clearly a high priority especially as its implications are so substantial (Zierl and Bugmann 2005; Pauli et al. 2007) and resulting in range shifts of some European butterflies (Hill et al. 1999, 2002; Franco et al. 2006; Luoto et al. 2006; Schweiger et al. 2008, in review).”
Five (or so) challenges for species distribution modelling (2006, background): “…this question requires quantifying how much climate can explain species distributions compared to other predictors, such as soils, site history, human influences, or other factors (e.g. Pearson et al., 2004; Thuiller et al., 2004a; del Barrio et al., 2006; Coudun et al., 2006; Luoto et al., 2006).”
Modelling stream fish species distribution in a river network: the relative effects of temperature versus physical factors (2008, methodology): “To date, AUC is one of the most used performance measures in ecology (e.g., Manel et al. 1999, 2001; Guisan & Zimmermann 2000; Pearce & Ferrier 2000; Luck 2002; Gibson et al. 2004; Araujo et al. 2005; Luoto et al. 2006).”
Improving generalized regression analysis for the spatial prediction of forest communities (2006, background): “…Lehmann, 2004); fern diversity (Lehmann et al., 2002a; Zaniewski et al., 2002); amphibians (Joly et al., 2001; Ray et al., 2002); birds (Suarez-Seoane et al., 2002); butterflies (Luoto et al., 2006); aquatic invertebrates (Castella et al., 2001); and coral reef habitats (GarzaPérez et al., 2004).”
Improving species distribution models for climate change studies: variable selection and scale (2011, methodology): “…of using only climate predictors and a resolution of 10 · 10 km or 50 · 50 km pixel SDMs to explore a variety of methodological comparisons focused on SDM (e.g. Araújo et al., 2006; Thuiller et al., 2006; Pöyry et al., 2008) and ecological issues (e.g. Luoto et al., 2006; Svenning et al., 2008).”
Climate warming and the decline of amphibians and reptiles in Europe (2006, background): “Non-climatic factors have been shown to be important for modelling distributions of other taxa (e.g. Coudun et al., 2006; Luoto et al., 2006) and their appropriate incorporation within models along with feed-back mechanisms among variables is likely to magnify estimates of decline or extinction of…”
The performance of state-of-the-art modelling techniques depends on geographical distribution of species. (2009, background): “Numerous studies have recently demonstrated that the performance of the bioclimatic models may depend on the characteristics of the species (e.g. Venier et al., 1999; Karl et al., 2002; Thuiller et al., 2003; Segurado and Araújo, 2004; Luoto et al., 2006).”
Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity (2010, background): “These models have wide relevance in conservation biology (Araújo et al. 2005b; Rissler et al. 2006), biogeography (Lobo et al. 2001; Luoto et al. 2006; Richards et al. 2007), reserves design (Araújo & Williams 2000; Margules & Pressey 2000; OrtegaHuerta & Peterson 2004) and climate change…”
Threshold criteria for conversion of probability of species presence to either–or presence–absence (2007, methodology): “The resulting categorical map is used for practical applications (e.g., Araújo et al., 2004, 2006; Luoto et al., 2006), as well as for evaluating model prediction reliability, involving comparison with the inherently either–or presence/absence data using a confusion matrix (Fielding and Bell,…”
Assessing the vulnerability of European butterflies to climate change using multiple criteria (2010, methodology): “The modelling was based on three climate variables that have been successfully used in earlier studies on the biogeographical distribution modelling of European butterflies (e.g. Hill et al. 1999, 2002, 2003; Luoto et al. 2006).”
Species traits are associated with the quality of bioclimatic models (2008, background): “This suggests that the relatedness of species had only a weak influence on the relationship between traits and modelling accuracy (cf. Luoto et al., 2006).”
Model‐based uncertainty in species range prediction (2006, background): “, 2004; Martı́nez-Meyer & Peterson, 2006), factors governing species distributions (Coudun & Gégout, 2006; Luoto et al., 2006) and the geographical ecology of invasive species (Higgins et al.”