Island butterfly
biodiversity & biogeography
Photo: Scott Nielsen
PhD student Zachary and field assistant Ira looking out over islands in the Lake of the Woods island biodiversity/biogeography study area in Ontario.
Island butterfly biodiversity & biogeography
Lake of the Woods, Ontario
Graduate Student
Ph.D. candidate (Fall 2015)
Supervisor
Associate Professor & Alberta Biodiversity Conservation Chair
Supervisor
Faculty Service Officer
Status: Active, Active, study began in 2015

Ecologists have been fond of insular metaphors since the publication of the theory of island biogeography (MacArthur and Wilson 1963,Wilson and MacArthur 1967). Such metaphors have framed terrestrial habitat fragments as isolated “ecological islands” of suitable habitat situated in a ‘sea’ of otherwise unsuitable habitat. Over the past half-century, the theory of island biogeography has served as a versatile null model within the disciplines of population and landscape ecology (Gotelli 1996). While the theory has proved to be an appealing heuristic, generating a multitude of empirically-testable hypotheses relating to patterns of species diversity on both island archipelagoes and terrestrial fragmented landscapes, it has also reduced species diversity analyses to unimaginative curve-fitting in many cases (Haila 1986, 2002). Our research at Lake of the Woods, Ontario is focused on assessing how applications of island biogeography and related ecological theory have influenced our understandings of ecological patterns and processes on fragmented landscapes.

A priori parallels between oceanic islands and habitat patches on fragmented landscapes suggest that species diversity decreases with increasing habitat fragmentation (decreasing patch size and increasing patch isolation). In congruence with this analogy, the majority of literature concludes that fragmentation effects are of great conservation concern. Incongruently, however, a recent reemergence of theoretical approaches to habitat fragmentation research suggests that the size and isolation of habitat patches play little role in structuring species diversity. It has been hypothesized that only the aggregate amount of habitat remaining on fragmented landscapes affects the number of persisting species. While there is evidence to support this ‘habitat amount hypothesis’ (Fahrig 2013), it has also been suggested that many of the diversity-based analyses cited to support this hypothesis fail to account for variation in the responses of individual species to habitat fragmentation (Hanski 2015). Through assessing levels of congruence between species-specific responses to habitat fragmentation and broad patterns in species diversity on fragmented landscapes, we are testing the viability of traditional ‘curve-fitting’ approaches for assessing fragmentation effects, which may obscure responses of individual species – the unit at which species diversity is ultimately structured. 

The focus of Zachary’s research is on assessing how traditional and emerging approaches to theoretical ecology affect the way we perceive and quantify patterns of species diversity on fragmented landscapes. Ways in which ecologists measure species diversity vary widely, from a simple count of the number of species present, to measures of the relative abundances of species, to information entropies quantifying properties of species assemblage data.  Zachary’s work shows that different measures of species diversity can communicate different, even contradictory, messages about species assemblages. Using butterfly and plant assemblages on both true islands and ecological islands, Zachary is assessing i) which measures of species diversity are most appropriate for a variety of conservation applications, and ii) whether broad-scale approaches to quantifying species diversity on fragmented landscapes have potential to obscure population declines in individual species. With the recent swell in citizen science projects monitoring biodiversity around the world, Zachary is also assessing i) how these data are best analyzed, and ii) how these data compare with historical museum records.