Reference number : GC-2017-Q1-02094, amendment number : , agreement type : G, recipient legal name : Pennell, Matthew (The University of British Columbia), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : One key premise of modern ecology is that biological processes often scale with traits or with environmental conditions in predictable ways. The regularity of biological scaling forms the basis of a number of macroecological theories&mdash;most prominently the Metabolic Theory of Ecology. However, in macroecological models, these scaling relationships are usually assumed to be static through time and across taxa, even if this assumption is never made explicit. However, there is growing evidence that many ecological scaling relationships appear to vary across taxonomic groups, suggesting that they are the result of evolutionary processes and not simply a physical inevitability. 
 
My research goal is to develop new mathematical, statistical, computational, and conceptual tools to uncover the macroevolutionary dynamics of ecosystem structure and function, as captured by ecological and physiological scaling relationships. This work will provide a novel perspective on the generators of biodiversity, and reciprocally, will help us leverage information on evolutionary history to better forecast how ecosystems will respond to global change. And from a more theoretical angle, this research will result in a more synthetic understanding of biodiversity, one that bridges the conceptual divides between macroevolution and macroecology. Over the five years of this Discovery Grant, I will work towards my aim by focusing on four distinct, but interrelated projects: 
 
1) How have key ecological and physiological scaling relationships evolved over deep time? [PhD 1] 
 
2) How do predictions from macroecological models change when we consider scaling relationships to be evolved (and evolving) traits? [PhD 2] 
 
3) How have constraints and trade-offs shaped the macroevolution of photosynthetic capacity across C3 plants and how has the evolutionary dynamics of this &ldquo;trait&rdquo; influenced structure and function? [PhD 3] 
 
4) How do biases in large trait database trickle down to affect macroecological and macroevolutionary inferences and how well do current strategies for dealing with this ameliorate the problems? [PhD 4] 
 
I believe this work will lay the foundation for entirely new research programs at the interface of evolution, ecology, physiology, and information science. And from an applied perspective, understanding the macroevolutionary dynamics of key scaling traits will help us better forecast how global change will affect biodiversity., program purpose french : One key premise of modern ecology is that biological processes often scale with traits or with environmental conditions in predictable ways. The regularity of biological scaling forms the basis of a number of macroecological theories&mdash;most prominently the Metabolic Theory of Ecology. However, in macroecological models, these scaling relationships are usually assumed to be static through time and across taxa, even if this assumption is never made explicit. However, there is growing evidence that many ecological scaling relationships appear to vary across taxonomic groups, suggesting that they are the result of evolutionary processes and not simply a physical inevitability. 
 
My research goal is to develop new mathematical, statistical, computational, and conceptual tools to uncover the macroevolutionary dynamics of ecosystem structure and function, as captured by ecological and physiological scaling relationships. This work will provide a novel perspective on the generators of biodiversity, and reciprocally, will help us leverage information on evolutionary history to better forecast how ecosystems will respond to global change. And from a more theoretical angle, this research will result in a more synthetic understanding of biodiversity, one that bridges the conceptual divides between macroevolution and macroecology. Over the five years of this Discovery Grant, I will work towards my aim by focusing on four distinct, but interrelated projects: 
 
1) How have key ecological and physiological scaling relationships evolved over deep time? [PhD 1] 
 
2) How do predictions from macroecological models change when we consider scaling relationships to be evolved (and evolving) traits? [PhD 2] 
 
3) How have constraints and trade-offs shaped the macroevolution of photosynthetic capacity across C3 plants and how has the evolutionary dynamics of this &ldquo;trait&rdquo; influenced structure and function? [PhD 3] 
 
4) How do biases in large trait database trickle down to affect macroecological and macroevolutionary inferences and how well do current strategies for dealing with this ameliorate the problems? [PhD 4] 
 
I believe this work will lay the foundation for entirely new research programs at the interface of evolution, ecology, physiology, and information science. And from an applied perspective, understanding the macroevolutionary dynamics of key scaling traits will help us better forecast how global change will affect biodiversity., agreement title english : The phylogenetic history of ecosystem structure and function, agreement title french : The phylogenetic history of ecosystem structure and function, agreement number : RGPIN, agreement value : 165000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada