paper update

paper.md

@@ -46,11 +46,11 @@ The development of `psymple` emerged from the complex system modelling requireme
 
 An alternative approach is mechanistic modelling, which instead of observational data use physiological data to capture the underlying mechanisms which drive species distribution, such as energy balance, population dynamics or response to climate [@ke-po:2009]. Mechanistic SDMs decouple the physiology of a species from their native geography or climate, and allow SDMs in new geographic or climatic regimes to be created in the absence of observational data [@john:2019].
 
-While the schools of thought around correlative and mechanistic SDM are largely disjoint [@dorm:2012], there has more recently been development of models composed of both correlative and mechanistic components [@buck:2010; @to-va:2023]. In the wider context of complex systems modelling, the approach of building composite models out of different techniques is called hybrid, or spectrum, modelling.  
+While the schools of thought around correlative and mechanistic SDM are largely disjoint [@dorm:2012], there has more recently been development of models composed of both correlative and mechanistic components [@buck:2010; @to-va:2023], combining the expertise and benefits of both areas. In the wider context of complex systems modelling, the approach of building composite models out of different techniques is called hybrid, or spectrum, modelling.  
 
 An example hybrid framework in ecological modelling that arose from SDM is physiologically-based demographic modelling (PBDM), which uses physiological data to parametrise functions capturing biophysical or biochemical mechanisms, such as the development, mortality and fecundity rates of a species in response to environmental variables, see [@po-gu:2023] for an overview and references. The PBDM approach combines the considerable advantages of mechanistic SDMs, such as being able to consider the effects of tritrophic ecosystem interactions [@g-y-n-e:1999], or modelling the effects of climate change [@guti:2023], while retaining the comparable ease of parametrisation as status-quo correlative models due to its functional components.
 
-While PBDM is a highly-developed framework, it shares the same barriers to widespread introduction as general hybrid complex system models, which are often attributed to be the lack of available modelling frameworks [@bu-c-j:2018], the lack of flexibility in existing models [@buck:2010], or the lack of modelling platforms to implement existing ideas [@po-gu:2023]. The package `psymple` is a general platform designed to facilitate the creation of hybrid complex systems models and modelling frameworks. 
+While PBDM is a highly-developed framework, it shares the same barriers to widespread introduction as general hybrid complex system models. These barriers include the lack of available modelling frameworks [@bu-c-j:2018], the lack of flexibility in existing models [@buck:2010], or the lack of modelling platforms to implement existing ideas [@po-gu:2023]. The package `psymple` is a general platform designed to facilitate the creation of hybrid complex systems models and modelling frameworks. 
 
 Models in `psymple` are built from arbitrary combinations of modular mechanistic, dynamic components and correlative, functional components which naturally interact with each other. This structure allows for the creation of modelling frameworks such as PBDM, and, more widely, those capturing biological, economic and social systems, for which it is not feasible to capture the laws of interaction purely mechanistically. Examples include agroecological, bioeconomic and Earth systems modelling, and the development of `psymple` is a necessary first step in the development and release of accessible and impactful tools in these areas.