Editing IPCC:AR6/WGII/Chapter-2 (section)

==== 2.5.1.1 Assessment of Models and Sources of Uncertainties ====

<div id="h3-29-siblings" class="h3-siblings"></div>

Methods for projecting the impacts of climate change on biodiversity can be classified into three types: (1) statistical models such as SDMs ( [[#Elith--2009|Elith and Leathwick, 2009]] ); (2) mechanistic or process-based models ( [[#Chuine--2017|Chuine and Régnière, 2017]] ) and (3) trait-based models ( [[#Pacifici--2015|Pacifici et al., 2015]] ). It is only recently that models have been developed looking at lower levels of warming like 1.5°C ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ; [[#Warren--2018|Warren et al., 2018]] ).

SDMs or niche-based models assess potential geographic areas of suitable climate for the species in current conditions and then project them into future conditions ( [[#Trisurat--2018|Trisurat, 2018]] ; [[#Vieira--2018|Vieira et al., 2018]] ). There are limitations in all models and it is critical that modellers understand the assumptions, proper parameterization and limitations of each model technique, including differences between climate models, emission scenarios or RCPs and baselines ( [[#Araujo--2019|Araujo et al., 2019]] ). Several systems automate the development of SDMs, including R-packages ( [[#Beaumont--2016|Beaumont et al., 2016]] ; [[#Hallgren--2016|Hallgren et al., 2016]] ), and other model types ( [[#Foden--2019|Foden et al., 2019]] ) and aid in the use of climate model data ( [[#Suggitt--2017|Suggitt et al., 2017]] ), including allowing for connectivity constraints ( [[#Peterson--2013|Peterson et al., 2013]] ). [[#Buisson--2010|Buisson et al. (2010)]] found most variation in model outputs stems from differences in design, followed by general circulation models (GCMs).

Mechanistic approaches, also known as process-based models, project the responses of species to climate changes by explicitly incorporating known biological processes, thresholds and interactions ( [[#Morin--2009|Morin and Thuiller, 2009]] ; [[#Maino--2016|Maino et al., 2016]] ). Mechanistic models are able to accommodate a broad range of mechanisms of climate change impacts and include species-specific characteristics such as dispersal distances, longevity, fecundity, genetic evolution and phenotypic plasticity. However, sufficient knowledge is available for only a few well-studied species. Species’ traits have been used to more broadly estimate potential climate change impacts ( [[#Foden--2013|Foden et al., 2013]] ; [[#Cizauskas--2017|Cizauskas et al., 2017]] ).

Most models are on a large scale (20–50 km), and so cannot capture micro-climatic refugia generated by diversities of slope aspect, elevation or shade ( [[#Suggitt--2015|Suggitt et al., 2015]] ; [[#Suggitt--2018|Suggitt et al., 2018]] ). In analysing records of 430 climate-threatened and range-declining species in England, (Suggett et al., 2015; [[#Suggitt--2018|Suggitt et al., 2018]] ) showed that topographic diversity reduced population declines most strongly in areas experiencing the most local warming and in the species most sensitive to warming. Under these circumstances, topographic diversity reduced the risk of population extinction by 22% for plants and 9% for insects.

None of the modelling techniques are predictions of the future, they are rather projections of possible futures. To date, only a few studies have validated model performance against observations, but the studies that have been conducted do generally validate models using either SDMs or process-based models ( [[#Johnston--2013|Johnston et al., 2013]] ; [[#Fordham--2018|Fordham et al., 2018]] ). SDMs should be considered as hypotheses of what a future world might look like if the climate projections came to pass. Suggestions have been made on how to start bringing more biotic interactions into SDMs ( [[#Early--2019|Early and Keith, 2019]] ), but limited basic ecological understanding of interactions, along with limits on computation and funding, constrains how far and how fast these modelling techniques can advance.

'''Table 2.3 |''' Assessing uncertainty in detection and attribution of observed changes in terrestrial and freshwater species and ecosystems to climate change. The lines of evidence used to support given uncertainty statements, including confidence statements, of the attribution of key conclusions on observed biological changes to climate change and increased atmospheric CO2. Icons represent lines of evidence. This is a summary table that is fully detailed in Table SM2.1.

[[File:8059cc2fe5c8d787cd29275db8706dcf IPCC_AR6_WG2_Chapter2_Table_2_3_1.png]] [[File:4e685b2dc6ec250ec778d343ef8fd8ba IPCC_AR6_WG2_Chapter2_Table_2_3_2.png]] [[File:acf6972c018951e2b0845b7709bb2220 IPCC_AR6_WG2_Chapter2_Table_2_3_3.png]] [[File:1222a6aebf41ab38cd303336fab9b90f IPCC_AR6_WG2_Chapter2_Table_2_3_4.png]]

<div id="2.5.1.2 " class="h3-container"></div>

<span id="risk-assessment-and-non-modelling-approaches"></span>