Geoscience Reference
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(Biggs and Rogers 2003, Biggs et al. 2011) (see Chapter 1). Such boundaries can be adjusted to
local conditions and context, for example different TPCs may be appropriate inside and out-
side of protected areas. Regular review of TPCs allows them to be adapted to emerging scien-
tific knowledge and changing social preferences, while modelling and scenario building
helps to develop a continuum between past, present, and future as we move towards uncer-
tain and possibly no-analogue conditions (Biggs et al. 2011, Gillson and Marchant 2014).
Conservation strategies are urgently needed to combat, adapt to, and mitigate the effects of
anthropogenic climate change, despite the high level of uncertainty about the magnitude and
impacts of future climate scenarios and the complexity of interacting drivers that influence
biodiversity distribution and abundance (Dawson et al. 2011, Gillson et al. 2013). Knowledge
of climatically driven changes in distribution can inform strategic conservation decisions
about the configuration of reserves and protected area networks that maintain wildlife habi-
tat in with a range of microclimates and facilitate migration to new climate space through
enhanced connectivity and a well-managed matrix (see Chapter 5) (Bush 2002, Hannah et al.
2007). Long-term data can help in assessing which areas are most exposed to climate change,
which species and ecosystems are most sensitive and which have the greatest capacity to
adapt (Pearman et al. 2008a, b, Dawson et al. 2011). Knowledge of future changing rainfall and
fire regimes can also help in planning fire and herbivory regimes that ameliorate the impacts
of climate change, and in designing resilient agrarian landscapes that produce a wide range
of ecosystem services under variable environmental conditions (see subsequent sections)
(Scholze et al. 2006, Fischer et al. 2012, Seddon et al. 2014).
Knowledge of biodiversity responses to past warm climates can also help to validate the
outputs of models by hind-casting; if models can successfully hindcast of 'retrodict' the
impacts of known climate change in the past, we can be more confident that their predictions
of the effects of future climate scenarios are reliable (Anderson et al. 2006, Roberts and
Hamann 2011, Brewer et al. 2012). Modelling the interactions between past climate and vege-
tation change can also help in understanding the feedbacks between land cover and regional
climate systems, information which is essential to understanding how ecosystem services
might change in the future (Lézine et al. 2011, Krinner et al. 2012).
continuum
Climate is only one of many interacting drivers that affect biodiversity; land-use change, dis-
turbance, introduced species, over-exploitation, pollution, and diseases are interacting stres-
sors that act at different scales and may drive ecosystems or populations to dangerous tipping
points (Rockström et al. 2009, Barnosky et al. 2012, Brook et al. 2013). Using modelling tech-
niques that integrate climate, land-use, and physiological effects can help in more accurately
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