Towards a networks based approach to biomonitoring

v Acknowledgements . vi 1 | Ecological networks: the missing links in biomonitoring science1 . 1 1.1 Biomonitoring in the 21st century . 2 1.2 The advantages of incorporating species interactions into biomonitoring schemes . 3 1.3 Incorporating ecological networks into biomonitoring schemes . 7 1.4 Network metrics informing ecological research . 9 1.5 Aims and thesis structure . 14 2 | Joining the dots: an automated method for constructing food webs from compendia of published interactions1 . 16 2.1 Summary . 17 2.2 Introduction . 18 2.3 Methods . 24 2.4 Results . 32 2.5 Discussion . 41 3 | The recovery of freshwater food webs from the effects of acidification . 48 3.1 Summary . 49 3.2 Introduction . 50 3.3 Methods . 53 3.4 Results . 60 3.5 Discussion . 66 4 | Food web topological plasticity disrupts the provisioning of ecosystem services. 73 4.1 Summary . 74 4.2 Introduction . 75 4.3 Methods . 77 4.4 Results . 82 Page | viii 4.5 Discussion . 89 5 | The recovery of a freshwater food web from a catastrophic pesticide spill . 92 5.1 Summary . 93 5.2 Introduction . 94 5.3 Methods . 99 5.4 Results . 107 5.5 Discussion . 117 6 | General Discussion . 121 7 | References . 118 Appendix A | The stability of the Upland Waters Monitoring Network food webs . 136 Appendix B | Drought rewires the cores of food webs1 . 161 Appendix C | Gene-to-ecosystem impacts of a catastrophic pesticide spill: testing a multilevel bioassessment approach in a river ecosystem1 . 178 Appendix D | Freshwater conservation and biomonitoring of structure and function: genes to ecosystems1 . 213 Appendix E | Supplementary material for Chapter 3 . 260 Appendix F | Supplementary material for Chapter 4 . 274 Appendix G | Supplementary material for Chapter 5 . 280 Chapter 1 | Introduction Page | 1 1 | Ecological networks: the missing links in biomonitoring science1 1 Gray, C. , Baird, D.J., Baumgartner, S. , Jacob, U. , Jenkins, G.B. , O’Gorman, E.J., Lu, X. , Ma, A. , Pocock, M.J.O. , Schuwirth, N. , Thompson, M. & Woodward, G. (2014). Ecological networks: the missing links in biomonitoring science. Journal of Applied Ecology, 51, 1444– 1449. Chapter 1 | Introduction Page | 2 1.1 Biomonitoring in the 21st century Biomonitoring programmes were first developed in the wake of the Industrial Revolution to measure the effects of environmental stressors on the natural world. They focus on measuring the biological response to environmental perturbations, as biota integrate the changes in environmental quality over time into one measure (i.e. presence, absence or composition), unlike chemical data which reflects only one point in time. Most current programmes are taxonomically constrained and monitor changes in biodiversity, although increasingly, aspects of ecosystem functioning are being incorporated. A range of indices have been developed which score taxa on their known sensitivity to particular stressors (e.g. Balloch, Davies & Jones. 1976; Wright, Furse & Armitage 1993; Bonada et al. 2006; Murphy et al. 2013). Changes are assessed against a baseline level relative to a reference or idealised level (e.g. targets for restoration or acceptable levels of a response variable for that place and time). This approach of assessing the biota of a site with respect to a ‘reference’ condition now underpins many biomonitoring schemes across Europe (e.g. Simpson et al. 2005; Murphy et al. 2013) and other parts of the world (Simpson & Norris 2000). However, pre-industrial (i.e. pre 1800) target conditions for many habitats no longer exist, or are very rare; many of European freshwater habitats are impacted (Friberg et al. 2011; Malaj et al. 2014) and many grasslands worldwide have experienced eutrophication driven by emissions and nitrogen deposition (Clark & Tilman 2008). Furthermore preindustrial states are very difficult to model with confidence (Battarbee et al. 2005). Additional challenges are provided by global climate change, since the reference conditions themselves may be shifting (Pauly 1995; Bennion et al. 2011). Unfortunately, this makes assigning appropriate reference conditions for biomonitoring problematic. Due to the paucity of baseline data, current biomonitoring schemes are still unable to diagnose many perturbations, often there is also a generally poor understanding of the underlying ecological mechanisms governing an ecosystems response to Chapter 1 | Introduction Page | 3 environmental change (Friberg et al. 2011). Newly emerging environmental threats, such as the many facets of climate change, pose new challenges for biomonitoring schemes. Thus, there is a growing need to determine how best to assess the impact of these emerging stressors, both in isolation and in combination. Also, the structural biodiversity-centric focus of traditional methods (e.g. Wright, Furse & Armitage 1993; Metcalfe-Smith 1996; Murphy et al. 2013) now needs to be augmented with more explicitly functional measures (e.g. Young, Matthaei & Townsend 2008), to provide complementary insights into the impacts of stressors (Woodward et al. 2012b). Incorporating species interactions into biomonitoring approaches may help to overcome many of the limitations of current biomonitoring approaches, and provide a new template for ecosystem monitoring. 1.2 The advantages of incorporating species interactions into biomonitoring schemes Traditional biomonitoring schemes have focused on presence/absence or abundance of taxa (network 'nodes') across environmental gradients, while ignoring the network of pairwise i