Dr Guy Woodward (Queen Mary University of London) “Food webs and stressors: impacts at higher organisational levels”
Food webs are comprised of species, which are comprised of individuals, which are comprised of molecules...
Predictable patterns in complex systems: energy from small, abundant species to large, rare species Broadstone Stream (a); Tuesday Lake (b); Ythan Estuary (c)
Woodward et al. (2005) Trends in Ecology & Evolution
The role of body size (big fish eat little fish)
e.g. a can eat b and c; c cannot eat a or b. Ordering of niches may be related to body-size (e.g., a is the largest, c is the smallest species)
a b c
d
Size structure in real food webs – individuals matter b) Individual sized-based web
Increasing prey size
a) Species-averaged web
Increasing predator size
Increasing predator size
Feeding matrix for 31 entities as either a) species or b) size classes. Black dots = observed links, grey dots = predicted links (a = 47% fit; b = 93% fit). (Woodward et al. 2010)
Resource quality drives consumption rates
y = log % mass loss d-1 x1 = log litter C:N
y
x2 = log fungal mass r2 0.97
x2
x1
Hladyz et al (2009) Freshwater Biology
The food web as an ecological prism
Connecting multiple levels of organisation, structure and function...via the food web
ECOSYSTEM GOODS & SERVICES Provision of drinking water Climate regulation Pest & pathogen control Maintenance of viable fisheries Flood defence Ecotourism
Structure is linked to functioning across nutrient gradients Decomposition rates follow a unimodal curve across a eutrophication gradient – rates are fastest where large consumers (“shredders”) predominate. (Woodward et al. 2012, Science)
Ecosystems in a changing climate….? Current focus on lower levels of organisation (individuals, species populations) Effects on higher levels & ecosystem services still poorly understood...
Climate change is a compound stressor – we need to examine its component parts before addressing synergies between them (and with other stressors)
COMPONENT
ECOLOGICAL CONSEQUENCE
Temperature
Elevated metabolic demands
Hydrology
Habitat fragmentation by droughts
Phenology
Consumer-resource mismatches
Wildfires
Manifold effects of riparian vegetation loss
Atmospheric change
Altered consumer-resource stoichiometry
Invasive species
Emergence of novel food webs
Changes in temperature and consumer body mass will alter metabolic rates
These key drivers operate at the individual level and scale up to the whole ecosystem...
Body size and metabolism offer a means to predict climate change impacts across organisational levels
Perkins et al 2010 Hydrobiologia
We can use ecological theories to help develop a more predictive framework
THEORY
ECOLOGICAL RELEVANCE
MT:
Metabolic Theories
Thermal sensitivity of nutrient cycles
FT:
Foraging Theory
Encounter rates and food web linkages
ES:
Ecological Stoichiometry
Carbon:nutrients at base of food webs
Woodward et al 2010 Philosophical Transactions of the Royal Society B
The tools at our disposal – none are perfect, so we combine them Pros
Cons
Surveys
Realism
Inferential, confounded
Natural experiments
Realism
Limited replication, few sites
Field experiments
Some realism
Often small-scale
Lab experiments
High control
Limited realism, small-scale
Modeling
Predictive
Limited realism, lack of data
Trade-off : “Replication – Realism – Control”
Empirical approaches in complex systems
Surveys
Natural experiments
Field experiments
Studying “sentinel systems” at high latitudes can help us to anticipate climate change impacts
A Natural Experiment – the Hengill Geothermal Region
Isolating the effects of temperature • • • •
16 streams Temperature gradient 5-48°C No confounding water chemistry No dispersal constraints
Temperature [°C]
1 “hot” stream
5-25°C range
Streams
Ordination analysis: temperature drives species turnover
+ Temperature + Fish abundance & size Woodward et al. (Global Change Biology 2010)
Ecosystem process rates increase with temperature in field assays Microbial decomposition
Algal production
Total decomposition
Woodward et al 2010 Philosophical Transactions of the Royal Society B
A large thermal gradient over a small spatial gradient
log N
Species-based allometric scaling: “trivariate” food webs
log M
log M
log M
log M
log N
Unpublished data – in prep
log M
log M
log M
A new long-term whole-system warming experiment
a) NSF Grant: Cross, Benstead, Huryn – secondary production & whole system metabolism b) NERC Grant: Woodward, Reuman & Petchey – food web structure & dynamics
Empirical approaches in complex systems
Surveys
Natural experiments
Field experiments
Using field data to test a priori theoretical predictions
Long-term mesocosm experiment at FBA River Lab 4°C warming above ambient since 2006
Yvon-Durocher et al 2010 Advances in Ecological Research
Each component of the carbon cycle has its own activation energy
Metabolic balance: higher heterotrophy in warm ponds
Changes in metabolic balance almost exactly matched theoretical predictions. Warmer systems shifted from sinks towards sources of CO2 – a potential positive feedback. Yvon-Durocher et al 2010 Philosophical Transactions of the Royal Society B
Universal patterns? Congruence between Icelandic & U.K. results
Community structure: is the world ‘getting smaller’? (predicted by metabolic theory, temperature-size rule etc.)
Log body mass (individual size-bins)
Yvon-Durocher et al 2011 Global Change Biology
3 consumer spp. 2 resource spp. 3 temperatures 2 latitudes...
Process
Biodiversity-ecosystem functioning relations (leaf-litter decomposition)
B A
D EE F CD C
?
Species
Simulating climate warming and biodiversity loss in stream assemblages across a latitudinal gradient Consumer diversity
Thermal regimes: 5, 10 and 15ºC
Locations: Northern Sweden Southern England
Umeå
London
Perkins et al 2010 Advances in Ecological Research
Temperature and resource identity were significant
Perkins et al 2010 Advances in Ecological Research
No effect of richness (polycultures were averages of monocultures)…but species identity and size were important Perkins et al 2010 Advances in Ecological Research
Monocultures
Bicultures
Triculture
Metabolic capacity (allometrically scaled with body size) accounted for most of the variance
Perkins et al 2010 Advances in Ecological Research
Replicability and realism – trivariate food webs Brown et al. 2011 Journal of Animal Ecology
Drought reduces biodiversity and secondary production
Ledger et al. 2011 Global Change Biology
Large, rare and rare-at-size species are lost (red triangles)...small fast-growers invade (yellow circles)
Woodward et al (in press Phil. Trans Roy Soc B)
Quantifying the food web: from stocks to fluxes
Ledger et al (Nature Climate Change, 2012)
Long-term shifts in acidified food webs…ecological inertia and recovery
1980s
1990s
log N
1970s
log M
Layer et al. (2011) Invasion of progressively larger predators following high pH during long hot summers distorts food web size structure and stability
2000s
Whole food web patterns: 20 streams across a broad spatial pH gradient (Layer et al. 2010) – might acid webs be more stable, thus slowing recovery?
Broadstone Stream
Will food webs become less stable as both pH and temperatures rise? Layer et al. (2010): Space-for-time survey and modeling of 20 streams across a pH gradient
Current and new food web grants
Title& Funding&Body& Fragility)of)stream)ecosystem)func2oning)in) N.E.R.C.)) response)to)drought:)an)experimental)test)
£& £701k)
Start& 2012)
Diversity)of)Upland)Rivers)for)Ecosystem) Service)Sustainability)(DURESS))
N.E.R.C.))
£3m)
2012)
Using)individual)metabolism)and)body)size) to)predict)climate)warming)impacts)on) aqua2c)food)webs)
N.E.R.C.))
£511k)
2011)
The&temperature&dependence&of& biogeochemical&cycles&
AXA&Insurance& £90k&
2011&
Predictable&feedbacks&between&warming,& community&structure&and&ecosystem& funcEoning&
N.E.R.C.&
£468k&
2010&
ManipulaEng&the&chemosyntheEc&and& photosyntheEc&support&of&river&food&webs&
N.E.R.C.&
£531k&
2010&
A team effort - thanks to all involved – and to you for listening! Pichler, D1., Friberg, N.2,3, Thompson, M.1, Christensen, J.B.2, Perkins, D.M.1, O’Gorman, E.1 Reide, J.8, Reiss, J.,1 Trimmer, M1., Yvon-Durocher, G.1, Demars, B.3, Olafsson, J.S.4, Gislason, G.M.5, Ledger, M.E.6, Brown, L7., Edwards, F. 9 1 Queen Mary University of London, School of Biological & Chemical Sciences, London, U.K. E1 4NS. 2 National Environmental Research Institute, Department of Freshwater Ecology, Vejlsøvej 25, DK-8600 Silkeborg, Denmark. 3 Macaulay Land Use Research Institute, Catchment Management Group, Craigiebuckler, Aberdeen, U.K. AB15 8QH 4 Institute of Freshwater Fisheries, Vagnhofdi 7, 110 Reykjavik, Iceland 5 Institute of Biology, University of Iceland, Sturlugata 7, 101 Reykjavik, Iceland 6 University of Birmingham, U.K. 7 University of Leeds, U.K. 8. University of Darmstadt, Germany 9. CEH, U.K.
