Post on 06-Feb-2018
Electronic Supplemental Information – Disease ecology meets ecosystem science by D. L.
Preston, J. A. Mischler, A. R. Townsend and P. T. J. Johnson
Methods and Results for Empirical Literature Searches
Figure 1: “The divide between disease ecology and ecosystem science”
We conducted two literature searches using the Web of Science database to quantify 1)
the proportion of disease ecology publication that involve different levels of ecological
organization (that is, host, population, community and ecosystem) and 2) the proportion of
ecosystem ecology publications that involve different types of ecological interactions (that is,
herbivory, predation, competition, parasitism and mutualism). We focused on publications from
1980 to 2013 because we found no ecosystem-disease publications before that date, and we
restricted the search to the Ecology section of the Web of Science database because this produced
the most relevant publications (for example, omitting publications on human medicine). The aims
of our searches were to compare the relative proportion of publications, rather than the absolute
values. Our search strings were established to minimize the numbers of papers that do not fit the
aims of each search, and to avoid biases between different levels of ecological organization or
different types of species interactions. As a result, the number of publications is likely
conservative because it misses papers that do not contain the keywords used. We first conducted
the following title key word search to identify publications in disease ecology: TI=(parasit* OR
disease* OR pathog* OR infect*) AND WC = (ecology). We then combined that search with
each of the following searches that identified publications with title keywords involving different
levels of ecological organization: [TI = (host*) AND WC = (ecology)], [TI = (population*) AND
WC = (ecology)], [TI = (communit*) AND WC = (ecology)], and [TI = (ecosystem*) AND WC
= (ecology)]. To standardize for increases in the number of disease ecology publications over
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time, we then divided the number of publications at each level of ecological organization per year
by the total number disease ecology publications per year. To examine whether the resulting
yearly proportions of disease ecology publications at each level of organization changed over
time (from 1980 to 2013) we used generalized additive models that allowed nonlinear
relationships and accounted for temporal autocorrelation. We used AIC comparisons of multiple
models to determine whether smoothing, autoregressive or moving average terms improved fit
over simple linear models (after Altizer and others 2013). We used the mgcv and nlme packes in
R for the analyses (R Core Team 2013).
For the second literature search we used a similar approach by first identifying
publications that involved ecosystem ecology using the following search string: TI=((ecosystem
AND (function* OR process* OR propert* OR structure OR stability OR dynamic* OR service*
OR engineer* OR disturbance* OR energ* OR change* OR diversity)) OR succession OR
biogeochem* OR ((nutrient* OR nitrogen OR phosphorus OR carbon OR element*) AND (cycl*
OR recycl* OR flux* OR dynamic*)) OR decomposition OR (energ* AND (flow* OR flux* OR
dynamic*)) OR (product* AND (biomass OR primary OR secondary)) OR (change* AND
(global OR environmental))) AND WC = (ecology). We then combined the above search string
with additional searches that identified publications that included specific types of ecological
interactions in their titles: [TI = (predat*) AND WC = (ecology)], [TI = (compet*) AND WC =
(ecology)], [TI = (herbiv* OR graz*) AND WC = (ecology)], [TI = (mutual*) AND WC =
(ecology)], and [TI = (parasit*) AND WC = (ecology)]. To maintain consistency with the disease
ecology search, we restricted the results to publications between 1980 and 2013. We determined
that using a simple search term for each level of ecological organization or type of species
interaction was the most efficient method to ensure there were not major differences in the
efficiency of our search strings. Although this likely makes our total number of publications
conservative, it ensure there is little bias in the results.
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The disease ecology search string returned 8,466 total papers. Publications with the term
‘ecosystem’ were less common than all other levels of ecological organization. We present the
proportion of publications that involved different levels of ecological organization in two ways:
the total proportion from 1980 to 2013 (Figure 1a) and the yearly proportion, which allowed
visualizing trends over time (Figure 1b). For ease of presentation, these data were binned at two-
year intervals in the figure (but not for analyses). For the host, community, and ecosystem level,
simple linear models performed better than generalized additive models in evaluating time trends
in the proportion of publications. The proportion of disease ecology publications between 1980
and 2013 did not change significantly at the host level (GLM, p = 0.141) or the population level
(GAM, p = 0.786). In contrast, the proportion of publications at the community level (GLM, p <
0.001) and the ecosystem level (GLM, p = 0.026) increased significantly from 1980 to 2013
(Figure 1b).
The second search identified 11,680 total ecosystem ecology publications and
reinforced the finding that papers linking ecosystems and disease are uncommon. However, we
note that all of the species interaction terms were relatively uncommon in the titles of ecosystem
ecology publications. Papers that involved herbivory were considerably more common than the
other interaction types, at 2.6% of the total (Figure S1). Parasitism was less common than
herbivory, predation or competition, but was more common than mutualism.
Figure S2: “Patterns in existing ecosystem and disease research”
To examine patterns in published studies linking ecosystem science and disease ecology,
we first identified papers that quantified how parasites affected ecosystems, specifically focusing
on ecosystem structure, biogeochemistry, energy flow, and temporal ecosystem dynamics. We
initially filtered publications that were found with the aforementioned searches used to generate
results shown in Figure 1. This included the Web of Science searches of disease ecology papers at
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the ecosystem level and of ecosystem science papers that involved host/parasite interactions
(described above). We included only primary literature where the authors directly quantified
effects of parasitism and disease. We omitted most publications that focused on community
structure or food webs, as these topics focus on community ecology. We also omitted review
papers that appeared in those searches, but included papers from their literature cited that fit our
criteria. After identifying an initial list of publications, we then searched the literature cited of
those papers to identify additional relevant publications. Lastly, we performed additional focused
searches using Google Scholar to make the dataset more complete (using the search terms
“ecosystem” and “disease” or “parasite”). Among the papers that met our criteria, we extracted
information on six variables: the type of ecosystem (forest, freshwater, marine, grassland or
other), the ecosystem property affected (biogeochemistry, ecosystem structure, energy flow, or
temporal ecosystem dynamics), the approach used in the study (observational, experimental,
modeling, or a combination), the mechanism underlying ecosystem effects of parasites (density-
mediated indirect, trait-mediated indirect or direct effect), and the taxa of hosts and parasites.
We identified a total of 39 publications where the effects of parasites on ecosystem
structure and function were quantified. The full citations and the information extracted are
provided in Table S1. Figure S2 shows the observed patterns in mechanisms, ecosystem types,
ecosystem properties and approaches used. The patterns in host and parasite taxa are shown in
Figure S3.
References
Altizer SA, Ostfeld RS, Johnson PTJ, Kutz S, Harvell CD. 2013. Climate
change and infectious diseases: from evidence to a predictive framework. Science
341: 514-519.
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R Core Team. 2013. R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-
project.org/.
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Supplemental Figures and Tables
Figure S1. The percentage of ecosystem ecology publications (1980 to 2013) that include title
keywords for different types of species interactions.
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Figure S2. Patterns in mechanisms, ecosystem properties studied, approaches used and
ecosystem types from 39 publications that quantified how parasites affected some aspect of
ecosystem structure or function.
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Figure S3. Patterns in host and parasite taxa from 39 publications that quantified cases where
parasites affected ecosystem structure or function.
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Table S1. Published Studies Quantifying the Effects of Parasites on Ecosystem Structure and Function
Ecosystem Property
Ecosystem Type
Host/Parasite System
Mechanism Approach Ecosystem Effects
Citation
Ecosystem Structure
Abiotic Structure Intertidal mud flat
Amphipods and trematode worms
Host density regulation
Observational field study
Amphipod declines increase sediment particle sizes and erosion rates.
Mouritsen and others 1998. Journal of the Marine Biological Association of the United Kingdom.
Temperate forest
Chesnut trees and fungal pathogens
Host density regulation
Observational field study
Loss of chesnut trees has altered soil properties, including carbon and nitrogen content.
Rhoades 2007. Pedobiologia.
Biotic Structure Temperate forest
Rabbits and myxoma virus
Host density regulation
Observational field study
Rabbit declines facilitate shifts from grassland to forest ecosystems.
Sumption and Flowerdew 1985. Mammal Review.
Marine estuary
Marsh plants and hemiparasitic plants
Host density regulation
Observational field study
Parasitic plants alter patterns of plant composition, which forms ecosystem structure.
Pennings and Callaway 1996. Ecology.
Intertidal mud flat
Cockles and trematode worms
Alteration of host traits
Observation and experiment
Trematodes impair cockle burrowing ability, altering the role of an ecosystem engineer.
Thomas and others 1998. Proceedings of the Royal Society, B.
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Rocky intertidal shore
Snails and trematode worms
Alteration of host traits
Experiment Trematodes alter rates of snail grazing leading to changes in macroalgae structure.
Wood and others 2007. Proceedings of the National Academy of Sciences.
Alpine forest
White park pine and fungal pathogens
Host density regulation
Observational field study
White pine blister rust affects the formation of tree islands at treeline.
Resler and Tomback. 2008. Arctic, Antartic and Alpine Research.
Temperate forest
Oak trees and root fungal pathogens
Host density regulation
Observation and modelling
Oak tree declines cause changes in forest structure, including tree size distribution and abudnance of standing dead trees.
Cobb and others 2012. Journal of Ecology.
Temperate forest
Oak trees and root fungal pathogens
Host density regulation
Observational field study
Sudden oak death drives course woody debris dynamics within the forest.
Cobb and others 2012. Ecosystems.
Biogeochemistry
Carbon Cycling Grassland Wildebeest and rinderpest virus
Host density regulation
Modelling Eradication of rinderpest leads to increases in tree density and net carbon storage.
Holdo and others 2009. PLoS Biology.
Nutrient Cycling Open ocean Marine bacteria and viruses
Host density regulation
Experiment Lysis of bacterial cells by viruses releases bioavailable iron used by phytoplankton.
Poorvin and others 2004. Limnology and Oceanography.
Grassland Grassland plants and hemiparasitic plants
Host density regulation
Experiment Hemiparasites change soil microbial composition leading to increased rates of nitrogen cycling.
Bardgett and others 2006. Nature.
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River floodplain
Fungal pathogens and alder trees
Host density regulation
Observational field study
Reductions in tree density have led to reductions in nitrogen fixation.
Ruess and others 2009. Ecosystems.
Temperate forest
Beech trees and pathogenic fungi
Host density regulation
Observational field study
Shifts from beech to other tree species have altered nitrogen cycling.
Lovett and others 2010. Ecosystems.
Tropical
streamAmphibians and chytrid fungi
Host density regulation
Experiment The loss of tadpoles reduces rates of nitrogen cycling.
Whiles and others 2013. Ecosystems.
Temperate stream
Snails and trematode worms
Alteration of host traits
Experiment Trematode infection alter rates of host nutrient excretion.
Bernot and others 2013. Freshwater Science.
Decomposition Temperate stream
Chesnut trees and fungal pathogens
Host density regulation
Experiment Chestnut leaves were processed at different rates than replacement species, leading to changes in decomposition.
Smock and MacGregor 1988. Journal of the North American Benthological Society.
Sub-arctic heathland
Plants and hemiparasitic plants
Direct effect of parasites
Observation and experiment
Hemiparasites are enriched in nutrients and accelerate litter decomposition.
Quested and others 2002. Oecologia.
Temperate stream
Isopods and acanthocephalan worms
Alteration of host traits
Observation and experiment
Acanthocephalan infection reduces rates of litter breakdown by isopods.
Hernandez and Sukhdeo 2008. International Journal for Parasitology.
Temperate forest
Mistletoe and eucalyptus trees
Direct effect of parasites
Observational field study
Mistletoe litterfall alters phosphorus and trace element cycling on the forest floor.
March and Watson 2010. Austral Ecology.
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Alpine tundra
Alpine plants and hemiparasitic plants
Direct effect of parasites
Observation and experiment
Hemiparasites accelerate rates of litter decomposition and increase available nitrogen.
Spasojevic and Suding 2011. Oecologia.
Temperate stream
Maple trees and foliar fungal pathogens
Alteration of host traits
Experiment Fungal infection delays decomposition rates of leaves within streams.
Grimmett and others 2012. Freshwater Science.
Temperate forest
Dung beetles and nematodes
Alteration of host traits
Experiment Nematode infection reduces rates of feces consumption by host beetles, leading to changes in decomposition.
Boze and others 2012. Journal of Insect Behavior.
Energy Flow
Primary Production
Open ocean Phytoplankton and viruses
Host density regulation
Experiment Viruses reduce primary production by up to 78%.
Suttle and others 1990. Nature.
Temperate stream
Caddisflies and microsporidian parasites
Host density regulation
Observational field study
Caddisfly declines result in increases in benthic primary production.
Kohler and Wiley 1997. Ecology.
Grassland Plants and foliar fungal pathogens
Alteration of host traits
Experiment Foliar fungal pathogens strongly reduce grassland primary production.
Mitchell 2003. Ecology Letters.
Marine estuary
Cockles and trematode worms
Alteration of host traits
Experiment Infection causes cockles to alter habitat such that local primary production and secondary production increases.
Mouritsen and Poulin 2006. Journal of the Marine Biological Association of the United Kingdom.
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Tropical stream
Amphibians and chytrid fungi
Host density regulation
Experiment Amphibian declines lead to changes in benthic primary production.
Connely and others 2008. Ecosystems.
Grassland Grassland plants and soil fungal pathogens
Host density regulation
Experiment Soil pathogens alter relationships between plant species richness and productivity.
Maron and others 2011. Ecology Letters.
Secondary Production
Marine estuary
Multiple hosts and parasites
Direct effect of parasites
Observational field study
Parasite biomass equals or exceeds many free-living groups, including birds.
Kuris and others 2008. Nature.
Freshwater pond
Multiple hosts and trematode worms
Direct effect of parasites
Observational field study
Trematode biomass equals or exceeds many free-living groups, including most insects.
Preston and others 2013. Journal of Animal Ecology.
Ecosystem Subsidies
Freshwater stream/ temperate forest
Crickets and nematomorph worms
Alteration of host traits
Observational field study
Infected crickets provde a large energetic subsidy to enter streams.
Sato and others 2011. Ecology.
Freshwater stream/ temperate forest
Crickets and nematomorph worms
Alteration of host traits
Experiment Eliminating cricket subsides led to cascading effects on benthic invertebrates, primary production, and decomposition.
Sato and others 2012. Ecology Letters.
Temporal Dynamics
Succession Freshwater lake
Phytoplankton and chytrid fungi
Host density regulation
Observational field study
Chytrid infection accelerates phytoplankton succession.
Van Donk and Ringleberger 1983. Freshwater Biology.
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Sand dune Plants and soil pathogens
Alteration of host traits
Experiment Soil pathogens control plant competition and patterns of sucession.
Van der Putten and others 1993. Nature.
Temperate forest
Dougals fir trees and root-rot fungi
Host density regulation
Observational field study
A fungal pathogen acellerates sucession by supressing early successional tree species.
Holah and others 1997. Oecologia.
Stability Coral reef Sea urchins and microbial pathogens
Host density regulation
Observational field study
Extirpations of urchins facilitates macroalgae and eliminates coral recruitment, lowering reef resilience.
Lessios 1988. Annual Review of Ecology and Systemtics.
Kelp forest Sea urchins and microbial pathogens
Host density regulation
Observational field study
Extirpations of urchins leads to shift from urchin barrens to kelp forest.
Scheibling 1986. Oecologia.
Invasibility Grassland Grassland plants and viruses
Host density regulation
Modeling The presence of viruses is necessary to allow invasion success of annual grasses in California.
Borer and others 2007. Proceedings of the National Academy of Sciences.
For each publication, we report the ecosystem property that is affected, the type of ecosystem, the host/parasite system, the mechanism through
which parasites exert ecosystem effects (that is, density-mediated indirect effects, trait-mediated indirect effects, or direct effects), the approach
used in the study (observational field study, experiment or modeling), and a description of the effects that were observed.
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Table S2. Traits of the Host, the Parasite, Their Interaction, and the Ecosystem that are Predicted to Affect the Magnitude and Scale of Ecosystem Effects of Disease
Traits Prediction and Rationale
Parasite Pathogenicity and virulence Disease severity is determined in part by parasite traits and can mediate the strength of indirect effects.
Host manipulation Manipulators alter host behavior, morphology, and physiology, increasing the potential for trait-mediated effects.
Host castration Castrators eliminate host reproduction, potentially inducing density-mediated effects.
Introduced vs. native Introduced parasites are most likely to cause epizootics, increasing the potential for density-mediated effects.
Transmission mode Directly transmitted, frequency dependent parasites may increase the potential for density-mediated effects.
Body size and productivity Large and productive parasites can exert direct effects on energy and matter flows.
Host Functional role Unique host functional roles (for example, ability to cycle nutrients) enhance the potential for ecosystem effects.
Abundance Dominant host species with a high density are most likely to facilitate ecosystem roles of parasites.
Physical structure Hosts that are ecosystem engineers (for example, trees and corals) will mediate parasite-driven changes in ecosystem structure.
Interaction strengths Hosts that are keystone species by virtue of their interactions (for example, predation) enhance the potential for ecosystem effects.
Trophic position Hosts that exert top-down or bottom-up effects may enhance the potential for ecosystem roles of parasites.
Introduced vs. native Introduced hosts can strongly alter ecosystems, enhancing the potential for ecosystem effects.
Resistance and tolerance Disease severity is determined in part by host resistance and tolerance, and can mediate the strength of indirect effects.
Interaction
Host outcome Greater host damage or mortality will increase the potential for ecosystem effects.
Infection prevalence and intensity
Increasing prevalence and intensity should increase the potential for ecosystem effects.
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Transmission rate High transmission rates may contribute to ecosystem effects.
Geographic extent of the infection
The larger area over which hosts are affected, the larger the potential scale of ecosystem effects.
Co-evolutionary history A long co-evolutionary history can lead to lower virulence and host adaptation, decreasing the potential for ecosystem effects.
Coinfection Coinfection may increase or decrease ecosystem effects, depending on host responses and parasite interactions.
Ecosystem
Biotic vs. abiotic controls over process rates
Biota must control aspects of ecosystem functioning for parasites to have important roles in ecosystem processes.
Biotic vs. abiotic controls over physical structure
Biota must control aspects of ecosystem structure for parasites to have important roles in ecosystem structure.
Complexity Complex ecosystems with many species interactions can buffer changes due to single species.
Resilience, resistance and robustness
More stable ecosystems may diminish the potential for some ecosystem roles of parasites.
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