31 research outputs found
Manipulating host resistance structure reveals impact of pathogen dispersal and environmental heterogeneity on epidemics
Understanding how variation in hosts, parasites, and the environment shapes patterns of disease is key to predicting ecological and evolutionary outcomes of epidemics. Yet in spatially structured populations, variation in host resistance may be spatially confounded with variation in parasite dispersal and environmental factors that affect disease processes. To tease apart these disease drivers, we paired surveys of natural epidemics with experiments manipulating spatial variation in host susceptibility to infection. We mapped epidemics of the wind-dispersed powdery mildew pathogen Podosphaera plantaginis in five populations of its plant host, Plantago lanceolata. At 15 replicate sites within each population, we deployed groups of healthy potted 'sentinel' plants from five allopatric host lines. By tracking which sentinels became infected in the field and measuring pathogen connectivity and microclimate at those sites, we could test how variation in these factors affected disease when spatial variation in host resistance and soil conditions was minimized. We found that the prevalence and severity of sentinel infection varied over small spatial scales in the field populations, largely due to heterogeneity in pathogen prevalence on wild plants and unmeasured environmental factors. Microclimate was critical for disease spread only at the onset of epidemics, where humidity increased infection risk. Sentinels were more likely to become infected than initially healthy wild plants at a given field site. However, in a follow-up laboratory inoculation study we detected no significant differences between wild and sentinel plant lines in their qualitative susceptibility to pathogen isolates from the field populations, suggesting that primarily non-genetic differences between sentinel and wild hosts drove their differential infection rates in the field. Our study leverages a multi-faceted experimental approach to disentangle important biotic and abiotic drivers of disease patterns within wild populations.Peer reviewe
Resources, key traits and the size of fungal epidemics in Daphnia populations
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111939/1/jane12363.pd
Habitat, predators, and hosts regulate disease in Daphnia through direct and indirect pathways
Community ecology can link habitat to disease via interactions among habitat, focal hosts, other hosts, their parasites, and predators. However, complicated food web interactions (i.e., trophic interactions among predators and their impacts on host density and diversity) often obscure the important pathways regulating disease. Here, we disentangle community drivers in a case study of planktonic disease, using a twoâstep approach. In step one, we tested univariate field patterns linking community interactions directly to two disease metrics. Density of focal hosts (Daphnia dentifera) was related to density but not prevalence of fungal (Metschnikowia bicuspidata) infections. Both disease metrics appeared to be driven by selective predators that cull infected hosts (fish, e.g., Lepomis macrochirus), sloppy predators that spread parasites while feeding (midges, Chaoborus punctipennis), and spore predators that reduce contact between focal hosts and parasites (other zooplankton, especially smallâbodied Ceriodaphnia sp.). Host diversity also negatively correlated with disease, suggesting a dilution effect. However, several of these univariate patterns were initially misleading, due to confounding ecological links among habitat, predators, host density, and host diversity. In step two, path models uncovered and explained these misleading patterns, and grounded them in habitat structure (refuge size). First, rather than directly reducing infection prevalence, fish predation drove disease indirectly through changes in density of midges and frequency of small spore predators (which became more frequent in lakes with small refuges). Second, small spore predators drove the two disease metrics through fundamentally different pathways: they directly reduced infection prevalence, but indirectly reduced density of infected hosts by lowering density of focal hosts (likely via competition). Third, the univariate diversityâdisease pattern (signaling a dilution effect) merely reflected the confounding direct effects of these small spore predators. Diversity per se had no effect on disease, after accounting for the links between small spore predators, diversity, and infection prevalence. In turn, these small spore predators were regulated by both sizeâselective fish predation and refuge size. Thus, path models not only explain each of these surprising results, but also trace their origins back to habitat structure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/1/ecm1222_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/2/ecm1222-sup-0001-AppendixS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/3/ecm1222.pd
Global maps of soil temperature
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0â5 and 5â15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (â0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications
Global maps of soil temperature
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-kmÂČ resolution for 0â5 and 5â15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-kmÂČ pixels (summarized from 8500 unique temperature sensors) across all the worldâs major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications
Global maps of soil temperature.
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications
Interactions between ecosystems and disease in the plankton of freshwater lakes
I investigated effects of environmental change on disease, and effects of disease on ecosystems, using a freshwater zooplankton host and its fungal parasite. This research involved lake surveys, manipulative experiments, and mathematical models. My results indicate that ecosystem characteristics such as habitat structure, nutrient availability, and quality of a hostâs resources (here, phytoplankton) can affect the spread of disease. For example, a survey of epidemics in lakes revealed direct and indirect links between habitat structure and epidemic size, where indirect connections were mediated by non-host species. Then, in a mesocosm experiment in a lake, manipulations of habitat structure and nutrient availability interactively affected the spread of disease, and nutrient enrichment increased densities of infected hosts. In a separate laboratory experiment, poor quality resources were shown to decrease parasite transmission rate by altering host foraging behavior. My experimental results also suggest that disease can affect ecosystems through effects on host densities and host traits. In the mesocosm experiment, the parasite indirectly increased abundance of algal resources by decreasing densities of the zooplankton host. Disease in the experimental zooplankton populations also impacted nutrient stoichiometry of algae, which could entail a parasite-mediated shift in food quality for grazers such as the host. Additionally, I showed that infection dramatically reduces host feeding rate, and used a dynamic epidemiological model to illustrate how this parasite-mediated trait change could affect densities of resources and hosts, as well as the spread of disease. I discuss the implications of these ecosystemâdisease interactions in light of ongoing changes to habitat and nutrient regimes in freshwater ecosystems.Ph.D
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Understanding the ecology and evolution of host-parasite interactions across scales.
Predicting the emergence, spread and evolution of parasites within and among host populations requires insight to both the spatial and temporal scales of adaptation, including an understanding of within-host up through community-level dynamics. Although there are very few pathosystems for which such extensive data exist, there has been a recent push to integrate studies performed over multiple scales or to simultaneously test for dynamics occurring across scales. Drawing on examples from the literature, with primary emphasis on three diverse host-parasite case studies, we first examine current understanding of the spatial structure of host and parasite populations, including patterns of local adaptation and spatial variation in host resistance and parasite infectivity. We then explore the ways to measure temporal variation and dynamics in host-parasite interactions and discuss the need to examine change over both ecological and evolutionary timescales. Finally, we highlight new approaches and syntheses that allow for simultaneous analysis of dynamics across scales. We argue that there is great value in examining interplay among scales in studies of host-parasite interactions
Robotany: A portable, lowâcost platform for precise automated aerial imaging of field plots
Abstract The 1Â m2 quadrat is a standard field survey tool in ecology. Traditionally, a researcher places a square frame on the ground and manually records data about organisms (typically plants) within that quadrat. Collecting data through this method can require a great deal of time onâsite. For some studies, it would be more efficient to collect data as images in the field, and then extract desired data from the images later. Equipment currently available for precise aerial imaging of plants is most applicable to largeâscale settings (e.g. entire fields) or controlled environments (e.g. greenhouses or growth chambers). There is a lack of technology suited to 1Â ĂÂ 1Â m quadrat surveys of natural communities. To satisfy this need, we developed a portable, lowâcost platform (âRobotanyâ) that automatically takes a set of data samples to precisely cover a 1Â m2 field plot. The current design is optimized for taking aerial photographs of short herbaceous plants in mowed or grazed habitats, at a spatial resolution of 24 nonâoverlapping photographs per 1Â m2, using a digital singleâlens reflex (DSLR) camera with the lens 55Â cm above the ground. Novel attachment and actuation methods allow for fast, convenient assembly and disassembly, and the waterproof frame can be disinfected with ethanol. The device was reliable and precise in its initial two summers of field testing (ca. 200 plots imaged). These images were of sufficient resolution to identify common plant taxa, and to collect information on plant size, flowering status, and damage by foliar pathogens and herbivores. The apparatus was robust to frequent disassembly, transport and reassembly. The onâsite time and labour of quadratâbased field surveys can be greatly reduced with this device. For some applications, images may replace onâsite (manual) data collection from quadrats. For other applications, the images may complement onâsite data collection, as a digital backâup and source of additional data (e.g. highâresolution spatial mapping of plant species or traits, or types of ground cover). The Robotany is modular and can be adapted to different research needs, including replacement of the camera with a different type of sampler