Metacommunity Dynamics Of Benthic Macroinvertebrates In A Large River

Metacommunity ecology focuses on the interaction between local communities and is inherently linked to dispersal as a result. Within this framework, communities are structured by a combination of in-site responses to the immediate environment (species sorting), stochasticity (patch dynamics), and connections to other communities via distance between communities and dispersal (neutrality), and source-sink dynamics (mass effects; see Chapter 1 for a detailed description of metacommunity theory, the study site, and macroinvertebrate communities found). In Chapter 2 I describe spatial scale of study and dispersal ability as both have the ability to influence the degree to which communities interact. However, little is known about how these factors influence the importance of all metacommunity dynamics. I compared dispersal mode of immature aquatic insects and dispersal ability of winged adults across multiple spatial scales in a large river. The strongest drivers of river communities were patch dynamics, followed by species sorting, then neutrality. Active dispersers during aquatic lifestages on average exhibited lower patch dynamics, higher species sorting, and significant mass effects compared to passive dispersers. Active and strong dispersers also had a scale-independent influence of neutrality, while neutrality was stronger at broader spatial scale for passive and weak dispersers. These results indicate as dispersal ability increases patch dynamics decreases, species sorting increases, and neutrality should decrease. The perceived influence of neutrality may also be dependent on spatial scale and dispersal ability. In Chapter 3 I describe how river benthic macroinvertebrate communities may influence tributary invertebrate communities via adult flight and tributaries may influence mainstem communities via immature drift. This relationship may also depend on relative mainstem and tributary size, as well as abiotic tributary influence on mainstem habitat. To investigate the interaction between a larger river and tributary I sampled mainstem benthic invertebrate communities and quantified habitat of a 7th order river (West Branch Susquehanna River) above and below a 5th order tributary confluence, as well as 0.95-3.2 km upstream in the tributary. Non-metric multidimensional scaling showed similar patterns of clustering between sampling locations for both habitat characteristics and invertebrate communities. In addition, mainstem river communities and habitat directly downstream of the tributary confluence cluster tightly together, intermediate between tributary and mid-channel river samples. In Bray-Curtis dissimilarity comparisons between tributary and mainstem river communities the furthest upstream tributary communities were least similar to river communities. Middle tributary samples were also closest by Euclidean distance to the upstream mainstem riffle and exhibited higher similarity to mid-channel samples than the furthest downstream tributary communities. My results indicate river and tributary benthic invertebrate communities may interact and likely result in direct and indirect mass effects of a tributary on the downstream mainstem community by invertebrate drift and habitat restructuring via material delivery from the tributary. I also showed likely direct effects of adult dispersal from the river and oviposition in proximal tributary locations where Euclidian, rather than river, distance may be more important in determining river-tributary interactions.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.

Topographic and meteorological influences on spatial scaling of heavy convective rainfall in mountainous regions

Characterizing the spatial scaling and dynamics of convective precipitation in mountainous terrain and the development of downscaling methods to transfer precipitation fields from one scale to another is the overall motivation for this research. Substantial progress has been made on characterizing the space-time organization of Midwestern convective systems and tropical rainfall, which has led to the development of statistical/dynamical downscaling models. Space-time analysis and downscaling of orographic precipitation has received less attention due to the complexities of topographic influences. This study uses multiscale statistical analysis to investigate the spatial scaling of organized thunderstorms that produce heavy rainfall and flooding in mountainous regions. Focus is placed on the eastern and western slopes of the Appalachian region and the Front Range of the Rocky Mountains. Parameter estimates are analyzed over time and attention is given to linking changes in the multiscale parameters with meteorological forcings and orographic influences on the rainfall. Influences of geographic regions and predominant orographic controls on trends in multiscale properties of precipitation are investigated. Spatial resolutions from 1 km to 50 km are considered. This range of spatial scales is needed to bridge typical scale gaps between distributed hydrologic models and numerical weather prediction (NWP) forecasts and attempts to address the open research problem of scaling organized thunderstorms and convection in mountainous terrain down to 1-4 km scales.

Mean age of carbon in fine roots from temperate forests and grasslands with different management

Fine roots are the most dynamic portion of a plant's root system and a major source of soil organic matter. By altering plant species diversity and composition, soil conditions and nutrient availability, and consequently belowground allocation and dynamics of root carbon (C) inputs, land-use and management changes may influence organic C storage in terrestrial ecosystems. In three German regions, we measured fine root radiocarbon (14C) content to estimate the mean time since C in root tissues was fixed from the atmosphere in 54 grassland and forest plots with different management and soil conditions. Although root biomass was on average greater in grasslands 5.1 ± 0.8 g (mean ± SE, n = 27) than in forests 3.1 ± 0.5 g (n = 27) (p < 0.05), the mean age of C in fine roots in forests averaged 11.3 ± 1.8 yr and was older and more variable compared to grasslands 1.7 ± 0.4 yr (p < 0.001). We further found that management affects the mean age of fine root C in temperate grasslands mediated by changes in plant species diversity and composition. Fine root mean C age is positively correlated with plant diversity (r = 0.65) and with the number of perennial species (r = 0.77). Fine root mean C age in grasslands was also affected by study region with averages of 0.7 ± 0.1 yr (n = 9) on mostly organic soils in northern Germany and of 1.8 ± 0.3 yr (n = 9) and 2.6 ± 0.3 (n = 9) in central and southern Germany (p < 0.05). This was probably due to differences in soil nutrient contents and soil moisture conditions between study regions, which affected plant species diversity and the presence of perennial species. Our results indicate more long-lived roots or internal redistribution of C in perennial species and suggest linkages between fine root C age and management in grasslands. These findings improve our ability to predict and model belowground C fluxes across broader spatial scales.

Past forest composition, structures and processes – How paleoecology can contribute to forest conservation

The importance of long-term historical information derived from paleoecological studies has long been recognized as a fundamental aspect of effective conservation. However, there remains some uncertainty regarding the extent to which paleoecology can inform on specific issues of high conservation priority, at the scale for which conservation policy decisions often take place. Here we review to what extent the past occurrence of three fundamental aspects of forest conservation can be assessed using paleoecological data, with a focus on northern Europe. These aspects are (1) tree species composition, (2) old/large trees and coarse woody debris, and (3) natural disturbances. We begin by evaluating the types of relevant historical information available from contemporary forests, then evaluate common paleoecological techniques, namely dendrochronology, pollen, macrofossil, charcoal, and fossil insect and wood analyses. We conclude that whereas contemporary forests can be used to estimate historical, natural occurrences of several of the aspects addressed here (e.g. old/large trees), paleoecological techniques are capable of providing much greater temporal depth, as well as robust quantitative data for tree species composition and fire disturbance, qualitative insights regarding old/large trees and woody debris, but limited indications of past windstorms and insect outbreaks. We also find that studies of fossil wood and paleoentomology are perhaps the most underutilized sources of information. Not only can paleoentomology provide species specific information, but it also enables the reconstruction of former environmental conditions otherwise unavailable. Despite the potential, the majority of conservation-relevant paleoecological studies primarily focus on describing historical forest conditions in broad terms and for large spatial scales, addressing former climate, land-use, and landscape developments, often in the absence of a specific conservation context. In contrast, relatively few studies address the most pressing conservation issues in northern Europe, often requiring data on the presence or quantities of dead wood, large trees or specific tree species, at the scale of the stand or reserve. Furthermore, even fewer examples exist of detailed paleoecological data being used for conservation planning, or the setting of operative restorative baseline conditions at local scales. If ecologist and conservation biologists are going to benefit to the full extent possible from the ever-advancing techniques developed by the paleoecological sciences, further integration of these disciplines is desirable.

Characteristics, Distribution and Persistence of Thin Layers Over a 48 Hour Period

The biological and physical processes contributing to planktonic thin layer dynamics were examined in a multidisciplinary study conducted in East Sound, Washington, USA between June 10 and June 25, 1998. The temporal and spatial scales characteristic of thin layers were determined using a nested sampling strategy utilizing 4 major types of platforms: (1) an array of 3 moored acoustical instrument packages and 2 moored optical instrument packages that recorded distributions and intensities of thin layers; (2) additional stationary instrumentation deployed outside the array comprised of meteorological stations, wave-tide gauges, and thermistor chains; (3) a research vessel anchored 150 m outside the western edge of the array; (4) 2 mobile vessels performing basin-wide surveys to define the spatial extent of thin layers and the physical hydrography of the Sound. We observed numerous occurrences of thin layers that contained locally enhanced concentrations of material; many of the layers persisted for intervals of several hours to a few days. More than one persistent thin layer may be present at any one time, and these spatially distinct thin layers often contain distinct plankton assemblages. The results suggest that the species or populations comprising each distinct thin layer have responded to different sets of biological and/or physical processes. The existence and persistence of planktonic thin layers generates extensive biological heterogeneity in the water column and may be important in maintaining species diversity and overall community structure.

Evidence of species-specific neighborhood effects in the dipterocarpaceae of a Bornean rain forest

Although accumulating evidence indicates that local intraspecific density-dependent effects are not as rare in species-rich communities as previously suspected, there are still very few detailed and systematic neighborhood analyses of species-rich communities. Here, we provide such an analysis with the overall goal of quantifying the relative importance of inter- and intraspecific interaction strength in a primary, lowland dipterocarp forest located at Danum, Sabah, Malaysia. Using data on 10 abundant overstory dipterocarp species from two 4-ha permanent plots, we evaluated the effects of neighbors on the absolute growth rate of focal trees (from 1986 to 1996) over increasing neighborhood radii (from 1 to 20 m) with multiple regressions. Only trees 10 cm to < 100 cm girth at breast height in 1986 were considered as focal trees. Among neighborhood models with one neighbor term, models including only conspecific larger trees performed best in five out of 10 species. Negative effects of conspecific larger neighbors were most apparent in large overstory species such as those of the genus Shorea. However, neighborhood models with separate terms and radii for heterospecific and conspecific neighbors accounted for more variability in absolute growth rates than did neighborhood models with one neighbor term. The conspecific term was significant for nine out of 10 species. Moreover, in five out of 10 species, trees without conspecific neighbors had significantly higher absolute growth rates than trees with conspecific neighbors. Averaged over the 10 species, trees without conspecific neighbors grew 32.4 cm(2) in basal area from 1986 to 1996, whereas trees with conspecific neighbors only grew 14.7 cm(2) in basal area, although there was no difference in initial basal area between trees in the two groups. Averaged across the six species of the genus Shorea, negative effects of conspecific larger trees were significantly stronger than for heterospecific larger neighbors. Thus, high local densities within neighborhoods of 20 m may lead to strong intraspecific negative and, hence, density-dependent, effects even in species rich communities with low overall densities at larger spatial scales. We conjecture that the strength of conspecific effects may be correlated with the degree of host specificity of ectomycorrhizae.

Functional traits determine plant co-occurrence more than environment or evolutionary relatedness in global drylands

Plant-plant interactions are driven by environmental conditions, evolutionary relationships (ER) and the functional traits of the plants involved. However, studies addressing the relative importance of these drivers are rare, but crucial to improve our predictions of the effects of plant-plant interactions on plant communities and of how they respond to differing environmental conditions. To analyze the relative importance of - and interrelationships among - these factors as drivers of plant-plant interactions, we analyzed perennial plant co-occurrence at 106 dryland plant communities established across rainfall gradients in nine countries. We used structural equation modelling to disentangle the relationships between environmental conditions (aridity and soil fertility), functional traits extracted from the literature, and ER, and to assess their relative importance as drivers of the 929 pairwise plant-plant co-occurrence levels measured. Functional traits, specifically facilitated plants' height and nurse growth form, were of primary importance, and modulated the effect of the environment and ER on plant-plant interactions. Environmental conditions and ER were important mainly for those interactions involving woody and graminoid nurses, respectively. The relative importance of different plant-plant interaction drivers (ER, functional traits, and the environment) varied depending on the region considered, illustrating the difficulty of predicting the outcome of plant-plant interactions at broader spatial scales. In our global-scale study on drylands, plant-plant interactions were more strongly related to functional traits of the species involved than to the environmental variables considered. Thus, moving to a trait-based facilitation/competition approach help to predict that: (1) positive plant-plant interactions are more likely to occur for taller facilitated species in drylands, and (2) plant-plant interactions within woody-dominated ecosystems might be more sensitive to changing environmental conditions than those within grasslands. By providing insights on which species are likely to better perform beneath a given neighbour, our results will also help to succeed in restoration practices involving the use of nurse plants. (C) 2014 Geobotanisches Institut ETH, Stiftung Ruebel. Published by Elsevier GmbH. All rights reserved.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Pollen and charcoal in lake sediments compared with historically documented forest fires in southern Switzerland since AD 1920

Charcoal in unlaminated sediments dated by 210Pb was analysed by the pollen-slide and thin-section methods. The results were compared with the number and area of forest fires on different spatial scales in the area around Lago di Origlio as listed in the wildfire database of southern Switzerland since AD 1920. The influx of the number of charcoal particles > 75 µm2 in pollen slides correlates well with the number of annual forest fires recorded within a distance of 20-50 km from the coring site. Hence a size-class distinction or an area measurement by image analysis may not be absolutely necessary for the reconstruction of regional fire history. A regression equation was computed and tested against an independent data set. Its use makes it possible to estimate the charcoal area influx (or concentration) from the particle number influx (or concentration). Local fires within a radius of 2 km around the coring site correlate well with the area influx of charcoal particles estimated by the thin-section method measuring the area of charcoal particles larger than 20 000 µm2 or longer than 50 µm. Pollen percentages and influx values suggest that intensive agriculture and Castanea sativa cultivation were reduced 30-40 years ago, followed by an increase of forest area and a development to more natural woodlands. The traditional Castanea sativa cultivation was characterized by a complete use of the biomass produced, so abandonment of chestnut led to an increasing accumulation of dead biomass, thereby raising the fire risk. On the other hand, the pollen record of the regional vegetation does not show any clear response to the increase of fire frequency during the last three decades in this area.

Investigating the potential of reported cattle mortality data in Switzerland for syndromic surveillance

Systems for the identification and registration of cattle have gradually been receiving attention for use in syndromic surveillance, a relatively recent approach for the early detection of infectious disease outbreaks. Real or near real-time monitoring of deaths or stillbirths reported to these systems offer an opportunity to detect temporal or spatial clusters of increased mortality that could be caused by an infectious disease epidemic. In Switzerland, such data are recorded in the "Tierverkehrsdatenbank" (TVD). To investigate the potential of the Swiss TVD for syndromic surveillance, 3 years of data (2009-2011) were assessed in terms of data quality, including timeliness of reporting and completeness of geographic data. Two time-series consisting of reported on-farm deaths and stillbirths were retrospectively analysed to define and quantify the temporal patterns that result from non-health related factors. Geographic data were almost always present in the TVD data; often at different spatial scales. On-farm deaths were reported to the database by farmers in a timely fashion; stillbirths were less timely. Timeliness and geographic coverage are two important features of disease surveillance systems, highlighting the suitability of the TVD for use in a syndromic surveillance system. Both time series exhibited different temporal patterns that were associated with non-health related factors. To avoid false positive signals, these patterns need to be removed from the data or accounted for in some way before applying aberration detection algorithms in real-time. Evaluating mortality data reported to systems for the identification and registration of cattle is of value for comparing national data systems and as a first step towards a European-wide early detection system for emerging and re-emerging cattle diseases.

Temporal and small-scale spatial variation in grassland productivity, biomass quality, and nutrient limitation

Characterization of spatial and temporal variation in grassland productivity and nutrition is crucial for a comprehensive understanding of ecosystem function. Although within-site heterogeneity in soil and plant properties has been shown to be relevant for plant community stability, spatiotemporal variability in these factors is still understudied in temperate grasslands. Our study aimed to detect if soil characteristics and plant diversity could explain observed small-scale spatial and temporal variability in grassland productivity, biomass nutrient concentrations, and nutrient limitation. Therefore, we sampled 360 plots of 20 cm × 20 cm each at six consecutive dates in an unfertilized grassland in Southern Germany. Nutrient limitation was estimated using nutrient ratios in plant biomass. Absolute values of, and spatial variability in, productivity, biomass nutrient concentrations, and nutrient limitation were strongly associated with sampling date. In April, spatial heterogeneity was high and most plots showed phosphorous deficiency, while later in the season nitrogen was the major limiting nutrient. Additionally, a small significant positive association between plant diversity and biomass phosphorus concentrations was observed, but should be tested in more detail. We discuss how low biological activity e.g., of soil microbial organisms might have influenced observed heterogeneity of plant nutrition in early spring in combination with reduced active acquisition of soil resources by plants. These early-season conditions are particularly relevant for future studies as they differ substantially from more thoroughly studied later season conditions. Our study underlines the importance of considering small spatial scales and temporal variability to better elucidate mechanisms of ecosystem functioning and plant community assembly.