Andrews Experimental Forest Research Articles

Snow cover variability in a forest ecotone of the Oregon Cascades via MODIS Terra products

Snow cover pattern and persistence have important implications for planetary energy balance, climate sensitivity to forcings, and vegetation structure, function, and composition. Variability in snow cover within mountainous regions of the Pacific Northwest, USA is attributable to a combination of anthropogenic climate change and climate oscillations. However, snow covered areas can be heterogeneous and patchy, requiring more detailed mapping of snow trends to understand their potential influences on montane forests. We used standard daily MODIS snow products (MOD10A1.5) to investigate the 15-year record (2000–2014) of snow cover in the predominant forest ecotone of the Oregon Western Cascades. We modeled the ecotone using field data from the H.J. Andrews Experimental Forest, and only considered forested MODIS Terra pixels located within the mapped ecotone of a five-county region. Three snow cover metrics were developed using both binary and fractional snow cover data: mean ecotone snow cover percent, number of snow covered days during the melt season, and day of snow disappearance. Snow cover and depletion dates exhibited large interannual variability and no significant linear trends. This variability is likely influenced by the preceding wintertime states of the Pacific Decadal Oscillation (PDO) and the El Niño/Southern Oscillation (ENSO), which tend to covary. We improve and generalize existing methods for power analysis of trend estimation and quantify the number of uninterrupted observations of the snow metrics that would be needed to distinguish trends of different magnitudes from noise variance, taking possible autocorrelation into account. Sensitivity analyses of the results to some of our heuristic choices are conducted, and challenges associated with optical remote sensing of snow in a dense montane forest are discussed.

Test of newly developed conceptual hydrological model for simulation of rain-on-snow events in forested watershed

A conceptual hydrological model that links the Xin'anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoff and peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin'anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can provide a useful tool for discharge forecasting in ungauged basins.

Seeing the climate through the trees: observing climate and forestry impacts on streamflow using a 60‐year record

AbstractPaired watershed experiments involving the removal or manipulation of forest cover in one of the watersheds have been conducted for more than a century to quantify the impact of forestry operations on streamflow. Because climate variability is expected to be large, forestry treatment effects would be undetectable without the treatment–control comparison. New understanding of climate variability provides an opportunity to examine whether climate variability interacts with forestry treatments, in a predictable manner. Here, we use data from the H. J. Andrews Experimental Forest, Oregon, USA, to examine the impact of the El Niño‐Southern Oscillation on streamflow linked to forest harvesting. Our results show that the contrast between El Niño and La Niña events is so large that, whatever the state of the treated watershed in terms of regrowth of the forest canopy, extreme climatic variability related to El Niño‐Southern Oscillation remains the more dominant driver of streamflow response at this location. Improvements in forecasting interannual variation in climate might be used to minimize the impact of forestry treatments on streamflow by avoiding initial operations in La Niña years. Copyright © 2014 John Wiley & Sons, Ltd.

Quantifying spatial differences in metabolism in headwater streams

AbstractStream functioning includes simultaneous interaction among solute transport, nutrient processing, and metabolism. Metabolism is measured with methods that have limited spatial representativeness and are highly uncertain. These problems restrict development of methods for up-scaling biological processes that mediate nutrient processing. We used the resazurin–resorufin (Raz-Rru) tracer system to estimate metabolism at different spatial scales (habitat, subreach, and reach) in 2 headwater streams of the H. J. Andrews Experimental Forest (Oregon, USA), and present a mathematical framework for its application. We investigated the relationship between metabolism and hydrodynamics, i.e., geomorphic units (e.g., pool–riffle, pool–cascade), bed materials (i.e., alluvium vs bedrock channels), and type of transient storage (i.e., pure hyporheic exchange, pure surface transient storage, and a combination of both). The metabolic hotspots detected by the Raz-Rru system in both watersheds were related to hydrody...

Spatially distributed characterization of hyporheic solute transport during baseflow recession in a headwater mountain stream using electrical geophysical imaging

Summary The transport of solutes along hyporheic flowpaths is recognized as central to numerous biogeochemical cycles, yet our understanding of how this transport changes with baseflow recession, particularly in a spatially distributed manner, is limited. We conducted four steady-state solute tracer injections and collected electrical resistivity data to characterize hyporheic transport during seasonal baseflow recession in the H.J. Andrews Experimental Forest (Oregon, USA). We used temporal moment analysis of pixels generated from inversion of electrical resistivity data to compress time-lapse data into descriptive statistics (mean arrival time, temporal variance, and temporal skewness) for each pixel. A spatial visualization of these temporal moments in the subsurface at each of five 2-D transects perpendicular to the stream was interpreted to inform transport processes. As baseflow recession progressed we found increasing first arrival times, persistence, mean arrival time, temporal variance, and coefficient of variation, and decreasing skewness. These trends suggest that changes in hydrologic forcing alter the relative influence of transport phenomena (e.g., advection vs. other transport processes such as dispersion) along flowpaths. Spatial coverage obtained from electrical resistivity images allowed for qualitative comparison of spatial patterns in temporal moments both at an individual cross-section as well as between cross sections. We found that geomorphologic controls (e.g., bedrock confinement vs. gravel wedge deposits) resulted in different distributions and metrics of hyporheic transport. Results of this study provide further evidence that hyporheic transport is highly variable both in space and through the baseflow recession period. Geophysical images differentiate advection-dominated flowpaths from those that are more affected by other transport processes (e.g., dispersion, mobile-immobile exchange).

The Use of Sequence-Based SSR Mining for the Development of a Vast Collection of Microsatellites in <i>Aquilegia formosa</i>

Numerous microsatellite markers were developed for Aquilegia formosa from sequences deposited within the Expressed Sequence Tag (EST), Genomic Survey Sequence (GSS), and Nucleotide databases in NCBI. Microsatellites (SSRs) were identified and primers were designed for 9 SSR containing sequences in the Nucleotide database, 3803 sequences in the EST database, and 2226 sequences in the GSS database. For validation purposes, 45 primer pairs were used to amplify DNA from 16 A. formosa individuals from the H. J. Andrews experimental forest in Oregon, a Long Term Ecological Research (LTER) site. Genetic polymorphisms were identified at 30 of the 45 microsatellite loci with an average of 13.2 alleles per locus, and the observed level of heterozygosity was greater than 0.8 for 21 of the 30 loci. The use of these polymorphic loci was sufficient to individually separate the 16 individuals using a principal coordinate analysis. This comprehensive collection of primers significantly increased the availability of microsatellite primers for Aquilegia spp. and provided ample material for future studies that required highly variable SSRs such as mapping and association studies and investigation of plant mating system and gene flow.

Determinants of moth diversity and community in a temperate mountain landscape: vegetation, topography, and seasonality

Macromoth diversity, abundance, and community structure in the topographically complex HJ Andrews Experimental Forest and LTER site was studied on the west slope of the Cascade Range, Oregon. Data on 493 macromoth species (62,221 individuals) was sampled eight times/year at 20 locations from 2004 to 2008 and examined using multivariate statistics and generalized additive models to determine the importance of topography and vegetation on moth community assembly and diversity. Significant differences exist between moth communities at lower and higher elevations. High‐elevation moth communities are far more variable inter‐annually, whether associated with high‐elevation forests, meadows, or clearcuts. Low‐elevation young and old gymnosperm forests and riparian forests are more stable and predictable communities having less inter‐annual variability. High‐elevation communities show more intra‐annual variability than low‐elevation communities. Low‐elevation moth communities are more abundant than high‐elevation communities and typically associated with the most common, abundant species of macromoths in the study. High‐elevation communities, by contrast, are associated with less abundant, more evenly distributed species, as well as with rare moth species. Macromoth community structure and diversity were related to year or sample period and structural descriptions of vegetation communities, but not related to known host‐plant diversity. High‐elevation communities are threatened by contraction of montane meadows and climate change which, given the variability in high‐elevation communities, could severely impact the biological diversity of the western Cascades landscape. Nocturnal macromoths represent an important potential indicator of ecosystem health and change.

Species richness and abundance among macromoths: A comparison of taxonomic, temporal and spatial patterns in Oregon and South Korea

The present study aims to establish a long-term intercontinental collaboration based on a sampling protocol using standardized repeated measures at permanent sites to document macromoth species richness and abundance through time and across the landscape. We pooled the data from two continental regions providing a total of 12 trap sites: Mt. Jirisan National Park in South Korea (2005–2007) and HJ Andrews Experimental Forest in Oregon, USA. (2004–2006). A synthesis of our data indicated that: (i) noctuids (43–52%) and geometrids (33–39%) dominated the measures of species richness; (ii) using our sampling protocols more than three years would be needed to obtain a value of 90% of empirical species richness relative to Chao-1 estimated species richness; (iii) temperature alone could not explain the peak pattern in moth abundance and species richness; (iv) the highest/ lowest proportion of species richness and abundance were present in similar elevation and forest sites. These observations established a foundation for developing a network-oriented database for assessing biotic impact of environmental and contributed to identifying species at high risk to environmental change based on empirical measures of temporal and spatial breadth.

Interactive visual analysis promotes exploration of long‐term ecological data

Long‐term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, these kinds of data sets are difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods and spreadsheet software permit rigorous tests of pre‐conceived hypotheses and static charts for simple data exploration, they have limited capacity to provide an overview of the data and to enable ecologists to explore data iteratively, and interactively, before committing to statistical analysis. These issues hinder how ecologists gain knowledge and generate hypotheses from long‐term data. We present Ecological Distributions and Trends Explorer (EcoDATE), a web‐based, visual‐analysis tool that facilitates exploratory analysis of long‐term ecological data (i.e., generating hypotheses as opposed to confirming hypotheses). The tool, which is publicly available online, was created and refined through a user‐centered design process in which our team of ecologists and visualization researchers collaborated closely. The results of our collaboration were (1) a set of visual representation and interaction techniques well suited to communicating distribution patterns and temporal trends in ecological data sets, and (2) an understanding of processes ecologists use to explore data and generate and test hypotheses. We present three case studies to demonstrate the utility of EcoDATE and the exploratory analysis processes using long‐term data on cone production, stream chemistry, and forest structure collected as part of the H.J. Andrews Experimental Forest (HJA), Long Term Ecological Research (LTER), and US Forest Service Pacific Northwest Research Station programs. We also present results from a survey of 15 participants of a working group at the 2012 LTER All Scientists Meeting that showed that users appreciated the tool for its ease of use, holistic access to large data sets, and interactivity.

Linking aboveground net primary productivity to soil carbon and dissolved organic carbon in complex terrain

Factors influencing soil organic matter (SOM) stabilization and dissolved organic carbon (DOC) content in complex terrain, where vegetation, climate, and topography vary over the scale of a few meters, are not well understood. We examined the spatial correlations of lidar and geographic information system‐derived landscape topography, empirically measured soil characteristics, and current and historical vegetation composition and structure versus SOM fractions and DOC pools and leaching on a small catchment (WS1) in the H.J. Andrews Experimental Forest, located in the western Cascades Range of Oregon, USA. We predicted that aboveground net primary productivity (ANPP), litter fall, and nitrogen mineralization would be positively correlated with SOM, DOC, and carbon (C) content of the soil based on the principle that increased C inputs cause C stores in and losses from in the soil. We expected that in tandem, certain microtopographical and microclimatic characteristics might be associated with elevated C inputs and correspondingly, soil C stores and losses. We confirmed that on this site, positive relationships exist between ANPP, C inputs (litter fall), and losses (exportable DOC), but we did not find that these relationships between ANPP, inputs, and exports were translated to SOM stores (mg C/g soil), C content of the soil (% C/g soil), or DOC pools (determined with salt and water extractions). We suggest that the biogeochemical processes controlling C storage and lability in soil may relate to longer‐term variability in aboveground inputs that result from a heterogeneous and evolving forest stand.

Soil Microbe Active Community Composition and Capability of Responding to Litter Addition after 12 Years of No Inputs

One explanation given for the high microbial diversity found in soils is that they contain a large inactive biomass that is able to persist in soils for long periods of time. This persistent microbial fraction may help to buffer the functionality of the soil community during times of low nutrients by providing a reservoir of specialized functions that can be reactivated when conditions improve. A study was designed to test the hypothesis: in soils lacking fresh root or detrital inputs, microbial community composition may persist relatively unchanged. Upon addition of new inputs, this community will be stimulated to grow and break down litter similarly to control soils. Soils from two of the Detrital Input and Removal Treatments (DIRT) at the H. J. Andrews Experimental Forest, the no-input and control treatment plots, were used in a microcosm experiment where Douglas-fir needles were added to soils. After 3 and 151 days of incubation, soil microbial DNA and RNA was extracted and characterized using quantitative PCR (qPCR) and 454 pyrosequencing. The abundance of 16S and 28S gene copies and RNA copies did not vary with soil type or amendment; however, treatment differences were observed in the abundance of archaeal ammonia-oxidizing amoA gene abundance. Analysis of ∼110,000 bacterial sequences showed a significant change in the active (RNA-based) community between day 3 and day 151, but microbial composition was similar between soil types. These results show that even after 12 years of plant litter exclusion, the legacy of community composition was well buffered against a dramatic disturbance.

Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach

Although field-collected recordings typically contain multiple simultaneously vocalizing birds of different species, acoustic species classification in this setting has received little study so far. This work formulates the problem of classifying the set of species present in an audio recording using the multi-instance multi-label (MIML) framework for machine learning, and proposes a MIML bag generator for audio, i.e., an algorithm which transforms an input audio signal into a bag-of-instances representation suitable for use with MIML classifiers. The proposed representation uses a 2D time-frequency segmentation of the audio signal, which can separate bird sounds that overlap in time. Experiments using audio data containing 13 species collected with unattended omnidirectional microphones in the H. J. Andrews Experimental Forest demonstrate that the proposed methods achieve high accuracy (96.1% true positives/negatives). Automated detection of bird species occurrence using MIML has many potential applications, particularly in long-term monitoring of remote sites, species distribution modeling, and conservation planning.

Imaging hyporheic exchange

The dynamics of flow through the subterranean area at the base and along the sides of streambeds, known as the hyporheic zone, affect stream ecosystem dynamics, but researchers do not have a solid understanding of what controls the amount of hyporheic exchange.Ward et al. injected tracers into a stream in the H.J. Andrews Experimental Forest in Oregon and used electrical resistivity imaging to quantify the shape and size of the hyporheic zone. Repeated experiments quantify changes from spring high to summer low flows in the stream. The researchers studied how valley morphology and hydraulic gradients between the stream and surrounding landscape affected hyporheic exchange. Contrary to their expectations based on commonly accepted conceptual models, the scientists found that increasing hydraulic gradients from catchment to stream did not always lead to smaller hyporheic zones. They conclude that hydraulic gradients were not the dominant control on hyporheic exchange in the setting they studied. (Water Resources Research, doi:10.1029/2011WR011461, 2012)

The role of bedrock groundwater in rainfall–runoff response at hillslope and catchment scales

► We monitor storm response in bedrock groundwater tables in two headwater catchments. ► Bedrock groundwater did not rise above the soil–bedrock interface. ► Bedrock groundwater responded rapidly to storm events. ► Bedrock geology has considerable impact on hillslope rainfall–runoff response. Bedrock groundwater dynamics in headwater catchments are poorly understood and poorly characterized. Direct hydrometric measurements have been limited due to the logistical challenges associated with drilling through hard rock in steep, remote and often roadless terrain. We used a new portable bedrock drilling system to explore bedrock groundwater dynamics aimed at quantifying bedrock groundwater contributions to hillslope flow and catchment runoff. We present results from the Maimai M8 research catchment in New Zealand and Watershed 10 (WS10) at the H.J. Andrews Experimental Forest in Oregon, USA. Analysis of bedrock groundwater at Maimai, through a range of flow conditions, revealed that the bedrock water table remained below the soil–bedrock interface, indicating that the bedrock aquifer has minimal direct contributions to event-based hillslope runoff. However, the bedrock water table did respond significantly to storm events indicating that there is a direct connection between hillslope processes and the underlying bedrock aquifer. WS10 groundwater dynamics were dominated by fracture flow. A highly fractured and transmissive zone within the upper one meter of bedrock conducted rapid lateral subsurface stormflow and lateral discharge. The interaction of subsurface stormflow with bedrock storage directly influenced the measured hillslope response, solute transport and computed mean residence time. This research reveals bedrock groundwater to be an extremely dynamic component of the hillslope hydrological system and our comparative analysis illustrates the potential range of hydrological and geological controls on runoff generation in headwater catchments.

Hydrologic and geomorphic controls on hyporheic exchange during base flow recession in a headwater mountain stream

Hyporheic hydrodynamics are a control on stream ecosystems, yet we lack a thorough understanding of catchment controls on these flow paths, including valley constraint and hydraulic gradients in the valley bottom. We performed four whole‐stream solute tracer injections under steady state flow conditions at the H. J. Andrews Experimental Forest (Oregon, United States) and collected electrical resistivity (ER) imaging to directly quantify the 2‐D spatial extent of hyporheic exchange through seasonal base flow recession. ER images provide spatially distributed information that is unavailable for stream solute transport modeling studies from monitoring wells alone. The lateral and vertical extent of the hyporheic zone was quantified using both ER images and spatial moment analysis. Results oppose the common conceptual model of hyporheic “compression” by increased lateral hydraulic gradients toward the stream. We found that the extent of the hyporheic zone increased with decreasing vertical gradients away from the stream, in contrast to expectations from conceptual models. Increasing hyporheic extent was observed with both increasing and decreasing down‐valley (i.e., parallel to the valley gradient) and cross‐valley (i.e., from the hillslope to the stream, perpendicular to the valley gradient) hydraulic gradients. We conclude that neither cross‐valley nor down‐valley hydraulic gradients are sufficient predictors of hyporheic exchange flux nor flow path network extent. Increased knowledge of the controls on hyporheic exchange, the temporal dynamics of exchange flow paths, and their the spatial distribution is the first step toward predicting hyporheic exchange at the scale of individual flow paths. Future studies need to more carefully consider interactions between spatiotemporally dynamic hydraulic gradients and subsurface architecture as controls on hyporheic exchange.

Field Notes from the Andrews Experimental Forest

Field Notes from the Andrews Experimental Forest

Estimating the deep seepage component of the hillslope and catchment water balance within a measurement uncertainty framework

AbstractDeep seepage is a term in the hillslope and catchment water balance that is rarely measured and usually relegated to a residual in the water balance equation. While recent studies have begun to quantify this important component, we still lack understanding of how deep seepage varies from hillslope to catchment scales and how much uncertainty surrounds its quantification within the overall water balance. Here, we report on a hillslope water balance study from the H. J. Andrews Experimental Forest in Oregon aimed at quantifying the deep seepage component where we irrigated a 172‐m2 section of hillslope for 24·4 days at 3·6 ± 3 mm/h. The objective of this experiment was to close the water balance, identifying the relative partitioning of, and uncertainties around deep seepage and the other measured water balance components of evaporation, transpiration, lateral subsurface flow, bedrock return flow and fluxes into and out of soil profile storage. We then used this information to determine how the quantification of individual water balance components improves our understanding of key hillslope processes and how uncertainties in individual measurements propagate through the functional uses of the measurements into water balance components (i.e. meteorological measurements propagated through potential evapotranspiration estimates). Our results show that hillslope scale deep seepage composed of 27 ± 17% of applied water. During and immediately after the irrigation experiment, a significant amount of the irrigation water could not be accounted for. This amount decreased as the measurement time increased, declining from 28 ± 16% at the end of the irrigation to 20 ± 21% after 10 days drainage. This water is attributed to deep seepage at the catchment scale. Copyright © 2010 John Wiley & Sons, Ltd.

Hydrological connectivity of hillslopes and streams: Characteristic time scales and nonlinearities

Subsurface flow from hillslopes is widely recognized as an important contributor to streamflow generation; however, processes that control how and when hillslopes connect to streams remain unclear. We investigated stream and hillslope runoff dynamics through a wet‐up period in watershed 10 of the H. J. Andrews Experimental Forest in the western Cascades of Oregon where the riparian zone has been removed by debris flows. We examined the controls on hillslope‐stream connectivity on the basis of observations of hydrometric, stable isotope, and applied tracer responses and computed transit times for multiple runoff components for a series of storms during the wet‐up phase of the 2002–2003 winter rainy season. Hillslope discharge was distinctly threshold‐like with a near linear response and average quick flow ratio of 0.58 when antecedent rainfall was greater than 20 mm. Hillslope and stream stormflow varied temporally and showed strong hysteretic relationships. Event water mean transit times (8–34 h) and rapid breakthrough from applied hillslope tracer additions demonstrated that subsurface contributing areas extend far upslope during events. Despite rapid hillslope transport processes during events, soil water and runoff mean transit times during nonstorm conditions were greater than the time scale of storm events. Soil water mean transit times ranged between 10 and 25 days. Hillslope seepage and catchment base flow mean transit times were between 1 and 2 years. We describe a conceptual model that captures variable physical flow pathways, their synchronicity, threshold activation, hysteresis, and transit times through changing antecedent wetness conditions that illustrate the different stages of hillslope and stream connectivity.

Ectomycorrhizal mats alter forest soil biogeochemistry

Dense hyphal mats formed by ectomycorrhizal (EcM) fungi are prominent features in Douglas-fir forest ecosystems, and have been estimated to cover up to 40% of the soil surface in some forest stands. Two morphotypes of EcM mats have been previously described: rhizomorphic mats, which have thick hyphal rhizomorphs and are found primarily in the organic horizon, and hydrophobic mats, which occur in the mineral horizon and have an ashy appearance. This study surveyed EcM mat and non-mat soils from eight early and late seral conifer forest stands at the H.J. Andrews Experimental Forest in western Oregon. EcM mats were classified by morphology and taxonomic identities were determined by DNA sequencing. A variety of chemical and biochemical properties, including enzymes involved in C, N, and P cycling were measured. Analysis was confined to a comparison of rhizomorphic mats colonizing the organic horizon with non-mat organic soils, and hydrophobic mats with non-mat mineral soils. Both the organic and mineral horizons showed differences between mat and non-mat enzyme profiles when compared on a dry weight basis. In the organic horizon, rhizomorphic mats had greater chitinase activity than non-mat soils; and in the mineral horizon, hydrophobic mats had increased chitinase, phosphatase, and phenoloxidase activity compared to the non-mat soil. The rhizomorphic mats had 2.7 times more oxalate than the nonmats and significantly lower pH. In the mineral horizon, hydrophobic mats had 40 times more oxalate and significantly lower pH than non-mat mineral soils. Microbial biomass C was not significantly different between the rhizomorphic mat and non-mat organic soils. In the mineral horizon, however, the hydrophobic mats had greater microbial biomass C than the non-mat soils. These data demonstrate that soils densely colonized by EcM fungi create a unique soil environment with distinct microbial activities when compared to non-mat forest soils.

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

The effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in precipitation inputs and catchment characteristics between the treatment and control catchments. This paper presents a model-based change-detection approach that includes model and parameter uncertainty as an alternative to the traditional paired-catchment method for larger catchments. We use the HBV model and data from the HJ Andrews Experimental Forest in Oregon, USA, to develop and test the approach on two small (<1 km2) headwater catchments (a 100% clear-cut and a control) and then apply the technique to the larger 62 km2 Lookout catchment. Three different approaches are used to detect changes in stream peak flows using: (a) calibration for a period before (or after) change and simulation of runoff that would have been observed without land-cover changes (reconstruction of runoff series); (b) comparison of calibrated parameter values for periods before and after a land-cover change; and (c) comparison of runoff predicted with parameter sets calibrated for periods before and after a land-cover change. Our proof-of-concept change detection modelling showed that peak flows increased in the clear-cut headwater catchment, relative to the headwater control catchment, and several parameter values in the model changed after the clear-cutting. Some minor changes were also detected in the control, illustrating the problem of false detections. For the larger Lookout catchment, moderately increased peak flows were detected. Monte Carlo techniques used to quantify parameter uncertainty and compute confidence intervals in model results and parameter ranges showed rather wide distributions of model simulations. While this makes change detection more difficult, it also demonstrated the need to explicitly consider parameter uncertainty in the modelling approach to obtain reliable results. Citation Seibert, J. & McDonnell, J. J. (2010) Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty. Hydrol. Sci. J. 55(3), 316–332.