Laurel G. Larsen

Exploratory modeling: Extracting causality from complexity

On 22 May 2011 a massive tornado tore through Joplin, Mo., killing 158 people. With winds blowing faster than 200 miles per hour, the tornado was the most deadly in the United States since modern record keeping began in the 1950s.

Air-water gas exchange and CO2 flux in a mangrove-dominated estuary

[1]xa0Mangrove forests are highly productive ecosystems, but the fate of mangrove-derived carbon remains uncertain. Part of that uncertainty stems from the fact that gas transfer velocities in mangrove-surrounded waters are not well determined, leading to uncertainty in air-water CO2 fluxes. Two SF6 tracer release experiments were conducted to determine gas transfer velocities (k(600)u2009=u20098.3u2009±u20090.4 and 8.1u2009±u20090.6u2009cmu2009h−1), along with simultaneous measurements of pCO2 to determine the air-water CO2 fluxes from Shark River, Florida (232.11u2009±u200923.69 and 171.13u2009±u200920.28u2009mmol C m−2 d−1), an estuary within the largest contiguous mangrove forest in North America. The gas transfer velocity results are consistent with turbulent kinetic energy dissipation measurements, indicating a higher rate of turbulence and gas exchange than predicted by commonly used wind speed/gas exchange parameterizations. The results have important implications for carbon fluxes in mangrove ecosystems.

Linking metrics of landscape pattern to hydrological process in a lotic wetland

ContextStrong reciprocal interactions exist between landscape patterns and ecological processes. In wetlands, hydrology is the dominant abiotic driver of ecological processes and both controls, and is controlled, by vegetation presence and patterning. We focus on binary patterning in the Everglades ridge-slough landscape, where longitudinally connected flow, principally in sloughs, is integral to landscape function. Patterning controls discharge competence in this low-gradient peatland, with important feedbacks on hydroperiod and thus peat accretion and patch transitions.ObjectivesTo quantitatively predict pattern effects on hydrologic connectivity and thus hydroperiod.MethodsWe evaluated three pattern metrics that vary in their hydrologic specificity. (1) Landscape discharge competence considers elongation and patch-type density that capture geostatistical landscape features. (2) Directional connectivity index (DCI) extracts both flow path and direction based on graph theory. (3) Least flow cost (LFC) is based on a global spatial distance algorithm strongly analogous to landscape water routing, where ridges have higher flow cost than sloughs because of their elevation and vegetation structure. Metrics were evaluated in comparison to hydroperiod estimated using a numerically intensive hydrologic model for synthetic landscapes. Fitted relationships between metrics and hydroperiod for synthetic landscapes were extrapolated to contemporary and historical maps to explore hydroperiod trends in space and time.ResultsBoth LFC and DCI were excellent predictors of hydroperiod and useful for diagnosing how the modern landscape has reorganized in response to modified hydrology.ConclusionsMetric simplicity and performance indicates potential to provide hydrologically explicit, computationally simple, and spatially independent predictions of landscape hydrology, and thus effectively measure of restoration performance.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Making ecological models adequate

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a models ability to predict ecological systems responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

Fine particle retention within stream storage areas at base flow and in response to a storm event

Fine particles (1-100 µm), including particulate organic carbon (POC) and fine sediment, influence stream ecological functioning because they may contain or have a high affinity to sorb nitrogen and phosphorus. These particles are immobilized within stream storage areas, especially hyporheic sediments and benthic biofilms. However, fine particles are also known to remobilize under all flow conditions. This combination of downstream transport and transient retention, influenced by stream geomorphology, controls the distribution of residence times over which fine particles influence stream ecosystems. The main objective of this study was to quantify immobilization and remobilization rates of fine particles in a third-order sand-and-gravel bed stream (Difficult Run, Virginia, USA) within different geomorphic units of the stream (i.e., pool, lateral cavity, thalweg). During our field injection experiment, a thunderstorm-driven spate allowed us to observe fine particle dynamics during both baseflow and in response to increased flow. Solute and fine particles were measured within stream surface waters, porewaters, sediment cores, and biofilms on cobbles. Measurements were taken at four different subsurface locations with varying geomorphology and at multiple depths. Approximately 68% of injected fine particles were retained during baseflow until the onset of the spate. Retention was evident even after the spate, with 15.4% of the baseflow-deposited fine particles retained within benthic biofilms on cobbles and 14.9% within hyporheic sediment after the spate. Thus, through the combination of short-term remobilization and long-term retention, fine particles can serve as sources of carbon and nutrients to downstream ecosystems over a range of timescales.

How Important Is Connectivity for Surface Water Fluxes? A Generalized Expression for Flow Through Heterogeneous Landscapes

How important is hydrologic connectivity for surface-water fluxes though heterogeneous floodplains, deltas, and wetlands? While significant for management, this question remains poorly addressed. Here we adopt spatial resistance averaging, based on channel and patch configuration metrics quantifiable from aerial imagery, to produce an upscaled rate law for discharge. Our model suggests that patch coverage largely controls discharge sensitivity, with smaller effects from channel connectivity and vegetation patch fractal dimension. However, connectivity and patch configuration become increasingly important near the percolation threshold and at low water levels. These effects can establish positive feedbacks responsible for substantial flow change in evolving landscapes (14-36%, in our Everglades case study). Connectivity also interacts with other drivers; flow through poorly connected hydroscapes is less resilient to perturbations in other drivers. Finally, we found that flow through heterogeneous patches is alone sufficient to produce non-Manning flow-depth relationships commonly observed in wetlands but previously attributed to depth-varying roughness.

Complex networks of functional connectivity in a wetland reconnected to its floodplain

Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

Regional Sensitivities of Seasonal Snowpack to Elevation, Aspect, and Vegetation Cover in Western North America

In mountains with seasonal snow cover, the effects of climate change on snowpack will be constrained by landscape-vegetation interactions with the atmosphere. Airborne lidar surveys used to estimate snow depth, topography, and vegetation were coupled with reanalysis climate products to quantify these interactions and to highlight potential snowpack sensitivities to climate and vegetation change across the western U.S. at Rocky Mountain (RM), Northern Basin and Range (NBR), and Sierra Nevada (SNV) sites. In forest and shrub areas, elevation captured the greatest amount of variability in snow depth (16–79%) but aspect explained more variability (11–40%) in alpine areas. Aspect was most important at RM sites where incoming shortwave to incoming net radiation (SW:NetR↓) was highest (∼0.5), capturing 17–37% of snow depth variability in forests and 32–37% in shrub areas. Forest vegetation height exhibited negative relationships with snow depth and explained 3–6% of its variability at sites with greater longwave inputs (NBR and SNV). Variability in the importance of physiography suggests differential sensitivities of snowpack to climate and vegetation change. The high SW:NetR↓ and importance of aspect suggests RM sites may be more responsive to decreases in SW:NetR↓ driven by warming or increases in humidity or cloud cover. Reduced canopy-cover could increase snow depths at SNV sites, and NBR and SNV sites are currently more sensitive to shifts from snow to rain. The consistent importance of aspect and elevation indicates that changes in SW:NetR↓ and the elevation of the rain/snow transition zone could have widespread and varied effects on western U.S. snowpacks.

Salmon Creek radon data

This datafile contains results of 222Rn analysis of samples collectedn within the Salmon Creek Watershed in Sonoma County, Califonia. Please seen Woelfle-Erskine et al. (2017) for site location details. The presentn dataset is provided in support of Larsen and Woelfle-Erskine (in review).n The purpose of this dataset was to determine relative ages of watern samples. Data were collected in 2016 in the Fay Creek and Tannery Creekn watersheds, both second-order tributaries of Salmon Creek. For furthern information, please see the metadata file.