Montana Institute on Ecosystems

Hyporheic exchange is now widely acknowledged as a key driver of ecosystem processes in many streams. Yet stream ecologists have been slow to adopt nuanced hydrologic frameworks developed and applied by engineers and hydrologists to describe the relationship between water storage, water age, and water balance in finite hydrosystems such as hyporheic zones. Here, in the context of hyporheic hydrology, we summarize a well-established mathematical framework useful for describing hyporheic hydrology, while also applying the framework heuristically to visualize the relationships between water age, rates of hyporheic exchange, and water volume within hyporheic zones. Building on this heuristic application, we discuss how improved accuracy in the conceptualization of hyporheic exchange can yield a deeper understanding of the role of the hyporheic zone in stream ecosystems. Although the equations presented here have been well-described for decades, our aim is to make the mathematical basis as accessible as possible and to encourage broader understanding among aquatic ecologists of the implications of tailed age distributions commonly observed in water discharged from and stored within hyporheic zones. Our quantitative description of "hyporheic hydraulic geometry," associated visualizations, and discussion offer a nuanced and realistic understanding of hyporheic hydrology to aid in considering hyporheic exchange in the context of river and stream ecosystem science and management.

Reports of biogenic methane (CH4) synthesis associated with a range of organisms have steadily accumulated in the literature. This has not happened without controversy and in most cases the process is poorly understood at the gene and enzyme levels. In marine and freshwater environments, CH4 supersaturation of oxic surface waters has been termed the "methane paradox" because biological CH4 synthesis is viewed to be a strictly anaerobic process carried out by O2-sensitive methanogens. Interest in this phenomenon has surged within the past decade because of the importance of understanding sources and sinks of this potent greenhouse gas. In our work on Yellowstone Lake in Yellowstone National Park, we demonstrate microbiological conversion of methylamine to CH4 and isolate and characterize an Acidovorax sp. capable of this activity. Furthermore, we identify and clone a gene critical to this process (encodes pyridoxylamine phosphate-dependent aspartate aminotransferase) and demonstrate that this property can be transferred to Escherichia coli with this gene and will occur as a purified enzyme. This previously unrecognized process sheds light on environmental cycling of CH4, suggesting that O2-insensitive, ecologically relevant aerobic CH4 synthesis is likely of widespread distribution in the environment and should be considered in CH4 modeling efforts.

Abstract AimClimate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso‐ and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales.LocationEastern USA.Time periodLast century to present.Major taxa studiedTemperate broadleaf forests.MethodsWe review regional literature of past tree mortality studies associated with climate to identify mesoscale climate‐driven disturbance events. Using a dynamic vegetation model, we then simulate how these forests respond to a typical climate‐driven disturbance.ResultsBy identifying compound disturbance events from both a literature review and simulation modelling, we find that synchronous patterns of drought‐driven mortality at mesoscales have been overlooked within these forests.Main conclusionsAs ecologists, land managers and policy‐makers consider the intertwined drivers of climate and disturbance, a focus on spatio‐temporal scales equivalent to those of the drivers will provide insight into long‐term forest change, such as drought impacts. Spatially extensive studies should also have a long temporal scale to provide insight into pathways for forest change, evaluate predictions from dynamic forest models and inform development of global vegetation models. We recommend integrating data collected from spatially well‐replicated networks (e.g., archaeological, historical or palaeoecological data), consisting of centuries‐long, high‐resolution records, with models to characterize better the mesoscale response of forests to climate change in the past and in the future.

Abstract. Relationships between methane (CH4) fluxes and environmental conditions have been extensively explored in saturated soils, while in aerated soils, the relatively small magnitudes of CH4 fluxes have made research less prevalent. Our study builds on previous carbon cycle research at Tenderfoot Creek Experimental Forest, Montana to identify how environmental conditions reflected by topographic metrics can be leveraged to estimate watershed scale CH4 fluxes from point scale measurements. Here, we measured soil CH4 concentrations and fluxes across a range of landscape positions (7 riparian, 25 upland), utilizing topographic and seasonal gradients to examine the relationships between environmental variables, hydrologic dynamics, and CH4 emission and uptake. Riparian areas emitted small fluxes of CH4 throughout the study (median: 0.186 µg CH4-C m−2 h−1) and uplands increased in sink strength with dry down of the watershed (median: −22.9 µg CH4-C m−2 h−1). Locations with volumetric water content (VWC) below 38 % were methane sinks, and uptake increased with decreasing VWC. Above 43 % VWC, net CH4 efflux occurred, and at intermediate VWC net fluxes were near zero. Riparian sites had near neutral cumulative seasonal flux, and cumulative uptake of CH4 in the uplands was significantly related to topographic indices. These relationships were used to model the net seasonal CH4 flux of the upper Stringer Creek watershed (−1.75 kg CH4-C ha−1). This spatially distributed estimate was 111 % larger than that obtained by simply extrapolating the mean CH4 flux to the entire watershed area. Our results highlight the importance of quantifying the space-time variability of net CH4 fluxes as predicted by the frequency distribution of landscape positions when assessing watershed scale greenhouse gas balances.

Most of the Earth System Models (ESMs) project increases in net primary productivity (NPP) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO2, none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from (1) changes in C stocks and (2) changes in NPP. The C stock‐based additional P demand was estimated to range between −31 and 193 Tg P and between −89 and 262 Tg P for Representative Concentration Pathway (RCP) 2.6 and RCP8.5, respectively, with negative values indicating a P surplus. The NPP‐based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648–1606 Tg P for RCP2.6 and 924–2110 Tg P for RCP8.5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP‐based demand and C stock‐based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Overall, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.

Pollen assemblages from 50 small hollows were used to resolve fire-caused vegetation patterns in a ~2-km2 subalpine landscape on the Central Plateau of Tasmania, Australia. Sites were characterized by varying abundance of the dominant tree species, Athrotaxis cupressoides, reflecting mortality from a wildfire that occurred 53 years prior to sampling. Sites were classified a priori based on fire-related Athrotaxis mortality as burned (100% standing dead), unburned (<5% standing dead), and mixed (intermediate proportions). Non-parametric analysis of variance and discriminant analysis were used to quantify the variability in key pollen taxa and pollen ratios among burn classifications. The ratio of Athrotaxis to Poaceae pollen was the clearest metric distinguishing among burn classifications. When discriminant analysis was informed with data from the eight most dominant pollen data, samples were classified with high accuracy (0.96–0.98). Macroscopic charcoal concentrations varied widely among sites, but median values were consistent with inferred fire patterns, increasing in abundance from unburned to burned sites. The results support the use of small hollows to resolve fine-scale vegetation patterns (e.g. within 100 m of a site). The discriminant analysis function was also applied to five late-Holocene pollen samples from the study area, to test the potential of these methods to classify samples with unknown group assignments. The posterior probability of assigned group membership ranged from 0.85 to 0.99, demonstrating the similarity of the fossil pollen to the calibration dataset. Our calibration dataset provides a means to classify fossil samples from the region in terms of Athrotaxis cover and fire-caused mortality. This approach could be applied to other regions to quantify disturbance-related vegetation patterns or spatial heterogeneity over Holocene timescales.

Year-to-year variations in the atmospheric methane (CH4) growth rate show significant correlation with climatic drivers. The second half of 2010 and the first half of 2011 experienced the strongest La Niña since the early 1980s, when global surface networks started monitoring atmospheric CH4 mole fractions. We use these surface measurements, retrievals of column-averaged CH4 mole fractions from GOSAT, new wetland inundation estimates, and atmospheric δ13C-CH4 measurements to estimate the impact of this strong La Niña on the global atmospheric CH4 budget. By performing atmospheric inversions, we find evidence of an increase in tropical CH4 emissions of ∼6–9 TgCH4 yr−1 during this event. Stable isotope data suggest that biogenic sources are the cause of this emission increase. We find a simultaneous expansion of wetland area, driven by the excess precipitation over the Tropical continents during the La Niña. Two process-based wetland models predict increases in wetland area consistent with observationally-constrained values, but substantially smaller per-area CH4 emissions, highlighting the need for improvements in such models. Overall, tropical wetland emissions during the strong La Niña were at least by 5% larger than the long-term mean.

Abstract Reliable detection of nonnative alleles is crucial for the conservation of sensitive native fish populations at risk of introgression. Typically, nonnative alleles in a population are detected through the analysis of genetic markers in a sample of individuals. Here we show that common assumptions associated with such analyses yield substantial overestimates of the likelihood of detecting nonnative alleles. We present a revised equation to estimate the likelihood of detecting nonnative alleles in a population with a given level of admixture. The new equation incorporates the effects of the genotypic structure of the sampled population and shows that conventional methods overestimate the likelihood of detection, especially when nonnative or F-1 hybrid individuals are present. Under such circumstances—which are typical of early stages of introgression and therefore most important for conservation efforts—our results show that improved detection of nonnative alleles arises primarily from increasing the number of individuals sampled rather than increasing the number of genetic markers analyzed. Using the revised equation, we describe a new approach to determining the number of individuals to sample and the number of diagnostic markers to analyze when attempting to monitor the arrival of nonnative alleles in native populations.