[1] The fate of biologically available nitrogen (N) and carbon (C) in stream ecosystems is controlled by the coupling of physical transport and biogeochemical reaction kinetics. However, determining the relative role of physical and biogeochemical controls at different temporal and spatial scales is difficult. The hyporheic zone (HZ), where groundwaterstream water mix, can be an important location controlling N and C transformations because it creates strong gradients in both the physical and biogeochemical conditions that control redox biogeochemistry. We evaluated the coupling of physical transport and biogeochemical redox reactions by linking an advection, dispersion, and residence time model with a multiple Monod kinetics model simulating the concentrations of oxygen (O 2 ), ammonium (NH 4 ), nitrate (NO 3 ), and dissolved organic carbon (DOC). We used global Monte Carlo sensitivity analyses with a nondimensional form of the model to examine coupled nitrification-denitrification dynamics across many scales of transport and reaction conditions. Results demonstrated that the residence time of water in the HZ and the uptake rate of O 2 from either respiration and/or nitrification determined whether the HZ was a source or a sink of NO 3 to the stream. We further show that whether the HZ is a net NO 3 source or net NO 3 sink is determined by the ratio of the characteristic transport time to the characteristic reaction time of O 2 (i.e., the Damköhler number, Da O2 ), where HZs with Da O2 < 1 will be net nitrification environments and HZs with Da O2 ) 1 will be net denitrification environments.Ã Our coupling of the hydrologic and biogeochemical limitations of N transformations across different temporal and spatial scales within the HZ allows us to explain the widely contrasting results of previous investigations of HZ N dynamics which variously identify the HZ as either a net source or sink of NO 3 . Our model results suggest that only estimates of residence times and O 2 uptake rates are necessary to predict this nitrification-denitrification threshold and, ultimately, whether a HZ will be either a net source or sink of NO 3 .Citation: Zarnetske, J. P., R. Haggerty, S. M. Wondzell, V. A. Bokil, and R. González-Pinzón (2012), Coupled transport and reaction kinetics control the nitrate source-sink function of hyporheic zones, Water Resour. Res., 48, W11508,

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Summary 1.The spatial distribution of species is mediated by a combination of biotic interactions and environmental conditions. Understanding the relative importance of these factors and how they interact is particularly important for predicting the spread of non-native species and their impact on resident communities. 2. We used a 3-species Lotka-Volterra model parameterized with field and experimental data to understand the potential for continued spread by an introduced, non-native, dune-building beach grass (Ammophila breviligulata) and whether this invasion will result in coexistence or displacement in the resident beach grass communities (native Elymus mollis and introduced, non-native Ammophila arenaria) of the US Pacific Northwest. 3. We also used the model to investigate to what extent different rates of ocean-driven sand supply mediate the outcomes of beach grass species interactions. 4. Our model suggests that A. breviligulata could invade and dominate dunes across the range of sand supply rates observed in the region. We found that sand supply influenced intra-vs. interspecific interactions, the strength of positive and indirect effects among beach grasses and the long-term abundances of the beach grass species themselves. 5. Of the two non-natives, A. breviligulata is the inferior dune-building species. Thus, our results suggest that further invasions by A. breviligulata could reduce the coastal protection services afforded by tall dunes currently dominated by A. arenaria. 6. Synthesis: In systems with strong environmental forcing and stressful conditions such as coastal dunes, environmentally mediated positive and indirect species interactions can govern invasion success and long-term native-non-native coexistence. In doing so, these interactions ultimately shape community structure and ecosystem function. Understanding the joint effects of environmental forcing and species interactions on community assembly is particularly important in cases where species introductions can alter ecosystem services, such as coastal protection, which are vulnerable to the effects of climate change.

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models.

Vector-transmitted diseases of plants have had devastating effects on agricultural production worldwide, resulting in drastic reductions in yield for crops such as cotton, soybean, tomato, and cassava. Plant-vector-virus models with continuous replanting are investigated in terms of the effects of selection of cuttings, roguing, and insecticide use on disease prevalence in plants. Previous models are extended to include two replanting strategies: frequencyreplanting and abundance-replanting. In frequency-replanting, replanting of infected cuttings depends on the selection frequency parameter , whereas in abundance-replanting, replanting depends on plant abundance via a selection rate parameter also denoted as. The two models are analysed and new thresholds for disease elimination are defined for each model. Parameter values for cassava, whiteflies, and African cassava mosaic virus serve as a case study. A numerical sensitivity analysis illustrates how the equilibrium densities of healthy and infected plants vary with parameter values. Optimal control theory is used to investigate the effects of roguing and insecticide use with a goal of maximizing the healthy plants that are harvested. Differences in the control strategies in the two models are seen for large values of. Also, the combined strategy of roguing and insecticide use performs better than a single control.