Red deer mediate spatial and temporal plant heterogeneity in boreal forests

Selective herbivory can influence both spatial and temporal vegetation heterogeneity. For example, many northern European populations of free-ranging ungulates have reached unprecedented levels, which can influence plant species turnover, long-term maintenance of biodiversity and the subsequent stability of boreal ecosystems. However, the mechanisms by which large herbivores affect spatial and temporal vegetation heterogeneity remain poorly understood. Here, we combined a 10-year exclusion experiment with a herbivore intensity gradient to investigate how red deer (Cervus elaphus) acts as a driver of temporal and spatial heterogeneity in the understory of a boreal forest. We measured the two dimensions of heterogeneity as temporal and spatial species turnover. We found that temporal heterogeneity was positively related to herbivory intensity, and we found a similar trend for spatial heterogeneity. Removing red deer (exclosure) from our study system caused a distinct shift in species composition, both spatially (slow response) and temporally (quick response). Vegetation from which red deer had been excluded for 10 years showed the highest spatial heterogeneity, suggesting that the most stable forest understory will occur where there are no large herbivores. However, excluding red deer resulted in lower species diversity and greater dominance by a low number of plant species. If both stable but species rich ecosystems are the management goal, these findings suggest that naturally fluctuating, but moderate red deer densities should be sustained.     

Plant community composition as a driver of decomposition dynamics in riparian wetlands

Riparian wetlands are well known for providing the important ecosystem service of carbon storage. However, changes in land-use regimes surrounding riparian wetlands have been shown to result in alterations to the wetland plant community. These plant community changes have the potential to alter litter quality, decomposition rates, and ultimately the capacity of riparian wetlands to store carbon. To determine the effects of plant community shifts associated with disturbance on decomposition and carbon inputs, we performed a yearlong decomposition experiment using in situ herbaceous material, leaf litter, and control litter and examined biomass inputs in six headwater riparian wetlands in central Pennsylvania. Two sites were classified as Hemlock-Mixed Hardwood Palustrine Forest, two were classified as Broadleaf Palustrine Forest, and two were classified as Reed Canary Grass-Floodplain Grassland (Zimmerman et al. 2012). Plant matter with greater initial percent C, percent lignin, and lignin:N ratios decomposed more slowly while plant matter with greater initial cellulose decomposed more quickly. However, no significant differences were found between plant community types in decomposition rate or amount of carbon remaining at the end of the experiment, indicating that the differences in plant community type did not have a large impact on decomposition in riparian wetlands. This work has important implications for studies that examine the decomposition dynamics of a few select species, as they may not capture the decomposition dynamics of the plant community and thus extrapolating results from these studies to the larger ecosystem may be inappropriate.     

Indonesia’s blue carbon: a globally significant and vulnerable sink for seagrass and mangrove carbon

The global significance of carbon storage in Indonesia’s coastal wetlands was assessed based on published and unpublished measurements of the organic carbon content of living seagrass and mangrove biomass and soil pools. For seagrasses, median above- and below-ground biomass was 0.29 and 1.13 Mg C ha^?1 respectively; the median soil pool was 118.1 Mg C ha^?1. Combining plant biomass and soil, median carbon storage in an Indonesian seagrass meadow is 119.5 Mg C ha^?1. Extrapolated to the estimated total seagrass area of 30,000 km², the national storage value is 368.5 Tg C. For mangroves, median above- and below-ground biomass was 159.1 and 16.7 Mg C ha^?1, respectively; the median soil pool was 774.7 Mg C ha^?1. The median carbon storage in an Indonesian mangrove forest is 950.5 Mg C ha^?1. Extrapolated to the total estimated mangrove area of 31,894 km², the national storage value is 3.0 Pg C, a likely underestimate if these habitats sequester carbon at soil depths >1 m and/or sequester inorganic carbon. Together, Indonesia’s seagrasses and mangroves conservatively account for 3.4 Pg C, roughly 17 % of the world’s blue carbon reservoir. Continued degradation and destruction of these wetlands has important consequences for CO₂ emissions and dissolved carbon exchange with adjacent coastal waters. We estimate that roughly 29,040 Gg CO₂ (eq.) is returned annually to the atmosphere–ocean pool. This amount is equivalent to about 3.2 % of Indonesia’s annual emissions associated with forest and peat land conversion. These results highlight the urgent need for blue carbon and REDD+ projects as a means to stem the decline in wetland area and to mitigate the release of a significant fraction of the world’s coastal carbon stores.     

Neural assemblies revealed by inferred connectivity-based models of prefrontal cortex recordings

We extend the theory of weakly coupled oscillators to incorporate slowly varying inputs and parameters. We employ a combination of regular perturbation and an adiabatic approximation to derive equations for the phase-difference between a pair of oscillators. We apply this to the simple Hopf oscillator and then to a biophysical model. The latter represents the behavior of a neuron that is subject to slow modulation of a muscarinic current such as would occur during transient attention through cholinergic activation. Our method extends and simplifies the recent work of Kurebayashi (Physical Review Letters, 111, 214101, 2013) to include coupling. We apply the method to an all-to-all network and show that there is a waxing and waning of synchrony of modulated neurons.     

Modeling the effects of extracellular potassium on bursting properties in pre-Bötzinger complex neurons

There are many types of neurons that intrinsically generate rhythmic bursting activity, even when isolated, and these neurons underlie several specific motor behaviors. Rhythmic neurons that drive the inspiratory phase of respiration are located in the medullary pre-Bötzinger Complex (pre-BötC). However, it is not known if their rhythmic bursting is the result of intrinsic mechanisms or synaptic interactions. In many cases, for bursting to occur, the excitability of these neurons needs to be elevated. This excitation is provided in vitro (e.g. in slices), by increasing extracellular potassium concentration (K _out ) well beyond physiologic levels. Elevated K _out shifts the reversal potentials for all potassium currents including the potassium component of leakage to higher values. However, how an increase in K _out , and the resultant changes in potassium currents, induce bursting activity, have yet to be established. Moreover, it is not known if the endogenous bursting induced in vitro is representative of neural behavior in vivo. Our modeling study examines the interplay between K _out , excitability, and selected currents, as they relate to endogenous rhythmic bursting. Starting with a Hodgkin-Huxley formalization of a pre-BötC neuron, a potassium ion component was incorporated into the leakage current, and model behaviors were investigated at varying concentrations of K _out . Our simulations show that endogenous bursting activity, evoked in vitro by elevation of K _out , is the result of a specific relationship between the leakage and voltage-dependent, delayed rectifier potassium currents, which may not be observed at physiological levels of extracellular potassium.     

Convergent neuromodulation onto a network neuron can have divergent effects at the network level

Different neuromodulators often target the same ion channel. When such modulators act on different neuron types, this convergent action can enable a rhythmic network to produce distinct outputs. Less clear are the functional consequences when two neuromodulators influence the same ion channel in the same neuron. We examine the consequences of this seeming redundancy using a mathematical model of the crab gastric mill (chewing) network. This network is activated in vitro by the projection neuron MCN1, which elicits a half-center bursting oscillation between the reciprocally-inhibitory neurons LG and Int1. We focus on two neuropeptides which modulate this network, including a MCN1 neurotransmitter and the hormone crustacean cardioactive peptide (CCAP). Both activate the same voltage-gated current (I _MI ) in the LG neuron. However, I _MI-MCN1 , resulting from MCN1 released neuropeptide, has phasic dynamics in its maximal conductance due to LG presynaptic inhibition of MCN1, while I _MI-CCAP retains the same maximal conductance in both phases of the gastric mill rhythm. Separation of time scales allows us to produce a 2D model from which phase plane analysis shows that, as in the biological system, I _MI-MCN1 and I _MI-CCAP primarily influence the durations of opposing phases of this rhythm. Furthermore, I _MI-MCN1 influences the rhythmic output in a manner similar to the Int1-to-LG synapse, whereas I _MI-CCAP has an influence similar to the LG-to-Int1 synapse. These results show that distinct neuromodulators which target the same voltage-gated ion channel in the same network neuron can nevertheless produce distinct effects at the network level, providing divergent neuromodulator actions on network activity.     

Ion channel noise can explain firing correlation in auditory nerves

Sensory neurons code information about stimuli in their sequence of action potentials (spikes). Intuitively, the spikes should represent stimuli with high fidelity. However, generating and propagating spikes is a metabolically expensive process. It is therefore likely that neural codes have been selected to balance energy expenditure against encoding error. Our recently proposed optimal, energy-constrained neural coder (Jones et al. Frontiers in Computational Neuroscience, 9, 61 2015) postulates that neurons time spikes to minimize the trade-off between stimulus reconstruction error and expended energy by adjusting the spike threshold using a simple dynamic threshold. Here, we show that this proposed coding scheme is related to existing coding schemes, such as rate and temporal codes. We derive an instantaneous rate coder and show that the spike-rate depends on the signal and its derivative. In the limit of high spike rates the spike train maximizes fidelity given an energy constraint (average spike-rate), and the predicted interspike intervals are identical to those generated by our existing optimal coding neuron. The instantaneous rate coder is shown to closely match the spike-rates recorded from P-type primary afferents in weakly electric fish. In particular, the coder is a predictor of the peristimulus time histogram (PSTH). When tested against in vitro cortical pyramidal neuron recordings, the instantaneous spike-rate approximates DC step inputs, matching both the average spike-rate and the time-to-first-spike (a simple temporal code). Overall, the instantaneous rate coder relates optimal, energy-constrained encoding to the concepts of rate-coding and temporal-coding, suggesting a possible unifying principle of neural encoding of sensory signals.     

Calcium dependent plasticity applied to repetitive transcranial magnetic stimulation with a neural field model

The calcium dependent plasticity (CaDP) approach to the modeling of synaptic weight change is applied using a neural field approach to realistic repetitive transcranial magnetic stimulation (rTMS) protocols. A spatially-symmetric nonlinear neural field model consisting of populations of excitatory and inhibitory neurons is used. The plasticity between excitatory cell populations is then evaluated using a CaDP approach that incorporates metaplasticity. The direction and size of the plasticity (potentiation or depression) depends on both the amplitude of stimulation and duration of the protocol. The breaks in the inhibitory theta-burst stimulation protocol are crucial to ensuring that the stimulation bursts are potentiating in nature. Tuning the parameters of a spike-timing dependent plasticity (STDP) window with a Monte Carlo approach to maximize agreement between STDP predictions and the CaDP results reproduces a realistically-shaped window with two regions of depression in agreement with the existing literature. Developing understanding of how TMS interacts with cells at a network level may be important for future investigation.     

Modelling zinc changes at the hippocampal mossy fiber synaptic cleft

Zinc, a transition metal existing in very high concentrations in the hippocampal mossy fibers from CA3 area, is assumed to be co-released with glutamate and to have a neuromodulatory role at the corresponding synapses. The synaptic action of zinc is determined both by the spatiotemporal characteristics of the zinc release process and by the kinetics of zinc binding to sites located in the cleft area, as well as by their concentrations. This work addresses total, free and complexed zinc concentration changes, in an individual synaptic cleft, following single, short and long periods of evoked zinc release. The results estimate the magnitude and time course of the concentrations of zinc complexes, assuming that the dynamics of the release processes are similar to those of glutamate. It is also considered that, for the cleft zinc concentrations used in the model (≤ 1 μM), there is no postsynaptic zinc entry. For this reason, all released zinc ends up being reuptaken in a process that is several orders of magnitude slower than that of release and has thus a much smaller amplitude. The time derivative of the total zinc concentration in the cleft is represented by the difference between two alpha functions, corresponding to the released and uptaken components. These include specific parameters that were chosen assuming zinc and glutamate co-release, with similar time courses. The peak amplitudes of free zinc in the cleft were selected based on previously reported experimental cleft zinc concentration changes evoked by single and multiple stimulation protocols. The results suggest that following a low amount of zinc release, similar to that associated with one or a few stimuli, zinc clearance is mainly mediated by zinc binding to the high-affinity sites on the NMDA receptors and to the low-affinity sites on the highly abundant GLAST glutamate transporters. In the case of higher zinc release brought about by a larger group of stimuli, most zinc binding occurs essentially to the GLAST transporters, having the corresponding zinc complex a maximum concentration that is more than one order of magnitude larger than that for the high and low affinity NMDA sites. The other zinc complexes considered in the model, namely those formed with sites on the AMPA receptors, calcium and K_ATP channels and with ATP molecules, have much smaller contributions to the synaptic zinc clearance.