Variation in the resilience of cloud forest vascular epiphytes to severe drought.

Epiphytes are common in tropical montane cloud forests (TMCFs) and play many important ecological roles, but the degree to which these unique plants will be affected by changes in climate is unknown. We investigated the drought responses of three vascular epiphyte communities bracketing the cloud base during a severe, El Niño-impacted dry season. Epiphytes were instrumented with sap flow probes in each site. Leaf water potential and pressure-volume curve parameters were also measured before and during the drought. We monitored the canopy microclimate in each site to determine the drivers of sap velocity across the sites. All plants greatly reduced their water use during the drought, but recovery occurred more quickly for plants in the lower and drier sites. Plants in drier sites also exhibited the greatest shifts in the osmotic potential at full saturation and the turgor loss point. Although all individuals survived this intense drought, epiphytes in the cloud forest experienced the slowest recovery, suggesting that plants in the TMCF are particularly sensitive to severe drought. Although vapor pressure deficit was an important driver of sap velocity in the highest elevation site, other factors, such as the volumetric water content of the canopy soil, were more important at lower (and warmer) sites.

Vapor pressure deficit predicts epiphyte abundance across an elevational gradient in a tropical montane region.

PREMISE OF THE STUDY: Tropical Montane Cloud Forests (TMCFs) are important ecosystems to study and preserve because of their high biodiversity and critical roles in local and regional ecosystem processes. TMCFs may be particularly affected by changes in climate because of the narrow bands of microclimate they occupy and the vulnerability of TMCF species to projected increases in cloud base heights and drought. A comprehensive understanding of the structure and function of TMCFs is lacking and difficult to attain because of variation in topography within and across TMCF sites. This causes large differences in microclimate and forest structure at both large and small scales. METHODS: In this study, we estimated the abundance of the entire epiphyte community in the canopy (bryophytes, herbaceous vascular plants, woody epiphytes, and canopy dead organic matter) in six sites. In each of the sites we installed a complete canopy weather station to link epiphyte abundance to a number of microclimatic parameters. KEY RESULTS: We found significant differences in epiphyte abundance across the sites; epiphyte abundance increased with elevation and leaf wetness, but decreased as vapor pressure deficit (VPD) increased. Epiphyte abundance had the strongest relationship with VPD; there were differences in VPD that could not be explained by elevation alone. CONCLUSIONS: By measuring this proxy of canopy VPD, TMCF researchers will better understand differences in microclimate and plant community composition across TMCF sites. Incorporating such information in comparative studies will allow for more meaningful comparisons across TMCFs and will further conservation and management efforts in this ecosystem.

Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons.

Conductance-based compartment modeling requires tuning of many parameters to fit the neuron model to target electrophysiological data. Automated parameter optimization via evolutionary algorithms (EAs) is a common approach to accomplish this task, using error functions to quantify differences between model and target. We present a three-stage EA optimization protocol for tuning ion channel conductances and kinetics in a generic neuron model with minimal manual intervention. We use the technique of Latin hypercube sampling in a new way, to choose weights for error functions automatically so that each function influences the parameter search to a similar degree. This protocol requires no specialized physiological data collection and is applicable to commonly-collected current clamp data and either single- or multi-objective optimization. We applied the protocol to two representative pyramidal neurons from layer 3 of the prefrontal cortex of rhesus monkeys, in which action potential firing rates are significantly higher in aged compared to young animals. Using an idealized dendritic topology and models with either 4 or 8 ion channels (10 or 23 free parameters respectively), we produced populations of parameter combinations fitting the target datasets in less than 80 hours of optimization each. Passive parameter differences between young and aged models were consistent with our prior results using simpler models and hand tuning. We analyzed parameter values among fits to a single neuron to facilitate refinement of the underlying model, and across fits to multiple neurons to show how our protocol will lead to predictions of parameter differences with aging in these neurons.

Habitat moisture is an important driver of patterns of sap flow and water balance in tropical montane cloud forest epiphytes.

Microclimate in the tropical montane cloud forest (TMCF) is variable on both spatial and temporal scales and can lead to large fluctuations in both leaf-level transpiration and whole plant water use. While variation in transpiration has been found in TMCFs, the influence of different microclimatic drivers on plant water relations in this ecosystem has been relatively understudied. Within the TMCF, epiphytes may be particularly affected by natural variation in microclimate due to their partial or complete disassociation from soil resources. In this study, we examined the effects of seasonal microclimate on whole plant water balance in epiphytes in both an observational and a manipulative experiment. We also evaluated the effects of different microclimatic drivers using three hierarchical linear (mixed) models. On average, 31 % of total positive sap flow was recovered via foliar water uptake (FWU) over the course of the study. We found that precipitation was the greatest driver of foliar water uptake and nighttime sap flow in our study species and that both VPD and precipitation were important drivers to daytime sap flow. We also found that despite adaptations to withstand seasonal drought, an extended dry period caused severe desiccation in most plants despite a large reduction in leaf-level and whole plant transpiration. Our results indicate that the epiphytes studied rely on FWU to maintain positive water balance in the dry season and that increases in dry periods in the TMCF may be detrimental to these common members of the epiphyte community.

Network Models Predict That Pyramidal Neuron Hyperexcitability and Synapse Loss in the dlPFC Lead to Age-Related Spatial Working Memory Impairment in Rhesus Monkeys.

Behavioral studies have shown spatial working memory impairment with aging in several animal species, including humans. Persistent activity of layer 3 pyramidal dorsolateral prefrontal cortex (dlPFC) neurons during delay periods of working memory tasks is important for encoding memory of the stimulus. In vitro studies have shown that these neurons undergo significant age-related structural and functional changes, but the extent to which these changes affect neural mechanisms underlying spatial working memory is not understood fully. Here, we confirm previous studies showing impairment on the Delayed Recognition Span Task in the spatial condition (DRSTsp), and increased in vitro action potential firing rates (hyperexcitability), across the adult life span of the rhesus monkey. We use a bump attractor model to predict how empirically observed changes in the aging dlPFC affect performance on the Delayed Response Task (DRT), and introduce a model of memory retention in the DRSTsp. Persistent activity-and, in turn, cognitive performance-in both models was affected much more by hyperexcitability of pyramidal neurons than by a loss of synapses. Our DRT simulations predict that additional changes to the network, such as increased firing of inhibitory interneurons, are needed to account for lower firing rates during the DRT with aging reported in vivo. Synaptic facilitation was an essential feature of the DRSTsp model, but it did not compensate fully for the effects of the other age-related changes on DRT performance. Modeling pyramidal neuron hyperexcitability and synapse loss simultaneously led to a partial recovery of function in both tasks, with the simulated level of DRSTsp impairment similar to that observed in aging monkeys. This modeling work integrates empirical data across multiple scales, from synapse counts to cognitive testing, to further our understanding of aging in non-human primates.