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Temperature increases associated with global climate change are likely to be accompanied by additional environmental stressors such as desiccation and food limitation, which may alter how temperature impacts organismal performance. To investigate how interactions between stressors influence thermal tolerance in the common forest ant, Aphaenogaster picea, we compared the thermal resistance of workers to heat shock with and without pre-exposure to desiccation or starvation stress. Knockdown (KD) time at 40.5 °C of desiccated ants was reduced 6% compared to controls, although longer exposure to desiccation did not further reduce thermal tolerance. Starvation, in contrast, had an increasingly severe effect on thermal tolerance: at 21 days, average KD time of starved ants was reduced by 65% compared to controls. To test whether reduction in thermal tolerance results from impairment of the heat-shock response, we measured basal gene expression and transcriptional induction of two heat-shock proteins (hsp70 and hsp40) in treated and control ants. We found no evidence that either stressor impaired the Hsp response: both desiccation and starvation slightly increased basal Hsp expression under severe stress conditions and did not affect the magnitude of induction under heat shock. These results suggest that the co-occurrence of multiple environmental stressors predicted by climate change models may make populations more vulnerable to future warming than is suggested by the results of single-factor heating experiments.

Storing and extracting heat during different seasons of the year is possible through the utilization of a ground aquifer with an open loop Ground Source Heat Pump (GSHP) system. Being able to predict the hydrothermal performance of geothermal storage is required for an efficient operation of the system for cooling and heating of buildings. Complex 2D and 3D hydrothermal numerical models can simulate the thermal performance of geothermal storage accurately but often lack the desired computational speed for conducting large number of simulations for performance optimization. Instead, a 1D radial model can be used to conduct fast evaluation. However, it is important that the model computes the amount of heat loss from an aquifer into the overburden and underlying layers accurately to evaluate the amount of geothermal storage in the aquifer at different times. In this study, a source term is introduced into a 1D model to simulate the heat transfer between the aquifer and caprock/baserock in the vertical direction. The following two heat loss models are introduced in the heat advection-conduction equation: (i) Newton’s heating/cooling law, which leads to a closed form solution, and (ii) a conduction-based semi-analytical model, which requires a 1D finite element solution. When compared to a full 2D axisymmetric simulation result, it was found that the Newton’s heating/cooling law model with a constant heat transfer coefficient works well in cases of fast heat flow rate in thick aquifers of around 100 meters. But large errors in estimating heat dissipation are observed in cases with low heat flow rate in thin aquifers, especially for simulations exceeding two to five years. On the other hand, the model with the conduction-based semi-analytical solution gives a better match for these conditions.

Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

Widespread tree mortality associated with drought has been observed on all forested continents and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analysed across species and biomes using a standardized physiological framework. Here, we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought-induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function.

When a host organism is infected by a symbiont, the resulting symbiotum has a phenotype distinct from uninfected hosts. Genotypic interactions between the partners may increase phenotypic variation of the host at the population level. Neotyphodium is an asexual, vertically transmitted endophytic symbiont of grasses often existing in hybrid form. Hybridization in Neotyphodium rapidly increases the symbiotum's genomic content and is likely to increase the phenotypic variation of the host. This phenotypic variation is predicted to enhance host performance, especially in stressful environments. We tested this hypothesis by comparing the growth, survival, and resource allocation of hybrid and nonhybrid infected host plants exposed to controlled variation in soil moisture and nutrients. Infection by a hybrid endophyte did not fit our predictions of comparatively higher root and total biomass production under low moisture/low nutrient treatments. Regardless of whether the host was infected by a hybrid or nonhybrid endophyte, both produced significantly higher root/total biomass when both nutrient and moisture were high compared to limited nutrient/moisture treatments. However, infection by hybrid Neotyphodium did result in significantly higher total biomass and host survival compared to nonhybrid infected hosts, regardless of treatment. Endophyte hybridization alters host strategies in response to stress by increasing survival in depauperate habitats and thus, potentially increasing the relative long-term host fitness.

Pathogens are common and diverse in natural communities and have been implicated in the success of host invasions. Yet few studies have experimentally measured how pathogens impact native versus exotic hosts, particularly when individual hosts are simultaneously coinfected by diverse pathogens. To estimate effects of interactions among multiple pathogens within host individuals on both transmission of pathogens and fitness consequences for hosts, we conducted a greenhouse experiment using California grassland species: the native perennial grass Nassella (Stipa) pulchra, the exotic annual grass Bromus hordeaceus, and three virus species, Barley yellow dwarf virus-PAV, Barley yellow dwarf virus-MAV, and Cereal yellow dwarf virus-RPV. In terms of virus transmission, the native host was less susceptible than the exotic host to MAV. Coinfection of PAV and MAV did not occur in any of the 157 co-inoculated native host plants. In the exotic host, PAV infection most strongly reduced root and shoot biomass, and coinfections that included PAV severely reduced biomass. Infection with single or multiple viruses did not affect biomass in the native host. However, in this species the most potentially pathogenic coinfections (PAV + MAV and PAV + MAV + RPV) did not occur. Together, these results suggest that interactions among multiple pathogens can have important consequences for host health, which may not be predictable from interactions between hosts and individual pathogens. This work addresses a key empirical gap in understanding the impact of multiple generalist pathogens on competing host species, with potential implications for population and community dynamics of native and exotic species. It also demonstrates how pathogens with relatively mild impacts independently can more substantially reduce host performance in coinfection.

Over the past century at the National Bison Range, temperature has increased by 0.6 °C, and annual precipitation has decreased by 26%, despite increases in May-June precipitation over the past 35 years. Limited experimental work to date has explored plant responses produced by the interaction of changes in both temperature and precipitation, and of the existing studies, none have focused on the endangered bunchgrass ecosystem. Using a 2-year climate change manipulation experiment, we show that bunchgrass productivity increased with supplemental growing season precipitation, while warming alone exerted no significant effect. More importantly, the ratio of June precipitation to minimum temperature, a representation of the interaction of climate variables, predicted bunchgrass productivity better than either climate variable individually. This ratio acted as a surrogate index reflecting increased evapotranspiration with rising temperatures and thus better predicting soil moisture available for plant growth. Experimental warming over the summer led to significantly lower plant species richness and biodiversity, while increased precipitation, when applied over the entire summer, counteracted some of these declines. Warming also led to greater and more rapid plant senescence over the summer, resulting in greater litter production [an increase of 47.82 ± 17.82 (± SE) percentage points] and potential fire risk. Given the simultaneous changes in precipitation and temperature predicted for the next century, multi-factor experiments are essential to understand how ecosystems will respond to future climate scenarios.