Stomatal regulation is crucial for forest species performance and survival on drought‐prone sites. We investigated the regulation of root and shoot hydraulics in three Pinus radiata clones exposed to drought stress and its coordination with stomatal conductance (gs) and leaf water potential (Ψleaf). All clones experienced a substantial decrease in root‐specific root hydraulic conductance (Kroot‐r) in response to the water stress, but leaf‐specific shoot hydraulic conductance (Kshoot‐l) did not change in any of the clones. The reduction in Kroot‐r caused a decrease in leaf‐specific whole‐plant hydraulic conductance (Kplant‐l). Among clones, the larger the decrease in Kplant‐l, the more stomata closed in response to drought. Rewatering resulted in a quick recovery of Kroot‐r and gs. Our results demonstrated that the reduction in Kplant‐l, attributed to a down regulation of aquaporin activity in roots, was linked to the isohydric stomatal behaviour, resulting in a nearly constant Ψleaf as water stress started. We concluded that higher Kplant‐l is associated with water stress resistance by sustaining a less negative Ψleaf and delaying stomatal closure.

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Plant root simulator (PRS) probes, a resin membrane technology, are increasingly used to measure soil nutrient availability in agricultural and nonagricultural systems. Like other resin technologies, the charged surface is meant to sorb nutrients until saturation; however, there is evidence that it acts as a dynamic exchanger in soils with low nutrient availability. This study compared the nutrient sorption dynamics of PRS probes during an 8‐wk period in a young Andisol forest soil on the island of Hawaii with and without P fertilization. Resin bags, a more established technology, were used to measure nutrient availability as a comparison. The PRS probe sorption dynamics differed for the six nutrients measured. Except for NO3, nutrient sorption appeared to reach equilibrium with the soil labile pools after 4 wk. Resin bags acted as an infinite sink for NH4+, NO3−, and PO43− and sorbed more than the PRS probes. Both technologies detected an increase in P availability due to fertilization. A comparison of nutrient availability from PRS probes and resin bags correlated poorly. Isolation of the PRS probes and resin bags from root activity did not improve measurements of labile nutrients. More research is required to understand the processes behind the apparent desorption of nutrients from the PRS probes in acidic forest soils. If used for a minimum of 4 wk, however, the PRS probes appear to provide an equilibrium measure of labile soil nutrients with high sensitivity to treatment differences.

A central challenge in community ecology is understanding the role that phenotypic variation among genotypes plays in structuring host-associated communities. While recent studies have investigated the relationship between plant genotype and the composition of soil microbial communities, the effect of genotype-by-environment interactions on the plant microbiome remains unclear. In this study, we assessed the influence of tree genetics (G), nitrogen (N) form and genotype-by-environment interaction (G x N) on the composition of the root microbiome. Rhizosphere communities (bacteria and fungi) and root-associated fungi (including ectomycorrhizal and saprotrophic guilds) were characterised in two genotypes of Pinus radiata with contrasting physiological responses to exogenous organic or inorganic N supply. Genotype-specific responses to N form influenced the composition of the root microbiome. Specifically, (1) diversity and composition of rhizosphere bacterial and root-associated fungal communities differed between genotypes that had distinct responses to N form, (2) shifts in the relative abundance of individual taxa were driven by the main effects of N form or host genotype and (3) the root microbiome of the P. radiata genotype with the most divergent growth responses to organic and inorganic N was most sensitive to differences in N form. Our results show that intraspecific variation in tree response to N form has significant consequences for the root microbiome of P. radiata, demonstrating the importance of genotype-by-environment interactions in shaping host-associated communities.

& Context A strategy widely proposed for increasing the resilience of forests against the impacts of projected climate change is to increase the number of species planted to spread and reduce the risks from a range of biotic and abiotic hazards. & Aims We tested this strategy in two case study areas in planted conifer forests in New Zealand and Scotland. & Methods The performance of the major tree species and an alternative was compared: radiata pine and Eucalyptus fastigata in New Zealand and Sitka spruce and Scots pine in Scotland. The process-based model 3-PG2S was used to simulate the effects of projected climate change at the end of this century, with and without CO 2 fertilisation, upon productivity and financial returns. The effects of an abiotic hazard and two biotic hazards were considered. & Results Under the current climate, the major species outperform alternatives in nearly all circumstances. However, with climate change, their relative performance alters. In New Zealand, planting of E. fastigata becomes more attractive particularly when various hazards and elevated CO 2 concentrations are considered. In Scotland, Scots pine becomes more attractive than Sitka spruce at lower interest rates. & Conclusions The major plantation species in both countries are well suited to the current climate, but deployment of alternative species and/or breeds can help to adapt these planted forests to the impacts of climate change.

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Abstract:It is common to generate digital elevation models (DEMs) from aerial laser scanning (ALS) data. However, cost and lack of knowledge may preclude its use. In contrast, global navigation satellite systems (GNSS) are seldom used to collect and generate DEMs. These receivers have the potential to be considered as data sources for DEM interpolation, as they can be inexpensive, easy to use, and mobile. The data interpolation method and spatial resolution from this method needs to be optimised to create accurate DEMs. Moreover, the density of GNSS data is likely to affect DEM accuracy. This study investigates three different deterministic approaches, in combination with spatial resolution and data thinning, to determine their combined effects on DEM accuracy. Digital elevation models were interpolated, with resolutions ranging from 0.5 m to 10 m using natural neighbour (NaN), topo to raster (ANUDEM), and inverse distance weighted (IDW) methods. The GNSS data were thinned by 25% (0.389 points m −2 ), 50% (0.259 points m −2 ), and 75% (0.129 points m −2 ) and resulting DEMs were contrast against a DEM interpolated from unthinned data (0.519 points m −2 ). Digital elevation model accuracy was measured by root mean square error (RMSE) and mean absolute error (MAE). It was found that the highest resolution, 0.5 m, produced the lowest errors in resulting DEMs (RMSE = 0.428 m, MAE = 0.274 m). The ANUDEM method yielded the greatest DEM accuracy from a quantitative perspective (RMSE = 0.305 m and MAE = 0.197 m); however, NaN produced a more visually appealing surface. In all the assessments, IDW showed the lowest accuracy. Thinning the input data by 25% and even 50% had relatively little impact on DEM quality; however, accuracy decreased markedly at 75% thinning (0.129 points m −2 ). This study showed that, in a time where ALS is commonly used to generate DEMs, GNSS-surveyed data can be used to create accurate DEMs. This study confirmed the need for optimization to choose the appropriate interpolation method and spatial resolution in order to produce a reliable DEM.