Search

Grazing by livestock can alter the surface conditions at grassland sites, impacting the transfer of energy between the atmosphere and ground and consequentially ground temperatures. In this study, we investigate surface cover in summer and winter and measure ground surface temperatures over 14 months at sites in central Mongolia that feature different grazing intensities (intensely and ungrazed) and topographic aspects (north- and south-facing). Overall, intense grazing leads to a substantially reduced vegetation cover, altered snow conditions, and lack of surface litter accumulation. Comparing intensely grazed and ungrazed plots shows large seasonal differences in ground surface temperatures, with grazed plots being up to + 5.1 °C warmer in summer and - 5.4 °C colder in winter at a south-facing site. We also find that the effect of grazing intensity depends on topographic aspect, with smaller seasonal differences of + 1.4 °C and - 2.5 °C found between grazed and ungrazed plots at a north-facing site. This relates to the lower available solar radiation at north-facing sites, which reduces the differences in vegetation cover between open and fenced plots. For both aspects, the seasonal differences largely offset each other, with both a small net cooling and warming depending on effects in spring and autumn. Our study suggests that livestock management could be used to modify the annual ground temperature dynamics, possibly even influencing local permafrost dynamics. [ABSTRACT FROM AUTHOR]

Forests overlap with large parts of the northern hemisphere permafrost area, and representing canopy processes is therefore crucial for simulating thermal and hydrological conditions in these regions. Forests impact permafrost through the modulation of radiative fluxes and exchange of turbulent fluxes, precipitation interception and regulation of transpiration. Forests also feature distinct soil layers of litter and organic matter, which play central roles for the infiltration and evaporation of water, while also providing thermal insulation for deeper ground layers. In this study, we present a new module within the CryoGrid community model to simulate forest ecosystems and their impact on the surface water and energy balance. The module includes a big‐leaf vegetation scheme with adaptations for canopy heat storage and transpiration. Furthermore, we account for the effect of surface litter layers on water and energy transfer. We show that the model is capable of simulating radiation, snow cover and ground temperatures below a deciduous needleleaf forest on a north‐facing slope in the Khentii Mountains in Central Mongolia. A sensitivity analysis of topographic aspect and ecosystem configuration confirms the important role of the litter layers for the energy and water balance of the ground. Furthermore, it suggests that the presence of permafrost is primarily linked to topographic aspect rather than the presence of forest at this site. The presented model scheme can be used to study the development of the ground thermal regime in forests, including the state of permafrost, under different climate, ecosystem, and land use scenarios. Plain Language Summary: Large parts of the permafrost in the Northern Hemisphere are covered by forest, which impact the transfer of water and energy between the atmosphere and the ground. In this study we include single‐layer vegetation scheme in an established permafrost model, and test this for a site in Mongolia at the southern limit of Eurasian permafrost and boreal forest. We find that forest soils have smaller variations in ground temperature than on the nearby steppe, and that surface litter layers provide substantial insulation and soil water retention. Our simulations also suggest that the local distribution of permafrost in our study area is linked to topography rather than forest cover. The vegetation scheme is based on a global land surface model and represents a new modeling tool that readily can be used for further studies of permafrost‐ecosystem interactions. Key Points: Novel developments in the CryoGrid Community Model reproduce how forests dampen the seasonal ground surface temperature signalSurface litter layers are essential for forest ground hydrothermal regime as they provide thermal insulation and retain soil moisturePermafrost in our simulations is confined to north‐facing slopes in the study region regardless of ecosystem setup [ABSTRACT FROM AUTHOR]

During a midwinter cruise north of 80°N to Rijpfjorden, Svalbard, the composition and vertical distribution of the zooplankton community were studied using two different samplers 1) a vertically hauled multiple plankton sampler (MPS; mouth area 0.25 m2, mesh size 200 μm) and 2) a horizontally towed Methot Isaacs Kidd trawl (MIK; mouth area 3.14 m2, mesh size 1500 μm). Our results revealed substantially higher species diversity (49 taxa) than if a single sampler (MPS: 38 taxa, MIK: 28) had been used. The youngest stage present (CIII) of Calanus spp. (including C. finmarchicus and C. glacialis) was sampled exclusively by the MPS, and the frequency of CIV copepodites in MPS was double that than in MIK samples. In contrast, catches of the CV-CVI copepodites of Calanus spp. were substantially higher in the MIK samples (3-fold and 5-fold higher for adult males and females, respectively). The MIK sampling clearly showed that the highest abundances of all three Thysanoessa spp. were in the upper layers, although there was a tendency for the larger-sized euphausiids to occur deeper. Consistent patterns for the vertical distributions of the large zooplankters (e.g. ctenophores, euphausiids) collected by the MPS and MIK samplers provided more complete data on their abundances and sizes than obtained by the single net. Possible mechanisms contributing to the observed patterns of distribution, e.g. high abundances of both Calanus spp. and their predators (ctenophores and chaetognaths) in the upper water layers during midwinter are discussed.

Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 m spatial resolution across Switzerland. Our results reveal strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 ∘ C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 ∘ C, respectively. We also found that, in open grasslands, maximum temperatures at 5 cm above ground are, on average, 3.4 ∘ C warmer than those of the macroclimate, suggesting that, in such habitats, heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed-effect models with input from detailed radiation estimates from radiative transfer models that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography, and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by root mean squared errors ranging from 1.18 to 3.43 ∘ C, with minimum temperatures being predicted more accurately overall than maximum temperatures. The microclimate-mapping methodology presented here enables a biologically relevant perspective when analysing climate–species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change. [ABSTRACT FROM AUTHOR]

Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Recently, snow routines in hydrological and land surface models were improved to incorporate more accurate representations of forest snow processes, but model intercomparison projects have identified deficiencies, partly due to incomplete knowledge of the processes controlling snow cover in forests. The Snow Under Forest (SnoUF) project was initiated to enhance knowledge of the complex interactions between snow and vegetation. Two field campaigns, during the winters 2016–2017 and 2017–2018, were conducted in a coniferous forest bordering the snow study at Col de Porte (1325 m a.s.l., French Alps) to document the snow accumulation and ablation processes. This paper presents the field site, the instrumentation and the collection and postprocessing methods. The observations include distributed forest characteristics (tree inventory, lidar measurements of forest structure, subcanopy hemispherical photographs), meteorology (automatic weather station and an array of radiometers), snow cover and depth (snow pole transect and laser scan) and snow interception by the canopy during precipitation events. The weather station installed under dense canopy during the first campaign has been maintained since then and has provided continuous measurements throughout the year since 2018. Data are publicly available from the repository of the Observatoire des Sciences de l'Univers de Grenoble (OSUG) data center at 10.17178/SNOUF.2022 (Sicart et al., 2022). [ABSTRACT FROM AUTHOR]

Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 meter spatial resolution across Switzerland. Our data reveals strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 °C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 °C. We also found that in open grasslands, maximum temperatures at 5 cm above ground are on average 3.4 °C warmer than that of macroclimate, suggesting that in such habitats heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed effects models with input from detailed radiation estimates that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by RSME's ranging from 1.18 to 3.43 °C, with minimum temperatures generally being predicted more accurately than maximum temperatures. The microclimate mapping methodology presented here enables a more biologically relevant perspective when analysing climate-species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change. [ABSTRACT FROM AUTHOR]

In mountain regions, forests that overlap with seasonal snow mostly reside in complex terrain. Due to persisting major observational challenges in these environments, the combined impact of forest structure and topography on seasonal snow cover dynamics is still poorly understood. Recent advances in forest snow process representation and increasing availability of detailed canopy structure datasets, however, now allow for hyper-resolution (<5 m) snow model simulations capable of resolving tree-scale processes. These can shed light on the complex process interactions that govern forest snow dynamics. We present multi-year simulations at 2 m resolution obtained with FSM2, a mass- and energy-balance-based forest snow model specifically developed and validated for metre-scale applications. We simulate an ∼3 km 2 model domain encompassing forested slopes of a sub-alpine valley in the eastern Swiss Alps and six snow seasons. Simulations thus span a wide range of canopy structures, terrain characteristics, and meteorological conditions. We analyse spatial and temporal variations in forest snow energy balance partitioning, aiming to quantify and understand the contribution of individual energy exchange processes at different locations and times. Our results suggest that snow cover evolution is equally affected by canopy structure, terrain characteristics, and meteorological conditions. We show that the interaction of these three factors can lead to snow accumulation and ablation patterns that vary between years. We further identify higher snow distribution variability and complexity in slopes that receive solar radiation early in winter. Our process-level insights corroborate and complement existing empirical findings that are largely based on snow distribution datasets only. Hyper-resolution simulations as presented here thus help to better understand how snowpacks and ecohydrological regimes in sub-alpine regions may evolve due to forest disturbances and a warming climate. They could further support the development of process-based sub-grid forest snow cover parameterizations or tiling approaches for coarse-resolution modelling applications. [ABSTRACT FROM AUTHOR]

Forests strongly modify the accumulation, metamorphism and melting of snow in mid and high-latitude regions. 17 Recently, snow routines in hydrological and land surface models have been improved to incorporate more accurate 18 representations of forest snow processes, but model inter-comparison projects have identified deficiencies, partly due to incomplete knowledge of the processes controlling snow cover in forests. The Snow Under Forest (SnoUF) project was initiated to enhance knowledge of the complex interactions between snow and vegetation. Two field campaigns, during the winters 2016-17 and 2017-18, were conducted in a coniferous forest bordering the snow study at Col de Porte (1325 m a.s.l, French Alps) to document the snow accumulation and ablation processes. This paper presents the field site, instrumentation, and collection methods. The observations include distributed forest characteristics (tree inventory, LIDAR measurements of forest structure, sub-canopy hemispherical photographs), meteorology (automatic weather station and radiometers array), snow cover and depth (snow poles transect and laser scan), and snow interception by the canopy during precipitation events. The weather station installed under dense canopy during the first campaign has been maintained since then and provides continuous measurements throughout the year since 2018. Data are publicly available from the repository of the Observatoire des Sciences de l'Univers de Grenoble (OSUG) data center at http://dx.doi.org/10.17178/SNOUF.2022 (Sicart et al., 2022). [ABSTRACT FROM AUTHOR]

In mountain regions, forests that overlap with seasonal snow mostly reside in complex terrain. Due to persisting major observational challenges in these environments, the combined impact of forest structure and topography on seasonal snow cover dynamics is still poorly understood. Recent advances in forest snow process representation and increasing availability of detailed canopy structure datasets, however, now allow for hyper-resolution (<5 m) snow model simulations capable of resolving tree-scale processes, which can shed light on the complex process interactions that govern forest snow dynamics. We present multi-year simulations at 2 m resolution obtained with FSM2, a mass- and energy-balance based forest snow model specifically developed and validated for meter-scale applications. We simulate a ~ 3 km² model domain encompassing forested slopes of a sub-alpine valley in the Eastern Swiss Alps and six snow seasons. Simulations thus span a wide range of canopy structures, terrain characteristics, and meteorological conditions. We analyse spatial and temporal variations in forest snow energy balance partitioning, aiming to quantify and understand the contribution of individual energy exchange processes at different locations and times. Our results suggest that snow cover evolution is equally affected by canopy structure, terrain characteristics and meteorological conditions. We show that the interaction of these three factors can lead to snow distribution and melt patterns that vary between years. We further identify higher snow distribution variability and complexity in slopes that receive solar radiation early in winter. Our process-level insights corroborate and complement existing empirical findings that are largely based on snow distribution datasets only. Hyper-resolution simulations as presented here thus help to better understand how snowpacks and ecohydrological regimes in sub-alpine regions may evolve as a result of forest disturbances and a warming climate. They could further support the development of process-based sub-grid forest snow cover parametrizations or tiling approaches for coarse-resolution modelling applications. [ABSTRACT FROM AUTHOR]

Aim: Pleistocene erratic boulders are rocks that were relocated by glaciers during the Ice Ages. When their geology differs from the geology of the landscape that surrounds them, erratic boulders form habitat islands for regionally rare, edaphically specialised, rock‐dwelling cryptogams (bryophytes, ferns and lichens). Such boulders constitute terrestrial model systems for exploring island biogeographic predictions and the effect of environmental variables on species diversity and community composition, which we studied in order to provide basic knowledge of the ecology, with relevance for the conservation, of these unusual island systems. Location: Siliceous erratic boulders in the calcareous Swiss Plateau and Jura Mountains. Methods: For 160 erratic boulders we recorded all bryophyte species and a diverse set of environmental variables. For all species and for specialist species (acidophile rock‐dwellers) separately, we analysed species–area relationships and nestedness, and explored relationships between environmental variables, species diversity and community composition. Results: We found 138 bryophyte species, 19 of which were specialists of erratic boulders. A steeper species–area curve for boulder specialists than for total species richness underlined the island properties of boulders for specialist species. Large boulders were more likely to harbour numerous boulder specialists and communities on small boulders were nested within the communities present on large boulders. However, at the landscape level small boulders contributed more specialist species than a few large boulders of the same surface area. Erratic boulders near settlements were less likely to harbour boulder specialists. Boulders in open land harboured different and more specialist species than boulders in forests. Conclusions: Large undisturbed erratic boulders in open land harbour rare bryophyte communities with a large number of specialist species. Conservation should thus prioritise this type of boulders. Furthermore, conserving large boulders is logistically easier, and they may function as flagships for small boulders that also contribute to the biodiversity within landscapes. [ABSTRACT FROM AUTHOR]

Land Surface Albedo (LSA) of forested environments continues to be a source of uncertainty in land surface modeling, especially across seasonally snow covered domains. Assessment and improvement of global scale model performance has been hampered by the contrasting spatial scales of model resolution and in‐situ LSA measurements. In this study, point‐scale simulations of the Community Land Model 5.0 (CLM5) were evaluated across a large range of forest structures and solar angles at two climatically different locations. LSA measurements, using an uncrewed aerial vehicle with up and down‐looking shortwave radiation sensors, showed canopy structural shading of the snow surface exerted a primary control on LSA. Diurnal patterns of measured LSA revealed strong effects of both azimuth and zenith angles, neither of which were adequately represented in simulations. In sparse forest environments, LSA were overestimated by up to 66%. Further analysis revealed a lack of correlation between Plant Area Index (PAI), the primary canopy descriptor in CLM5, and measured LSA. Instead, measured LSA showed considerable correlation with the fraction of snow visible in the sensor's field of view, a correlation which increased further when only considering the sunlit fraction of visible snow. The use of effective PAI values as a simple first‐order correction for the discrepancy between measured and simulated LSA in sparse forest environments substantially improved model results (64%–76% RMSE reduction). However, the large biases suggest the need for a more generic solution, for example, by introducing a canopy metric that represents canopy gap fraction rather than assuming a spatially homogeneous canopy. Key Points: Shading by trees was shown to exert a key control on Land Surface Albedo (LSA) across seasonally snow covered domainsDiurnal patterns of measured LSA revealed strong effects of azimuth and zenith angles, neither of which were represented in Community Land Model 5.0 (CLM5) simulationsIn sparse forests, CLM5 overestimated LSA by up to 66%; the use of effective Plant Area Index values reduced this bias substantially [ABSTRACT FROM AUTHOR]

Processes shaping forest snow cover evolution often vary at small spatial scales, which are not resolved by most model applications. Representing this variability at larger scales and coarser model resolutions constitutes a major challenge for model developers. In this study, we use a well‐validated hyper‐resolution forest snow model that explicitly resolves the spatial variability of canopy‐snow interactions at the meter scale to explore adequate representation of forest‐snow processes at coarser resolutions (50 m). For this purpose, we assess coarser‐resolution runs against spatially averaged results from corresponding hyper‐resolution simulations over a 150,000 m2 model domain. For the coarser‐resolution simulations, we tested alternative upscaling strategies. Our results reveal considerable discrepancies between strategies that utilize generalized canopy metrics versus strategies that apply a more detailed set of process‐specific canopy descriptors. Particularly, the inclusion of canopy descriptors that represent the various scales and perspectives relevant to the individual processes leads to accurate simulation of forest snow cover dynamics at coarse resolutions. Our results further demonstrate that a realistic representation of snow‐covered fraction in snowmelt calculations is important even for relatively small (∼50 m) grid cells. Ultimately, this work provides recommendations for modeling forest‐snow processes in large‐scale applications, which allow coarse resolution simulations to approximate spatially averaged results of corresponding hyper‐resolution simulations. Key Points: Upscaling experiments with a well‐validated hyper‐resolution forest snow model allowed assessing process representation at coarse resolutionProcess‐specific canopy metrics and detailed representation of shortwave radiation transfer improved coarse‐resolution simulationsAccounting for fractional snow‐covered area is critical to simulating accurate melt rates even for relatively small grid cells [ABSTRACT FROM AUTHOR]

The complex dynamics of snow accumulation and melt processes under forest canopies entail major observational and modeling challenges, as they vary strongly in space and time. In this study, we present novel data sets acquired with mobile multisensor platforms in subalpine and boreal forest stands. These data sets include spatially and temporally resolved measurements of shortwave and longwave irradiance, air and snow surface temperatures, wind speed, and snow depth, all coregistered to canopy structure information. We then apply the energy balance snow model FSM2 to obtain concurrent, distributed simulations of the forest snowpack at very high (“hyper”) resolution (2 m). Our data sets allow us to assess the performance of alternative canopy representation strategies within FSM2 at the level of individual snow energy balance components and in a spatially explicit manner. We demonstrate the benefit of accounting for detailed spatial patterns of shortwave and longwave radiation transfer through the canopy and show the importance of describing wind attenuation by the canopy using stand‐scale metrics. With the proposed canopy representation, snowmelt dynamics in discontinuous forest stands were successfully reproduced. Hyper‐resolution simulations resolving these effects provide an optimal basis for assessing the snow‐hydrological impacts of forest disturbances and for validating and improving the representation of forest snow processes in land surface models intended for coarser‐scale applications. [ABSTRACT FROM AUTHOR]

Uncooled thermal infrared (TIR) imagers, commonly used on aircraft and small unmanned aircraft systems (UAS, "drones"), can provide high‐resolution surface temperature maps, but their accuracy is dependent on reliable calibration sources. A novel method for correcting surface temperature observations made by uncooled TIR imagers uses observations over melting snow, which provides a constant 0 °C reference temperature. This bias correction method is applied to remotely sensed surface temperature observations of forests and snow over two mountain study sites: Laret, Davos, Switzerland (27 March 2017) in the Alps, and Sagehen Creek, California, USA (21 April 2017) in the Sierra Nevada. Surface temperature retrieval errors that arise from temperature‐induced instrument bias, differences in image resolution, retrieval of mixed pixels, and variable view angles were evaluated for these forest snow scenes. Applying the melting snow‐based bias correction decreased the root‐mean‐square error by about 1 °C for retrieving snow, water, and forest canopy temperatures from airborne TIR observations. The influence of mixed pixels on surface temperature retrievals over forest snow scenes was found to depend on image resolution and the spatial distribution of forest stands. Airborne observations over the forests at Sagehen showed that near the edges of TIR images, at more than 20° from nadir, the snow surface within forest gaps smaller than 10 m was obscured by the surrounding trees. These off‐nadir views, with fewer mixed pixels, could allow more accurate airborne and satellite‐based observations of canopy surface temperatures. Key Points: Thermal infrared camera bias was reduced by using the surface temperature of melting snow as a reference targetRetrieval of the surface temperature variability of forests and snow was found to depend on the spatial distribution of forest standsOff‐nadir observations over forests hindered snow surface temperature retrievals, but enabled improved canopy temperature measurements [ABSTRACT FROM AUTHOR]

A comprehensive analysis of canopy surface temperatures was conducted around a small and large gap at a forested alpine site in the Swiss Alps during the 2015 and 2016 snowmelt seasons (March-April). Canopy surface temperatures within the small gap were within 2-3°C of measured reference air temperature. Vertical and horizontal variations in canopy surface temperatures were greatest around the large gap, varying up to 18°C above measured reference air temperature during clear-sky days. Nighttime canopy surface temperatures around the study site were up to 3°C cooler than reference air temperature. These measurements were used to develop a simple parameterization for correcting reference air temperature for elevated canopy surface temperatures during (1) nighttime conditions (subcanopy shortwave radiation is 0 W m−2) and (2) periods of increased subcanopy shortwave radiation >400 W m−2 representing penetration of shortwave radiation through the canopy. Subcanopy shortwave and longwave radiation collected at a single point in the subcanopy over a 24 h clear-sky period was used to calculate a nighttime bulk offset of 3°C for scenario 1 and develop a multiple linear regression model for scenario 2 using reference air temperature and subcanopy shortwave radiation to predict canopy surface temperature with a root-mean-square error (RMSE) of 0.7°C. Outside of these two scenarios, reference air temperature was used to predict subcanopy incoming longwave radiation. Modeling at 20 radiometer locations throughout two snowmelt seasons using these parameterizations reduced the mean bias and RMSE to below 10 W m s−2 at all locations. [ABSTRACT FROM AUTHOR]

Tailored messages are those that specifically target individuals following an assessment of their unique characteristics. This systematic review assesses the evidence regarding the effectiveness of tailoring within eHealth interventions aimed at chronic disease management. OVID Medline/Embase databases were searched for randomised control trials, controlled clinical, trials, before -after studies, and time series analyses from inception - May 2014. Objectively measured clinical processes/outcomes were considered. Twenty-two papers were eligible for inclusion: 6/22 used fully tailored messaging and 16/22 used partially tailored messages. Two studies isolated tailoring as the active component. The remainder compared intervention with standard care. In all, 12/16 studies measuring clinical processes and 2/6 studies reporting clinical outcomes showed improvements, regardless of target group. Study quality was low and design did not allow for identification of interventions’ active component. Heterogeneity precluded meta-analysis. This review has demonstrated that there is a lack of evidence to suggest that tailoring within an eHealth context confers benefit over non-tailored eHealth interventions. [ABSTRACT FROM AUTHOR]

ABSTRACT Hydro-electricity is a critical resource in New Zealand, and as such improved understanding of the drivers of water resource availability is a key research goal. Large-scale atmospheric circulation is the principal driver of surface climate and water resource variability over New Zealand. Focusing on the Waitaki River (located in the South Island; one of the most important rivers for hydro-electricity in New Zealand), a comprehensive analysis is presented of the large-scale atmospheric circulation drivers of monthly inflow to the three main headwater lakes, Ohau, Pukaki and Tekapo. Analyses are undertaken using composite, correlation, partial least-squares ( PLS) regression and cross-wavelet analyses. Environment-to-climate composite analysis indicates that variation in lake inflow is driven primarily by the strength of the NE-SW pressure gradient over the three lakes (i.e. parallel to the axis of the Southern Alps, from which the lakes are fed). Relatively strong winds from a north-westerly direction are associated with high lake inflow; weaker winds from a more south-westerly direction occur during times of low inflow. Climate-to-environment composites of lake inflow, together with correlation, PLS and wavelet analysis, indicate that inflow is described well by the MZ1 and MZ2 New Zealand-based circulation indices, but not larger-scale modes of atmospheric circulation. The MZ1 and MZ2 indices have rarely been considered previously as explanatory variables for water resources in the South Island of New Zealand, but here it is suggested that these indices represent a promising new direction for future studies, particularly relating to season-ahead prediction of water resource availability. [ABSTRACT FROM AUTHOR]

Zooplankton often migrate vertically to deeper dark water during the day to avoid visual predators such as fish, a process which can strengthen benthic-pelagic coupling. In the Gulf of Finland, Baltic Sea, a pronounced hypoxic layer develops when there is an inflow of anoxic bottom water from the Central Baltic Sea, which could be a barrier for vertical migrants. Here, we report an acoustic study of the distributions of crustacean zooplankton (mysid shrimp and the copepod Limnocalanus macrurus), gelatinous zooplankton ( Aurelia aurita) and fish. Zooplankton trawl nets were used to ground-truth acoustic data. Vertical profiles of oxygen concentration were taken, and the physiological impact of hypoxia on mysids was investigated using biochemical assays. We hypothesised that the vertical distribution of zooplankton and fish would be significantly affected by vertical heterogeneity of oxygen concentrations because anoxia and hypoxia are known to affect physiology and swimming behaviour. In addition, we hypothesised that mysids present in areas with hypoxia would exhibit a preparatory antioxidant response, protecting them from oxidative damage during migrations. The acoustic data showed peaks of crustacean zooplankton biomass in hypoxic (<2 mL L) and low oxygen (2-4 mL L) concentrations (depth >75 m), whereas fish shoals and A. aurita medusae were found in normoxic (5-6 mL L) upper water layers (<40 m), with individual fish in deeper water excepting that rule. Mysid shrimp from areas with hypoxia had significantly enhanced antioxidant potential compared with conspecifics from areas with no hypoxia and had no significant indications of oxidative damage. We conclude that mysids can protect themselves from oxidative damage, enabling them to inhabit hypoxic water. Our data suggest that hypoxic and low oxygen zones (up to 4 mL L) may provide some zooplankton species with a refuge from visual predators such as fish. [ABSTRACT FROM AUTHOR]

Seasonal snow is a globally important water resource that contributes substantially to upland and lowland water resources. As such, there is a need to understand the controls on the spatial and temporal variation in snow distribution. This study meets this research need by investigating the topographic controls on snow depth distribution in the upper Jollie catchment in the Southern Alps of New Zealand. Furthermore, inter-annual variation in the importance of the topographic controls is examined and linked to variation in the dominant synoptic-scale weather patterns over a 4-year period (2007-2010). Through the use of regression trees, the relative importance of the topographic controls on snow depth was shown to vary between the four study years. In particular, elevation explained the greatest amount of variance in 2007 and 2008 and east-exposure explained the greatest variance in 2009 and 2010. The other wind exposure variables also had a large effect on the snow depth distribution in 2009 and 2010. Differences in the frequency and duration of synoptic weather patterns were physically consistent with the changing importance of these variables. In particular, a higher frequency of troughing events in 2009 and 2010 is thought to be associated with a reduced importance of elevation and greater influence of wind exposure on snow depth in these years. These findings demonstrate the importance of using multi-year data sets, and of considering topographic and climatic influences, when attempting to model alpine snow distribution. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]