Life in the freezer: protein metabolism in Antarctic fish

Whole-animal, in vivo protein metabolism rates have been reported in temperate and tropical, but not Antarctic fish. Growth in Antarctic species is generally slower than lower latitude species. Protein metabolism data for Antarctic invertebrates show low rates of protein synthesis and unusually high rates of protein degradation. Additionally, in Antarctic fish, increasing evidence suggests a lower frequency of successful folding of nascent proteins and reduced protein stability. This study reports the first whole-animal protein metabolism data for an Antarctic fish. Groups of Antarctic, Harpagifer antarcticus, and temperate, Lipophrys pholis, fish were acclimatized to a range of overlapping water temperatures and food consumption, whole-animal growth and protein metabolism measured. The rates of protein synthesis and growth in Antarctic, but not temperate fish, were relatively insensitive to temperature and were significantly lower in H. antarcticus at 3°C than in L. pholis. Protein degradation was independent of temperature in H. antarcticus and not significantly different to L. pholis at 3°C, while protein synthesis retention efficiency was significantly higher in L. pholis than H. antarcticus at 3°C. These results suggest Antarctic fish degrade a significantly larger proportion of synthesized protein than temperate fish, with fundamental energetic implications for growth at low temperatures.

Limits to photosynthesis: seasonal shifts in supply and demand for CO2 in Scots pine

Boreal forests undergo a strong seasonal photosynthetic cycle; however, the underlying processes remain incompletely characterized. Here, we present a novel analysis of the seasonal diffusional and biochemical limits to photosynthesis (A_net ) relative to temperature and light limitations in high-latitude mature Pinus sylvestris, including a high-resolution analysis of the seasonality of mesophyll conductance (g_m ) and its effect on the estimation of carboxylation capacity ( VCmax ). We used a custom-built gas-exchange system coupled to a carbon isotope analyser to obtain continuous measurements for the estimation of the relevant shoot gas-exchange parameters and quantified the biochemical and diffusional controls alongside the environmental controls over A_net . The seasonality of A_net was strongly dependent on VCmax and the diffusional limitations. Stomatal limitation was low in spring and autumn but increased to 31% in June. By contrast, mesophyll limitation was nearly constant (19%). We found that VCmax limited A_net in the spring, whereas daily temperatures and the gradual reduction of light availability limited A_net in the autumn, despite relatively high VCmax . We describe for the first time the role of mesophyll conductance in connection with seasonal trends in net photosynthesis of P. sylvestris, revealing a strong coordination between g_m and A_net , but not between g_m and stomatal conductance.

Direct and Indirect Effects of Environmental Limitations on White Spruce Xylem Anatomy at Treeline

Treeline ecosystems are of great scientific interest to study the effects of limiting environmental conditions on tree growth. However, tree growth is multidimensional, with complex interactions between height and radial growth. In this study, we aimed to disentangle effects of height and climate on xylem anatomy of white spruce [Picea glauca (Moench) Voss] at three treeline sites in Alaska; i.e., one warm and drought-limited, and two cold, temperature-limited. To analyze general growth differences between trees from different sites, we used data on annual ring width, diameter at breast height (DBH), and tree height. A representative subset of the samples was used to investigate xylem anatomical traits. We then used linear mixed-effects models to estimate the effects of height and climatic variables on our study traits. Our study showed that xylem anatomical traits in white spruce can be directly and indirectly controlled by environmental conditions: hydraulic-related traits seem to be mainly influenced by tree height, especially in the earlywood. Thus, they are indirectly driven by environmental conditions, through the environment's effects on tree height. Traits related to mechanical support show a direct response to environmental conditions, mainly temperature, especially in the latewood. These results highlight the importance of assessing tree growth in a multidimensional way by considering both direct and indirect effects of environmental forcing to better understand the complexity of tree growth responses to the environment.

Greening of the land surface in the world's cold regions consistent with recent warming

Global ecosystem function is highly dependent on climate and atmospheric composition, yet ecosystem responses to environmental changes remain uncertain. Cold, high-latitude ecosystems in particular have experienced rapid warming¹, with poorly understood consequences^2-4. Here, we use a satellite observed proxy for vegetation cover - the fraction of absorbed photosynthetically active radiation⁵ - to identify a decline in the temperature limitation of vegetation in global ecosystems between 1982 and 2012. We quantify the spatial functional response of maximum annual vegetation cover to temperature and show that the observed temporal decline in temperature limitation is consistent with expectations based on observed recent warming. An ensemble of Earth system models from the Coupled Model Intercomparison Project (CMIP5) mischaracterized the functional response to temperature, leading to a large overestimation of vegetation cover in cold regions. We identify a 16.4% decline in the area of vegetated land that is limited by temperature over the past three decades, and suggest an expected large decline in temperature limitation under future warming scenarios. This rapid observed and expected decline in temperature limitation highlights the need for an improved understanding of other limitations to vegetation growth in cold regions^3,4,6, such as soil characteristics, species migration, recruitment, establishment, competition, and community dynamics.

Distribution models for koalas in South Australia using citizen science-collected data

The koala (Phascolarctos cinereus) occurs in the eucalypt forests of eastern and southern Australia and is currently threatened by habitat fragmentation, climate change, sexually transmitted diseases, and low genetic variability throughout most of its range. Using data collected during the Great Koala Count (a 1-day citizen science project in the state of South Australia), we developed generalized linear mixed-effects models to predict habitat suitability across South Australia accounting for potential errors associated with the dataset. We derived spatial environmental predictors for vegetation (based on dominant species of Eucalyptus or other vegetation), topographic water features, rain, elevation, and temperature range. We also included predictors accounting for human disturbance based on transport infrastructure (sealed and unsealed roads). We generated random pseudo-absences to account for the high prevalence bias typical of citizen-collected data. We accounted for biased sampling effort along sealed and unsealed roads by including an offset for distance to transport infrastructures. The model with the highest statistical support (wAIC c ∼ 1) included all variables except rain, which was highly correlated with elevation. The same model also explained the highest deviance (61.6%), resulted in high R (2)(m) (76.4) and R (2)(c) (81.0), and had a good performance according to Cohen's κ (0.46). Cross-validation error was low (∼ 0.1). Temperature range, elevation, and rain were the best predictors of koala occurrence. Our models predict high habitat suitability in Kangaroo Island, along the Mount Lofty Ranges, and at the tips of the Eyre, Yorke and Fleurieu Peninsulas. In the highest-density region (5576 km(2)) of the Adelaide-Mount Lofty Ranges, a density-suitability relationship predicts a population of 113,704 (95% confidence interval: 27,685-199,723; average density = 5.0-35.8 km(-2)). We demonstrate the power of citizen science data for predicting species' distributions provided that the statistical approaches applied account for some uncertainties and potential biases. A future improvement to citizen science surveys to provide better data on search effort is that smartphone apps could be activated at the start of the search. The results of our models provide preliminary ranges of habitat suitability and population size for a species for which previous data have been difficult or impossible to gather otherwise.