Carbon sequestration potential of plantation forests in New Zealand - no single tree species is universally best.

BACKGROUND: Plantation forests are a nature-based solution to sequester atmospheric carbon and, therefore, mitigate anthropogenic climate change. The choice of tree species for afforestation is subject to debate within New Zealand. Two key issues are whether to use (1) exotic plantation species versus indigenous forest species and (2) fast growing short-rotation species versus slower growing species. In addition, there is a lack of scientific knowledge about the carbon sequestration capabilities of different plantation tree species, which hinders the choice of species for optimal carbon sequestration. We contribute to this discussion by simulating carbon sequestration of five plantation forest species, Pinus radiata, Pseudotsuga menziesii, Eucalyptus fastigata, Sequoia sempervirens and Podocarpus totara, across three sites and two silvicultural regimes by using the 3-PG an ecophysiological model. RESULTS: The model simulations showed that carbon sequestration potential varies among the species, sites and silvicultural regimes. Indigenous Podocarpus totara or exotic Sequoia sempervirens can provide plausible options for long-term carbon sequestration. In contrast, short term rapid carbon sequestration can be obtained by planting exotic Pinus radiata, Pseudotsuga menziesii and Eucalyptus fastigata. CONCLUSION: No single species was universally better at sequestering carbon on all sites we tested. In general, the results of this study suggest a robust framework for ranking and testing candidate afforestation species with regard to carbon sequestration potential at a given site. Hence, this study could help towards more efficient decision-making for carbon forestry.

Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach.

The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study, we have focused on understanding the association of COVID-19 cases with environmental and socioeconomic factors in Zambia - a sub-Saharan African country. We used Zambia's district-level COVID-19 data, covering 18 March 2020 (i.e., from first reported cases) to 17 July 2020. Geospatial approaches were used to organize, extract and establish the dataset, while a classification tree (CT) technique was employed to analyze the factors associated with the COVID-19 cases. The analyses were conducted in two stages: (1) the binary analysis of occurrences of COVID-19 (i.e., COVID-19 or No COVID-19), and (2) a risk level analysis which grouped the number of cases into four risk levels (high, moderate, low and very low). The results showed that the distribution of COVID-19 cases in Zambia was significantly influenced by the socioeconomic factors compared to environmental factors. More specifically, the binary model showed that distance to the airport, population density and distance to the town centres were the most combination influential factors, while the risk level analysis indicated that areas with high rates of human immuno-deficient virus (HIV) infection had relatively high chances of having many COVID-19 cases compared to areas with low HIV rates. The districts that are far from major urban establishments and that experience higher temperatures have lower chances of having COVID-19 cases. This study makes two major contributions towards the understanding of COVID-19 dynamics: (1) the methodology presented here can be effectively applied in other areas to understand the association of environmental and socioeconomic factors with COVID-19 cases, and (2), the findings from this study present the empirical evidence of the relationship between COVID-19 cases and their associated environmental and socioeconomic factors. Further studies are needed to understand the relationship of this disease and the associated factors in different cultural settings, seasons and age groups, especially as the COVID-19 cases increase and spread in many countries.

Diversification of forestry portfolios for climate change and market risk mitigation.

Investments in forestry are long-term and thus subject to numerous sources of risk. In addition to the volatility from markets, forestry investments are directly exposed to future impacts from climate change. We examined how diversification of forest management regimes can mitigate the expected risks associated with forestry activities in New Zealand based on an application of Modern Portfolio Theory. Uncertainties in the responses of Pinus radiata (D. Don) productivity to climate change, from 2050 to 2090, were simulated with 3-PG, a process-based forest growth model, based on future climate scenarios and Representative Concentration Pathways (RCPs). Future timber market scenarios were based on RCP-specific projections from the Global Timber Model and historical log grade prices. Outputs from 3-PG and the market scenarios were combined to compute annualized forestry returns for four P. radiata regimes for 2050-2090. This information was then used to construct optimal forestry portfolios that minimize investment risk for a given target return under different RCPs, forest productivity and market scenarios. While current P. radiata regimes in New Zealand are largely homogenous, our results suggest that regime diversification can mitigate future risks imposed by climate change and market uncertainty. Nevertheless, optimal portfolio compositions varied substantially across our range of scenarios and portfolio objectives. The application of this framework can help forest managers to better account for future risks in their management decisions.

Circadian rhythms have significant effects on leaf-to-canopy scale gas exchange under field conditions.

BACKGROUND: Molecular clocks drive oscillations in leaf photosynthesis, stomatal conductance, and other cell and leaf-level processes over ~24 h under controlled laboratory conditions. The influence of such circadian regulation over whole-canopy fluxes remains uncertain; diurnal CO2 and H2O vapor flux dynamics in the field are currently interpreted as resulting almost exclusively from direct physiological responses to variations in light, temperature and other environmental factors. We tested whether circadian regulation would affect plant and canopy gas exchange at the Montpellier European Ecotron. Canopy and leaf-level fluxes were constantly monitored under field-like environmental conditions, and under constant environmental conditions (no variation in temperature, radiation, or other environmental cues). RESULTS: We show direct experimental evidence at canopy scales of the circadian regulation of daytime gas exchange: 20-79 % of the daily variation range in CO2 and H2O fluxes occurred under circadian entrainment in canopies of an annual herb (bean) and of a perennial shrub (cotton). We also observed that considering circadian regulation improved performance by 8-17 % in commonly used stomatal conductance models. CONCLUSIONS: Our results show that circadian controls affect diurnal CO2 and H2O flux patterns in entire canopies in field-like conditions, and its consideration significantly improves model performance. Circadian controls act as a 'memory' of the past conditions experienced by the plant, which synchronizes metabolism across entire plant canopies.