Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.

High frequency fire alters C:N:P stoichiometry in forest litter

Fire is a major driver of ecosystem change and can disproportionately affect the cycling of different nutrients. Thus, a stoichiometric approach to investigate the relationships between nutrient availability and microbial resource use during decomposition is likely to provide insight into the effects of fire on ecosystem functioning. We conducted a field litter bag experiment to investigate the long-term impact of repeated fire on the stoichiometry of leaf litter C, N and P pools, and nutrient-acquiring enzyme activities during decomposition in a wet sclerophyll eucalypt forest in Queensland, Australia. Fire frequency treatments have been maintained since 1972, including burning every two years (2yrB), burning every four years (4yrB) and no burning (NB). C:N ratios in freshly fallen litter were 29-42% higher and C:P ratios were 6-25% lower for 2yrB than NB during decomposition, with correspondingly lower 2yrB N:P ratios (27-32) than for NB (34-49). Trends in litter soluble and microbial N:P ratios were similar to the overall litter N:P ratios across fire treatments. Consistent with these, the ratio of activities for N-acquiring to P-acquiring enzymes in litter was higher for 2yrB than NB while 4yrB was generally intermediate between 2yrB and NB. Decomposition rates of freshly fallen litter were significantly lower for 2yrB (72±2% mass remaining at the end of experiment) than for 4yrB (59±3%) and NB (62±3%), a difference that may be related to effects of N limitation, lower moisture content, and/or litter C quality. Results for older mixed-age litter were similar to those for freshly fallen litter although treatment differences were less pronounced. Overall, these findings show that frequent fire (2yrB) decoupled N and P cycling, as manifested in litter C:N:P stoichiometry and in microbial biomass N:P ratio and enzymatic activities. These data indicate that fire induced a transient shift to N-limited ecosystem conditions during the post-fire recovery phase. This article is protected by copyright. All rights reserved.

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.