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.

Legumes or nitrification inhibitors to reduce N2O emissions from subtropical cereal cropping systems in Oxisols?

The DAYCENT biogeochemical model was used to investigate how the use of fertilizers coated with nitrification inhibitors and the introduction of legumes in the crop rotation can affect subtropical cereal production and N2O emissions. The model was validated using comprehensive multi-seasonal, high-frequency dataset from two field investigations conducted on an Oxisol, which is the most common soil type in subtropical regions. Different N fertilizer rates were tested for each N management strategy and simulated under varying weather conditions. DAYCENT was able to reliably predict soil N dynamics, seasonal N2O emissions and crop production, although some discrepancies were observed in the treatments with low or no added N inputs and in the simulation of daily N2O fluxes. Simulations highlighted that the high clay content and the relatively low C levels of the Oxisol analyzed in this study limit the chances for significant amounts of N to be lost via deep leaching or denitrification. The application of urea coated with a nitrification inhibitor was the most effective strategy to minimize N2O emissions. This strategy however did not increase yields since the nitrification inhibitor did not substantially decrease overall N losses compared to conventional urea. Simulations indicated that replacing part of crop N requirements with N mineralized by legume residues is the most effective strategy to reduce N2O emissions and support cereal productivity. The results of this study show that legumes have significant potential to enhance the sustainable and profitable intensification of subtropical cereal cropping systems in Oxisols.

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.

Does manure management affect the latent greenhouse gas emitting potential of livestock manures?

With livestock manures being increasingly sought as alternatives to costly synthetic fertilisers, it is imperative that we understand and manage their associated greenhouse gas (GHG) emissions. Here we provide the first dedicated assessment into how the GHG emitting potential of various manures responds to the different stages of the manure management continuum (e.g., from feed pen surface vs stockpiled). The research is important from the perspective of manure application to agricultural soils. Manures studied included: manure from beef feedpen surfaces and stockpiles; poultry broiler litter (8-week batch); fresh and composted egg layer litter; and fresh and composted piggery litter. Gases assessed were methane (CH4) and nitrous oxide (N2O), the two principal agricultural GHGs. We employed proven protocols to determine the manures’ ultimate CH4 producing potential. We also devised a novel incubation experiment to elucidate their N2O emitting potential; a measure for which no established methods exist. We found lower CH4 potentials in manures from later stages in their management sequence compared with earlier stages, but only by a factor of 0.65×. Moreover, for the beef manures this decrease was not significant (P < 0.05). Nitrous oxide emission potential was significantly positively (P < 0.05) correlated with C/N ratios yet showed no obvious relationship with manure management stage. Indeed, N2O emissions from the composted egg manure were considerably (13×) and significantly (P < 0.05) higher than that of the fresh egg manure. Our study demonstrates that manures from all stages of the manure management continuum potentially entail significant GHG risk when applied to arable landscapes. Efforts to harness manure resources need to account for this.

Soybean rotation and crop residue management to reduce nitrous oxide emissions from sugarcane soils

NITROUS OXIDE (N2O) IS a potent greenhouse gas and the predominant ozone-depleting substance in the atmosphere. Agricultural nitrogenous fertiliser use is the major source of human-induced N2O emissions. A field experiment was conducted at Bundaberg from October 2012 to September 2014 to examine the impacts of legume crop (soybean) rotation as an alternative nitrogen (N) source on N2O emissions during the fallow period and to investigate low-emission soybean residue management practices. An automatic monitoring system and manual gas sampling chambers were used to measure greenhouse gas emissions from soil. Soybean cropping during the fallow period reduced N2O emissions compared to the bare fallow. Based on the N content in the soybean crop residues, the fertiliser N application rate was reduced by about 120 kg N/ha for the subsequent sugarcane crop. Consequently, emissions of N2O during the sugarcane cropping season were significantly lower from the soybean cropped soil than those from the conventionally fertilised (145 kg N/ha) soil following bare fallow. However, tillage that incorporated the soybean crop residues into soil promoted N2O emissions in the first two months. Spraying a nitrification inhibitor (DMPP) onto the soybean crop residues before tillage effectively prevented the N2O emission spikes. Compared to conventional tillage, practising no-till with or without growing a nitrogen catch crop during the time after soybean harvest and before cane planting also reduced N2O emissions substantially. These results demonstrated that soybean rotation during the fallow period followed with N conservation management practices could offer a promising N2O mitigation strategy in sugarcane farming. Further investigation is required to provide guidance on N and water management following soybean fallow to maintain sugar productivity.

Application of sorbers to mitigate greenhouse gas emissions from land-applied pig litter

Nitrous oxide is the foremost greenhouse gas (GHG)generated by land-applied manures and chemical fertilisers (Australian Government 2013). This research project was part of the National Agricultural Manure Management Program and investigated the potential for sorbers (i.e. specific naturally-occurring minerals) to decrease GHG emissions from spent piggery litter (as well as other manures)applied to soils. The sorbers investigated in this research were vermiculite and bentonite. Both are clays with high cation exchange capacities, of approximately 100–150 cmol/kg Faure 1998). The hypothesis tested in this study was that the sorbers bind ammonium in soil solution thereby suppressing ammonia (NH3)volatilisation and in doing so, slowing the kinetics of nitrate formation and associated nitrous oxide (N2O) emissions. A series of laboratory, glasshouse and field experiments were conducted to assess the sorbers’ effectiveness. The laboratory experiments comprised 64 vessels containing manure and sorber/manure ratios ranging from 1 : 10 to 1 : 1 incorporated into a sandy Sodosol via mixing. The glasshouse trial involved 240 pots comprising manure/sorber incubations placed 5 cm below the soil surface, two soil types (sandy Sodosol and Ferrosol) and two different nitrogen (N) application rates (50 kg N/ha and 150 kg N/ha) with a model plant (kikuyu grass). The field trial consisted of 96, 2 m · 2 m plots on a Ferrosol site with digit grass used as a model plant. Manure/ sorber mixtures were applied in trenches (5 cm below surface) to these plots at increasing sorber levels at anNloading rate of 200 kg/ha. Gas produced in all experiments was plumbed into a purpose-built automated gas analysis (N2O, NH3, CH4, CO2) system. In the laboratory experiments, the sorbers showed strong capacity to decreaseNH3 emissions (up to 80% decrease). Ammonia emissions were close to the detection limit in all treatments in the glasshouse and field trial. In all experiments, considerable N2O decreases (>40%) were achieved by the sorbers. As an example, mean N2O emission decreases from the field trial phase of the project are shown in Fig. 1a. The decrease inGHGemissions brought about by the clays did not negatively impact agronomic performance. Both vermiculite and bentonite resulted in a significant increase in dry matter yields in the field trial (Fig. 1b). Continuing work will optimise the sorber technology for improved environmental and agronomic performance across a range of soils (Vertosol, Dermosol in addition to Ferrosol and Sodosols) and environmental parameters (moisture, temperature, porosity, pH).

Soil N availability, rather than N deposition, controls indirect N2O emissions

Ammonia volatilised and re-deposited to the landscape is an indirect N2O emission source. This study established a relationship between N2O emissions, low magnitude NH4 deposition (0–30  kg N ha − 1 ), and soil moisture content in two soils using in-vessel incubations. Emissions from the clay soil peaked ( < 0.002 g N [ g soil ] − 1 min − 1 ) from 85 to 93% WFPS (water filled pore space), increasing to a plateau as remaining mineral-N increased. Peak N2O emissions for the sandy soil were much lower ( < 5 × 10 − 5 μg N [ g soil ] − 1 min − 1 ) and occurred at about 60% WFPS, with an indistinct relationship with increasing resident mineral N due to the low rate of nitrification in that soil. Microbial community and respiration data indicated that the clay soil was dominated by denitrifiers and was more biologically active than the sandy soil. However, the clay soil also had substantial nitrifier communities even under peak emission conditions. A process-based mathematical denitrification model was well suited to the clay soil data where all mineral-N was assumed to be nitrified ( R 2 = 90 % ), providing a substrate for denitrification. This function was not well suited to the sandy soil where nitrification was much less complete. A prototype relationship representing mineral-N pool conversions (NO3− and NH4+) was proposed based on time, pool concentrations, moisture relationships, and soil rate constants (preliminary testing only). A threshold for mineral-N was observed: emission of N2O did not occur from the clay soil for mineral-N <70 mg ( kg of soil ) − 1 , suggesting that soil N availability controls indirect N2O emissions. This laboratory process investigation challenges the IPCC approach which predicts indirect emissions from atmospheric N deposition alone.

A novel and effective technology for mitigating nitrous oxide emissions from land-applied manures

Land-applied manures produce nitrous oxide (N2O), a greenhouse gas (GHG). Land application can also result in ammonia (NH3) volatilisation, leading to indirect N2O emissions. Here, we summarise a glasshouse investigation into the potential for vermiculite, a clay with a high cation exchange capacity, to decrease N2O emissions from livestock manures (beef, pig, broiler, layer), as well as urea, applied to soils. Our hypothesis is that clays adsorb ammonium, thereby suppressing NH3 volatilisation and slowing N2O emission processes. We previously demonstrated the ability of clays to decrease emissions at the laboratory scale. In this glasshouse work, manure and urea application rates varied between 50 and 150 kg nitrogen (N)/ha. Clay : manure ratios ranged from 1 : 10 to 1 : 1 (dry weight basis). In the 1-year trial, the above-mentioned N sources were incorporated with vermiculite in 1 L pots containing Sodosol and Ferrosol growing a model pasture (Pennisetum clandestinum or kikuyu grass). Gas emissions were measured periodically by placing the pots in gas-tight bags connected to real-time continuous gas analysers. The vermiculite achieved significant (P ≤ 0.05) and substantial decreases in N2O emissions across all N sources (70% on average). We are currently testing the technology at the field scale; which is showing promising emission decreases (~50%) as well as increases (~20%) in dry matter yields. This technology clearly has merit as an effective GHG mitigation strategy, with potential associated agronomic benefits, although it needs to be verified by a cost–benefit analysis.