An improved technique for estimating short-term survival of released line-caught fish, and an application comparing barotrauma-relief methods in red emperor (Lutjanus sebae Cuvier 1816).

Promotion of better procedures for releasing undersize fish, advocacy of catch-and-release angling, and changing minimum legal sizes are increasingly being used as tools for sustainable management of fish stocks. However without knowing the proportion of released fish that survive, the conservation value of any of these measures is uncertain. We developed a floating vertical enclosure to estimate short-term survival of released line-caught tropical and subtropical reef-associated species, and used it to compare the effectiveness of two barotrauma-relief procedures (venting and shotline releasing) on red emperor (Lutjanus sebae). Barotrauma signs varied with capture depth, but not with the size of the fish. Fish from the greatest depths (40-52 m) exhibited extreme signs less frequently than did those from intermediate depths (30-40 m), possibly as a result of swim bladder gas being vented externally through a rupture in the body wall. All but two fish survived the experiment, and as neither release technique significantly improved short-term survival of the red emperor over non-treatment we see little benefit in promoting either venting or shotline releasing for this comparatively resilient species. Floating vertical enclosures can improve short-term post-release mortality estimates as they overcome many problems encountered when constraining fish in submerged cages.

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.

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.

Comparing fixed and flexible stocking as adaptations to inter-annual rainfall variability in the extensive beef industry of northern Australia

Many beef producers within the extensive cattle industry of northern Australia attempt to maintain a constant herd size from year-to-year (fixed stocking), whereas others adjust stock numbers to varying degrees annually in response to changes in forage supply. The effects of these strategies on pasture condition and cattle productivity cannot easily be assessed by grazing trials. Simulation studies, which include feedbacks of changes to pasture condition on cattle liveweight gain, can extend the results of grazing trials both spatially and temporally. They can compare a large number of strategies, over long periods of time, for a range of climate periods, at locations which differ markedly in climate. This simulation study compared the pasture condition and cattle productivity achieved by fixed stocking at the long-term carrying capacity with that of 55 flexible stocking strategies at 28 locations across Queensland and the Northern Territory. Flexible stocking strategies differed markedly in the degree they increased or decreased cattle stocking rates after good and poor pasture growing seasons, respectively. The 28 locations covered the full range in average annual rainfall and inter-annual rainfall variability experienced across northern Australia. Constrained flexibility, which limited increases in stocking rates after good growing seasons to 10% but decreased them by up to 20% after poor growing seasons, provides sustainable productivity gains for cattle producers in northern Australia. This strategy can improve pasture condition and increase cattle productivity relative to fixed stocking at the long-term carrying capacity, and its capacity to do this was greatest in the semiarid rangeland regions that contain the majority of beef cattle in northern Australia. More flexible stocking strategies, which also increased stocking rates after good growing seasons by only half as much as they decreased them after poor growing seasons, were equally sustainable and more productive than constrained flexibility, but are often impractical at property and industry scales. Strategies with the highest limits (e.g. 70%) for both annual increases and decreases in stocking rates could achieve higher cattle productivity, but this was at the expense of pasture condition and was not sustainable. Constrained flexible stocking, with a 10% limit for increases and a 20% limit for decreases in stocking rates annually, is a risk-averse adaptation to high and unpredictable rainfall variability for the extensive beef industry of northern Australia. © Australian Rangeland Society 2016.