Optimal dynamic control of invasions: applying a systematic conservation approach

The social, economic, and environmental impacts of invasive plants are well recognized. However, these variable impacts are rarely accounted for in the spatial prioritization of funding for weed management. We examine how current spatially explicit prioritization methods can be extended to identify optimal budget allocations to both eradication and control measures of invasive species to minimize the costs and likelihood of invasion. Our framework extends recent approaches to systematic prioritization of weed management to account for multiple values that are threatened by weed invasions with a multi-year dynamic prioritization approach. We apply our method to the northern portion of the Daly catchment in the Northern Territory, which has significant conservation values that are threatened by gamba grass (Andropogon gayanus), a highly invasive species recognized by the Australian government as a Weed of National Significance (WONS). We interface Marxan, a widely applied conservation planning tool, with a dynamic biophysical model of gamba grass to optimally allocate funds to eradication and control programs under two budget scenarios comparing maximizing gain (MaxGain) and minimizing loss (MinLoss) optimization approaches. The prioritizations support previous findings that a MinLoss approach is a better strategy when threats are more spatially variable than conservation values. Over a 10-year simulation period, we find that a MinLoss approach reduces future infestations by ~8% compared to MaxGain in the constrained budget scenarios and ~12% in the unlimited budget scenarios. We find that due to the extensive current invasion and rapid rate of spread, allocating the annual budget to control efforts is more efficient than funding eradication efforts when there is a constrained budget. Under a constrained budget, applying the most efficient optimization scenario (control, minloss) reduces spread by ~27% compared to no control. Conversely, if the budget is unlimited it is more efficient to fund eradication efforts and reduces spread by ~65% compared to no control

Resource-use efficiency explains grassy weed invasion in a low-resource savanna in north Australia

Comparative studies of plant resource use and ecophysiological traits of invasive and native resident plant species can elucidate mechanisms of invasion success and ecosystem impacts. In the seasonal tropics of north Australia, the alien C4 perennial grass Andropogon gayanus (gamba grass) has transformed diverse, mixed tree-grass savanna ecosystems into dense monocultures. To better understand the mechanisms of invasion, we compared resource acquisition and usage efficiency using leaf-scale ecophysiological and stand-scale growth traits of A. gayanus with a co-habiting native C4 perennial grass Alloteropsis semialata. Under wet season conditions, A. gayanus had higher rates of stomatal conductance, assimilation, and water use, plus a longer daily assimilation period than the native species A. semialata. Growing season length was also ~2 months longer for the invader. Wet season measures of leaf scale water use efficiency (WUE) and light use efficiency (LUE) did not differ between the two species, although photosynthetic nitrogen use efficiency (PNUE) was significantly higher in A. gayanus. By May (dry season) the drought avoiding native species A. semialata had senesced. In contrast, rates of A. gayanus gas exchange was maintained into the dry season, albeit at lower rates that the wet season, but at higher WUE and PNUE, evidence of significant physiological plasticity. High PNUE and leaf 15N isotope values suggested that A. gayanus was also capable of preferential uptake of soil ammonium, with utilization occurring into the dry season. High PNUE and fire tolerance in an N-limited and highly flammable ecosystem confers a significant competitive advantage over native grass species and a broader niche width. As a result A. gayanus is rapidly spreading across north Australia with significant consequences for biodiversity and carbon and retention

Invasive Andropogon gayanus (gamba grass) is an ecosystem transformer of nitrogen relations in Australian savanna

The African grass Andropogon gayanus Kunth. is invading Australian savannas, altering their ecological and biogeochemical function. To assess impacts on nitrogen (N) cycling, we quantified litter decomposition and N dynamics of grass litter in native grass and A. gayanus invaded savanna using destructive in situ grass litter harvests and litterbag incubations (soil surface and aerial position). Only 30% of the A. gayanus in situ litter decomposed, compared to 61% of the native grass litter, due to the former being largely comprised of highly resistant A. gayanus stem. In contrast to the stem, A. gayanus leaf decomposition was approximately 3- and 2-times higher than the dominant native grass, Alloteropsis semilata at the surface and aerial position, respectively. Lower initial lignin concentrations, and higher consumption by termites, accounted for the greater surface decomposition rate of A. gayanus. N flux estimates suggest the N release of A. gayanus litter is insufficient to compensate for increased N uptake and N loss via fire in invaded plots. Annually burnt invaded savanna may lose up to 8.2% of the upper soil N pool over a decade. Without additional inputs via biological N fixation, A. gayanus invasion is likely to diminish the N capital of Australia's frequently burnt savannas

Optimal stomatal behaviour around the world

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordStomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.This research was supported by the Australian Research Council (ARC MIA Discovery Project 1433500-2012-14). A.R. was financially supported in part by The Next-Generation Ecosystem Experiments (NGEE-Arctic) project, which is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science, and through the United States Department of Energy contract No. DE-AC02-98CH10886 to Brookhaven National Laboratory. M.O.d.B. acknowledges that the Brassica data were obtained within a research project financed by the Belgian Science Policy (OFFQ, contract number SD/AF/02) and coordinated by K. Vandermeiren at the Open-Top Chamber research facilities of CODA-CERVA (Tervuren, Belgium)

Some Cytological Observations on Peripheral Myelinated Nerve Fibers as Observed by the Polarized Light Method

Author Institution: Department of Anatomy, The Ohio State Universit

Optimal stomatal behaviour around the world

© 2015 Macmillan Publishers Limited. All rights reserved. Stomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate