Drone-based thermal remote sensing provides an effective new tool for monitoring the abundance of roosting fruit bats

Accurate and precise monitoring of species abundance is essential for determining population trends and responses to environmental change. However, traditional population survey methods can be unreliable and labour-intensive, which complicates the effective conservation and management of many threatened species. We developed a method of using drone-acquired thermal orthomosaics to monitor the abundance of grey-headed flying-foxes (Pteropus poliocephalus) within tree roosts, an IUCN Red Listed species of bat. We assessed the accuracy and precision of this new method and evaluated the performance of four semiautomated methods for counting flying-foxes in thermal orthomosaics, including machine learning and Computer Vision (CV) methods. We found a high concordance between the number of flying-foxes manually counted in drone-acquired thermal imagery and the true abundance of flying-foxes in single roost trees, as obtained from direct on-ground observation. This indicated that the number of flying-foxes observed in thermal imagery accurately reflected the true abundance of flying-foxes. In addition, for thermal orthomosaics of whole roost sites, the number of flying-foxes manually counted was highly repeatable between the same-day drone surveys and human counters, indicating that this method produced highly precise abundance estimates independent of the identity/experience of human counters. Finally, the number of flying-foxes manually counted in drone-acquired thermal orthomosaics was highly concordant with the counts derived from CV and machine learning-enabled classification techniques. This indicated that accurate and precise measures of colony abundance can be obtained semi-automatically, thus greatly reducing the amount of human effort involved for obtaining abundance estimates. Our method is thus valuable for reliably monitoring the abundance of individuals in flying-fox roosts and will aid in the conservation and management of this globally threatened group of flying-mammals, as well as other homeothermic arboreal-roosting species

First-principles investigation of Ag-Cu alloy surfaces in an oxidizing environment

In this paper we investigate by means of first-principles density functional theory calculations the (111) surface of the Ag-Cu alloy under varying conditions of pressure of the surrounding oxygen atmosphere and temperature. This alloy has been recently proposed as a catalyst with improved selectivity for ethylene epoxidation with respect to pure silver, the catalyst commonly used in industrial applications. Here we show that the presence of oxygen leads to copper segregation to the surface. Considering the surface free energy as a function of the surface composition, we construct the convex hull to investigate the stability of various surface structures. By including the dependence of the free surface energy on the oxygen chemical potential, we are able compute the phase diagram of the alloy as a function of temperature, pressure and surface composition. We find that, at temperature and pressure typically used in ethylene epoxidation, a number of structures can be present on the surface of the alloy, including clean Ag(111), thin layers of copper oxide and thick oxide-like structures. These results are consistent with, and help explain, recent experimental results.Comment: 10 pages, 6 figure

Upside-down fluxes Down Under: CO2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest

Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800mm and a mean annual temperature of 18°C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225gCm−2yr−1 on average, with a standard deviation of 108gCm−2yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2= 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.The Australian Education Investment Fund, Australian Terrestrial Ecosystem Research Network, Australian Research Council and Hawkesbury Institute for the Environment at Western Sydney University supported this work. We thank Jason Beringer, Helen Cleugh, Ray Leuning and Eva van Gorsel for advice and support. Senani Karunaratne provided soil classification details

Cost-effective prescribed burning solutions vary between landscapes in eastern Australia

Fire management agencies undertake a range of fire management strategies in an attempt to reduce the risk posed by future wildfires. This can include fuel treatments (prescribed burning and mechanical removal), suppression and community engagement. However, no agency has an unlimited budget and numerically optimal solutions can rarely be implemented or may not even exist. Agencies are trying to quantify the extent to which their management actions reduce risk across multiple values in the most cost-effective manner. In this paper, we examine the cost-effectiveness of a range of prescribed burning strategies across multiple landscapes in south-eastern Australia. Landscapes considered include vegetated areas surrounding the cities of Hobart, Melbourne, Adelaide, Canberra, and Sydney. Using a simulation approach, we examine the potential range of fires that could occur in a region with varying levels of edge and landscape prescribed burning treatment regimes. Damages to assets are measured for houses, lives, transmission lines, carbon and ecological assets. Costs of treatments are estimated from published models and all data are analyzed using multi-criteria decision analysis. Cost-effectiveness of prescribed burning varies widely between regions. Variations primarily relate to the spatial configuration of assets and natural vegetation. Regions with continuous urban interface adjacent to continuous vegetation had the most cost-effective fuel treatment strategies. In contrast, those regions with fragmented vegetation and discontinuous interfaces demonstrated the lowest cost-effectiveness of treatments. Quantifying the extent to which fuel treatments can reduce the risk to assets is vital for determining the location and extent of treatments across a landscape

Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand

Levels of fire activity and severity that are unprecedented in the instrumental record have recently been observed in forested regions around the world. Using a large sample of daily fire events and hourly climate data, here we show that fire activity in all global forest biomes responds strongly and predictably to exceedance of thresholds in atmospheric water demand, as measured by maximum daily vapour pressure deficit. The climatology of vapour pressure deficit can therefore be reliably used to predict forest fire risk under projected future climates. We find that climate change is projected to lead to widespread increases in risk, with at least 30 additional days above critical thresholds for fire activity in forest biomes on every continent by 2100 under rising emissions scenarios. Escalating forest fire risk threatens catastrophic carbon losses in the Amazon and major population health impacts from wildfire smoke in south Asia and east Africa.he authors acknowledge the New South Wales Government’s Department of Planning, Industry & Environment for providing funds to support this research via the NSW Bushfire Risk Management Research Hub. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Some of the analysis was carried out on the National Computational Infrastructure (NCI) which is supported by the Australian Commonwealth Government

Worldsheet correlators in AdS(3)/CFT(2)

The AdS_3/CFT_2 correspondence is checked beyond the supergravity approximation by comparing correlation functions. To this end we calculate 2- and 3-point functions on the sphere of certain chiral primary operators for strings on AdS_3 x S^3 x T^4. These results are then compared with the corresponding amplitudes in the dual 2-dimensional conformal field theory. In the limit of small string coupling, where the sphere diagrams dominate the string perturbation series, beautiful agreement is found.Comment: 23 page

On the Boundary Dynamics of Chern-Simons Gravity

We study Chern-Simons theory with a complex G_C or a real G x G gauge group on a manifold with boundary - this includes Lorentzian and Euclidean (anti-) de Sitter (E/A)dS gravity for G=SU(2) or G=SL(2,R). We show that there is a canonical choice of boundary conditions that leads to an unambiguous, fully covariant and gauge invariant, off-shell derivation of the boundary action - a G_C/G or G WZW model, coupled in a gauge invariant way to the boundary value of the gauge field. In particular, for (E/A)dS gravity, the boundary action is a WZW model with target space (E/A)dS_3, reminiscent of a worldsheet for worldsheet mechanism. We discuss in some detail the properties of the boundary theories that arise and we confront our results with various related constructions in the literature.Comment: 22 pages, LaTeX2e, v2: JHEP3.cls, references and a footnote adde

A semi-mechanistic model for predicting daily variations in species-level live fuel moisture content

Live Fuel Moisture Content (LFMC) is one of the main factors affecting forest ignitability as it determines the availability of existing live fuel to burn. Currently, LFMC is monitored through spectral vegetation indices or inferred from meteorological drought indices. While useful, neither approach provides mechanistic insights into species-specific LFMC variation and they are limited in the ability to forecast LFMC under altered future climates. Here, we developed a semi-mechanistic model to predict daily variation in LFMC across woody species from different functional types by adjusting a soil water balance model which estimates predawn leaf water potential (Ψpd). Our overarching goal was to balance the trade-off between biological realism, which enhances model applicability, and parameterization complexity, which may limit its value within operational settings. After calibration, model predictions were validated against a dataset comprising 1659 LFMC observations across peninsular Spain, belonging to different functional types and from contrasting climates. The overall goodness of fit for our model (R2 = 0.5) was better than that obtained by an existing models based on drought indices (R2 = 0.3) or spectral vegetation indices (R2 = 0.1). We observed the best predictive performance for seeding shrubs (R2 = 0.6) followed by trees (R2 = 0.5) and resprouting shrubs (R2 = 0.4). Through its relatively simple parameterization, the approach developed here may pave the way for a new generation of process-based models that can be used for operational purposes within fire risk mitigation scenarios.This work was partly founded by the Spanish Government, grant number RTI2018-094691-B-C31 (MCIU/AEI/FEDER, EU) . R.B-R. ac-knowledges the Community of Madrid for the predoctoral contract PEJD-2019-PRE/AMB-15,644 funded by the Youth Employment Initia-tive (YEI) . M. De C. was supported by the Spanish Ministry of Science and Innovation via competitive grant CGL2017-89149-C2-2-R. UNED founding for open access publishing

Remarks on the rolling tachyon BCFT

It is shown how the boundary correlators of the Euclidean theory corresponding to the rolling tachyon solution can be calculated directly from Sen's boundary state. The resulting formulae reproduce precisely the expected perturbative open string answer. We also determine the open string spectrum and comment on the implications of our results for the timelike theory.Comment: 20 pages, harvmac(b), no figure