Stress triangle: do introduced predators exert indirect costs on native predators and prey?

Non-consumptive effects of predators on each other and on prey populations often exceed the effects of direct predation. These effects can arise from fear responses elevating glucocorticoid (GC) hormone levels (predator stress hypothesis) or from increased vigilance that reduces foraging efficiency and body condition (predator sensitive foraging hypothesis); both responses can lead to immunosuppression and increased parasite loads. Non-consumptive effects of invasive predators have been little studied, even though their direct impacts on local species are usually greater than those of their native counterparts. To address this issue, we explored the non-consumptive effects of the invasive red fox Vulpes vulpes on two native species in eastern Australia: a reptilian predator, the lace monitor Varanus varius and a marsupial, the ringtail possum Pseudocheirus peregrinus. In particular, we tested predictions derived from the above two hypotheses by comparing the basal glucocorticoid levels, foraging behaviour, body condition and haemoparasite loads of both native species in areas with and without fox suppression. Lace monitors showed no GC response or differences in haemoparasite loads but were more likely to trade safety for higher food rewards, and had higher body condition, in areas of fox suppression than in areas where foxes remained abundant. In contrast, ringtails showed no physiological or behavioural differences between fox-suppressed and control areas. Predator sensitive foraging is a non-consumptive cost for lace monitors in the presence of the fox and most likely represents a response to competition. The ringtail\u27s lack of response to the fox potentially represents complete naiveté or strong and rapid selection to the invasive predator. We suggest evolutionary responses are often overlooked in interactions between native and introduced species, but must be incorporated if we are to understand the suite of forces that shape community assembly and function in the wake of biological invasions

Anthropogenic resource subsidies determine space use by Australian arid zone dingoes: an improved resource selection modelling approach

Dingoes (Canis lupus dingo) were introduced to Australia and became feral at least 4,000 years ago. We hypothesized that dingoes, being of domestic origin, would be adaptable to anthropogenic resource subsidies and that their space use would be affected by the dispersion of those resources. We tested this by analyzing Resource Selection Functions (RSFs) developed from GPS fixes (locations) of dingoes in arid central Australia. Using Generalized Linear Mixed-effect Models (GLMMs), we investigated resource relationships for dingoes that had access to abundant food near mine facilities, and for those that did not. From these models, we predicted the probability of dingo occurrence in relation to anthropogenic resource subsidies and other habitat characteristics over ∼ 18,000 km(2). Very small standard errors and subsequent pervasively high P-values of results will become more important as the size of data sets, such as our GPS tracking logs, increases. Therefore, we also investigated methods to minimize the effects of serial and spatio-temporal correlation among samples and unbalanced study designs. Using GLMMs, we accounted for some of the correlation structure of GPS animal tracking data; however, parameter standard errors remained very small and all predictors were highly significant. Consequently, we developed an alternative approach that allowed us to review effect sizes at different spatial scales and determine which predictors were sufficiently ecologically meaningful to include in final RSF models. We determined that the most important predictor for dingo occurrence around mine sites was distance to the refuse facility. Away from mine sites, close proximity to human-provided watering points was predictive of dingo dispersion as were other landscape factors including palaeochannels, rocky rises and elevated drainage depressions. Our models demonstrate that anthropogenically supplemented food and water can alter dingo-resource relationships. The spatial distribution of such resources is therefore critical for the conservation and management of dingoes and other top predators

A massive reservoir of low-excitation molecular gas at high redshift

Molecular hydrogen is an important component of galaxies because it fuels star formation and accretion onto AGN, the two processes that generate the large infrared luminosities of gas-rich galaxies. Observations of spectral-line emission from the tracer molecule CO are used to probe the properties of this gas. But the lines that have been studied in the local Universe, mostly the lower rotational transitions of J = 1-0 and J = 2-1, have hitherto been unobservable in high-redshift galaxies. Instead, higher transitions have been used, although the densities and temperatures required to excite these higher transitions may not be reached by much of the gas. As a result, past observations may have underestimated the total amount of molecular gas by a substantial amount. Here we report the discovery of large amounts of low-excitation molecular gas around the infrared-luminous quasar, APM 08279+5255 at z = 3.91, using the two lowest excitation lines of 12CO (J = 1-0 and J = 2-1). The maps confirm the presence of hot and dense gas near the nucleus, and reveal an extended reservoir of molecular gas with low excitation that is 10 to 100 times more massive than the gas traced by higher-excitation observations. This raises the possibility that significant amounts of low-excitation molecular gas may lurk in the environments of high-redshift (z > 3) galaxies.Comment: To appear as a Letter to Nature, 4th January 200

Counting the bodies: Estimating the numbers and spatial variation of Australian reptiles, birds and mammals killed by two invasive mesopredators

Aim Introduced predators negatively impact biodiversity globally, with insular fauna often most severely affected. Here, we assess spatial variation in the number of terrestrial vertebrates (excluding amphibians) killed by two mammalian mesopredators introduced to Australia, the red fox (Vulpes vulpes) and feral cat (Felis catus). We aim to identify prey groups that suffer especially high rates of predation, and regions where losses to foxes and/or cats are most substantial. Location Australia. Methods We draw information on the spatial variation in tallies of reptiles, birds and mammals killed by cats in Australia from published studies. We derive tallies for fox predation by (i) modelling continental-scale spatial variation in fox density, (ii) modelling spatial variation in the frequency of occurrence of prey groups in fox diet, (iii) analysing the number of prey individuals within dietary samples and (iv) discounting animals taken as carrion. We derive point estimates of the numbers of individuals killed annually by foxes and by cats and map spatial variation in these tallies. Results Foxes kill more reptiles, birds and mammals (peaking at 1071 km−2 year−1) than cats (55 km−2 year−1) across most of the unmodified temperate and forested areas of mainland Australia, reflecting the generally higher density of foxes than cats in these environments. However, across most of the continent – mainly the arid central and tropical northern regions (and on most Australian islands) – cats kill more animals than foxes. We estimate that foxes and cats together kill 697 million reptiles annually in Australia, 510 million birds and 1435 million mammals. Main conclusions This continental-scale analysis demonstrates that predation by two introduced species takes a substantial and ongoing toll on Australian reptiles, birds and mammals. Continuing population declines and potential extinctions of some of these species threatens to further compound Australia's poor contemporary conservation record

Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass

Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.Fil: Daleo, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Chaneton, Enrique Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Iribarne, Oscar Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Tognetti, Pedro Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Bruschetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: MacDougall, Andrew S.. University Of Guelph. Department Of Integrative Biology.; CanadáFil: Pascual, Jesus Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Sankaran, Mahesh. University of Leeds; Reino Unido. Tata Institute of Fundamental Research; IndiaFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Wang, Shaopeng. Peking University; ChinaFil: Bagchi, Sumanta. Indian Institute of Science; IndiaFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Catford, Jane A.. University of Melbourne; Australia. Kings College London (kcl);Fil: Dickman, Chris R.. The University Of Sydney; AustraliaFil: Dickson, Tymothy L.. University of Nebraska; Estados UnidosFil: Donohue, Ian. Trinity College Dublin; Reino UnidoFil: Eisenhauer, Nico. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research; AlemaniaFil: Gruner, Daniel S.. University of Maryland; Estados UnidosFil: Haider, Sylvia. German Centre for Integrative Biodiversity Research; Alemania. Martin Luther University Halle-Wittenberg; Alemania. Leuphana University of Lüneburg; AlemaniaFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Knops, Johannes M. H.. Xi’an Jiaotong-Liverpool University; ChinaFil: Lekberg, Ylva. University of Montana; Estados UnidosFil: McCulley, Rebecca L.. University of Kentucky; Estados UnidosFil: Moore, Joslin L.. University of Melbourne; Australia. Monash University; Australia. Arthur Rylah Institute for Environmental Research; AustraliaFil: Mortensen, Brent. Benedictine College; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de la Patagonia Austral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rocca, Camila. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentin

Quantifying extinction risk and forecasting the number of impending Australian bird and mammal extinctions

A critical step towards reducing the incidence of extinction is to identify and rank the species at highest risk, while implementing protective measures to reduce the risk of extinction to such species. Existing global processes provide a graded categorisation of extinction risk. Here we seek to extend and complement those processes to focus more narrowly on the likelihood of extinction of the most imperilled Australian birds and mammals. We considered an extension of existing IUCN and NatureServe criteria, and used expert elicitation to rank the extinction risk to the most imperilled species, assuming current management. On the basis of these assessments, and using two additional approaches, we estimated the number of extinctions likely to occur in the next 20 years. The estimates of extinction risk derived from our tighter IUCN categorisations, NatureServe assessments and expert elicitation were poorly correlated, with little agreement among methods for which species were most in danger – highlighting the importance of integrating multiple approaches when considering extinction risk. Mapped distributions of the 20 most imperilled birds reveal that most are endemic to islands or occur in southern Australia. The 20 most imperilled mammals occur mostly in northern and central Australia. While there were some differences in the forecasted number of extinctions in the next 20 years among methods, all three approaches predict further species loss. Overall, we estimate that another seven Australian mammals and 10 Australian birds will be extinct by 2038 unless management improves

Saving the world’s terrestrial megafauna

From the late Pleistocene to the Holocene, and now the so called Anthropocene, humans have been driving an ongoing series of species declines and extinctions (Dirzo et al. 2014). Large-bodied mammals are typically at a higher risk of extinction than smaller ones (Cardillo et al. 2005). However, in some circumstances terrestrial megafauna populations have been able to recover some of their lost numbers due to strong conservation and political commitment, and human cultural changes (Chapron et al. 2014). Indeed many would be in considerably worse predicaments in the absence of conservation action (Hoffmann et al. 2015). Nevertheless, most mammalian megafauna face dramatic range contractions and population declines. In fact, 59% of the world’s largest carnivores (≥ 15 kg, n = 27) and 60% of the world’s largest herbivores (≥ 100 kg, n = 74) are classified as threatened with extinction on the International Union for the Conservation of Nature (IUCN) Red List (supplemental table S1 and S2). This situation is particularly dire in sub-Saharan Africa and Southeast Asia, home to the greatest diversity of extant megafauna (figure 1). Species at risk of extinction include some of the world’s most iconic animals—such as gorillas, rhinos, and big cats (figure 2 top row)—and, unfortunately, they are vanishing just as science is discovering their essential ecological roles (Estes et al. 2011). Here, our objectives are to raise awareness of how these megafauna are imperiled (species in supplemental table S1 and S2) and to stimulate broad interest in developing specific recommendations and concerted action to conserve them

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups