A threatened species index for Australian birds

Quantifying species population trends is crucial for monitoring progress towards global conservation targets, justifying investments, planning targeted responses and raising awareness about threatened species. Many global indicators are slow in response and report on common species, not on those at greatest risk of extinction. Here we develop a Threatened Species Index as a dynamic tool for tracking annual changes in Australia's imperiled birds. Based on the Living Planet Index method and containing more than 17,000 time series for 65 bird taxa surveyed systematically, the index at its second iteration shows an average reduction of 59% between 1985 and 2016, and 44% between 2000 and 2016. Decreases seem most severe for shorebirds and terrestrial birds and least severe for seabirds. The index provides a potential means for measuring performance against the Convention on Biological Diversity's Aichi Target 12, enabling governments, agencies and the public to observe changes in threatened species

Bayesian Estimation of Animal Movement from Archival and Satellite Tags

The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools

Species History Masks the Effects of Human-Induced Range Loss – Unexpected Genetic Diversity in the Endangered Giant Mayfly Palingenia longicauda

Freshwater biodiversity has declined dramatically in Europe in recent decades. Because of massive habitat pollution and morphological degradation of water bodies, many once widespread species persist in small fractions of their original range. These range contractions are generally believed to be accompanied by loss of intraspecific genetic diversity, due to the reduction of effective population sizes and the extinction of regional genetic lineages. We aimed to assess the loss of genetic diversity and its significance for future potential reintroduction of the long-tailed mayfly Palingenia longicauda (Olivier), which experienced approximately 98% range loss during the past century. Analysis of 936 bp of mitochondrial DNA of 245 extant specimens across the current range revealed a surprisingly large number of haplotypes (87), and a high level of haplotype diversity (). In contrast, historic specimens (6) from the lost range (Rhine catchment) were not differentiated from the extant Rába population (, ), despite considerable geographic distance separating the two rivers. These observations can be explained by an overlap of the current with the historic (Pleistocene) refugia of the species. Most likely, the massive recent range loss mainly affected the range which was occupied by rapid post-glacial dispersal. We conclude that massive range losses do not necessarily coincide with genetic impoverishment and that a species' history must be considered when estimating loss of genetic diversity. The assessment of spatial genetic structures and prior phylogeographic information seems essential to conserve once widespread species

D1 Dopamine Receptor Signaling Is Modulated by the R7 RGS Protein EAT-16 and the R7 Binding Protein RSBP-1 in Caenoerhabditis elegans Motor Neurons

Dopamine signaling modulates voluntary movement and reward-driven behaviors by acting through G protein-coupled receptors in striatal neurons, and defects in dopamine signaling underlie Parkinson's disease and drug addiction. Despite the importance of understanding how dopamine modifies the activity of striatal neurons to control basal ganglia output, the molecular mechanisms that control dopamine signaling remain largely unclear. Dopamine signaling also controls locomotion behavior in Caenorhabditis elegans. To better understand how dopamine acts in the brain we performed a large-scale dsRNA interference screen in C. elegans for genes required for endogenous dopamine signaling and identified six genes (eat-16, rsbp-1, unc-43, flp-1, grk-1, and cat-1) required for dopamine-mediated behavior. We then used a combination of mutant analysis and cell-specific transgenic rescue experiments to investigate the functional interaction between the proteins encoded by two of these genes, eat-16 and rsbp-1, within single cell types and to examine their role in the modulation of dopamine receptor signaling. We found that EAT-16 and RSBP-1 act together to modulate dopamine signaling and that while they are coexpressed with both D1-like and D2-like dopamine receptors, they do not modulate D2 receptor signaling. Instead, EAT-16 and RSBP-1 act together to selectively inhibit D1 dopamine receptor signaling in cholinergic motor neurons to modulate locomotion behavior

Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes?

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions

Living on the Edge: Assessing the Extinction Risk of Critically Endangered Bonelli’s Eagle in Italy

Background: The population of Bonelli’s eagle (Aquila fasciata) has declined drastically throughout its European range due to habitat degradation and unnatural elevated mortality. There are less than 1500 breeding pairs accounted for in Europe, and the species is currently catalogued as Critically Endangered in Italy, where the 22 territories of Sicily, represent nearly 95% of the entire Italian population. However, despite national and European conservation concerns, the species currently lacks a specific conservation plan, and no previous attempts to estimate the risk of extinction have been made. Methodology/Principal Findings: We incorporated the most updated demographic information available to assess the extinction risk of endangered Bonelli’s eagle in Italy through a Population Viability Analysis. Using perturbation analyses (sensitivity and elasticity), and a combination of demographic data obtained from an assortment of independent methods, we evaluated which demographic parameters have more influence on the population’s fate. We also simulated different scenarios to explore the effects of possible management actions. Our results showed that under the current conditions, Bonelli’s eagle is expected to become extinct in Italy in less than 50 years. Stand-alone juvenile mortality was the most critical demographic parameter with the strongest influence on population persistence with respect to other demographic parameters. Measures aimed at either decreasing juvenile mortality, adult mortality or decreasing both juvenile and adult mortality resulted in equivalent net positive effects on population persistence (population growth rate l.1). In contrast, changes aimed at increasing breeding success had limited positive effects on demographic trends. Conclusions/Significance: Our PVA provides essential information to direct the decision-making process and exposes gaps in our previous knowledge. To ensure the long-term persistence of the species in Italy, measures are urgently needed to decrease both adult mortality due to poaching and juvenile mortality due to nest plundering, the top ranking mortality causes.PLL is supported by a “Juan de la Cierva” postdoctoral grant of the Spanish Ministry of Economy and Competitiveness (reference JCI-2011–09588)

Matrix composition mediates effects of habitat fragmentation: a modelling study

Context Habitat loss has clear negative effects on biodiversity, but whether fragmentation per se (FPS), excluding habitat loss does is debatable. A contribution to this debate may be that many fragmentation studies tend to use landscapes of fragmented focal-habitat and a single vastly different species-poor intervening land cover (the matrix). Objectives How does matrix composition influence the effect of FPS on biodiversity?. Methods Using an individual-based model to investigate the effect of different configurations of the matrix on the relationship between FPS and biodiversity of the focal-habitat. We manipulated the number and quality of land cover types in the matrix, and their similarity to the focal-habitat. Results Extremely different matrix, caused an order of magnitude stronger effect of FPS on alpha- and gamma-diversity and beta-diversity to decline. Low FPS led to high gamma-diversity. Increasing FPS caused a dramatic decline to low diversity. In contrast landscapes with a more similar matrix had lower diversity under low FPS declining little with increasing FPS. Having few matrix types caused beta-diversity to decline in general compared to landscapes with a larger numbers. Conclusions The effects of FPS on biodiversity may change depending on the number of matrix types and their similarity to the focal-habitat. We recommend that fragmentation studies should consider a greater variety of landscapes to help assess in which cases FPS does not have a negative impact and allow better predictions of the impacts of fragmentation. We show the importance of having a diversity of matrix land cover types and improving the hospitability of the matrix for species dependent on the focal-habitat

The power of monitoring: optimizing survey designs to detect occupancy changes in a rare amphibian population

Biodiversity conservation requires reliable species assessments and rigorously designed surveys. However, determining the survey effort required to reliably detect population change can be challenging for rare, cryptic and elusive species. We used a tropical bromeliad-dwelling frog as a model system to explore a cost-effective sampling design that optimizes the chances of detecting a population decline. Relatively few sampling visits were needed to estimate occupancy and detectability with good precision, and to detect a 30% change in occupancy with 80% power. Detectability was influenced by observer expertise, which therefore also had an effect on the sampling design – less experienced observers require more sampling visits to detect the species. Even when the sampling design provides precise parameter estimates, only moderate to large changes in occupancy will be detected with reliable power. Detecting a population change of 15% or less requires a large number of sites to be surveyed, which might be unachievable for range-restricted species occurring at relatively few sites. Unless there is high initial occupancy, rare and cryptic species will be particularly challenging when it comes to detecting small population changes. This may be a particular issue for long-term monitoring of amphibians which often display low detectability and wide natural fluctuations