Estimation of groundwater storage loss for the Indian Ganga Basin using multiple lines of evidence.

We used remote sensing data, field observations and numerical groundwater modelling to investigate long-term groundwater storage losses in the regional aquifer of the Ganga Basin in India. This comprised trend analysis for groundwater level observations from 2851 monitoring bores, groundwater storage anomaly estimation using GRACE and Global Land Data Assimilation System (GLDAS) data sets and numerical modelling of long-term groundwater storage changes underpinned by over 50,000 groundwater level observations and uncertainty analysis. Three analyses based on different methods consistently informed that groundwater storage in the aquifer is declining at a significant rate. Groundwater level trend indicated storage loss in the range - 1.1 to - 3.3 cm year-1 (median - 2.6 cm year-1) while the modelling and GRACE storage anomaly methods indicated the storage loss in the range of - 2.1 to - 4.5 cm year-1 (median - 3.2 cm year-1) and - 1.0 to - 4.2 cm year-1 (median - 1.7 cm year-1) respectively. Probabilistic modelling analysis also indicated that the average groundwater storage is declining in all the major basin states, the highest declining trend being in the western states of Rajasthan, Haryana and Delhi. While smaller compared to the western states, average groundwater storage in states further towards east-Uttar Pradesh, Bihar and West Bengal within the basin are also declining. Time series of storage anomalies obtained from the three methods showed similar trends. Probabilistic storage analysis using the numerical model vetted by observed trend analysis and GRACE data provides the opportunity for predictive analysis of storage changes for future climate and other scenarios.

Spatio-Temporal Modelling Informing Wolbachia Replacement Releases in a Low Rainfall Climate.

Releases of Aedes aegypti carrying Wolbachia bacteria are known to suppress arbovirus transmission and reduce the incidence of vector-borne diseases. In planning for Wolbachia releases in the arid environment of Jeddah, Saudi Arabia, we collected entomological data with ovitraps across a 7-month period in four locations. Herein, we show that mosquito presence in basements does not differ from that of non-basement areas of buildings. In modelling mosquito presence across the study sites, we found the spatial structure to be statistically significant in one of the four sites, while a significant spatial structure was found for egg production data across three of the four sites. The length scales of the spatial covariance functions fitted to the egg production data ranged from 143 m to 574 m, indicating that high productivity regions can be extensive in size. Rank-correlation analyses indicated that mosquito presence tended to persist from the dry to wet season, but that egg production ranks at locations could reverse. The data suggest that, in Jeddah, the quality of the local environment for breeding can vary over time. The data support the feasibility of dry season releases but with release numbers needing to be flexible depending on local rates of invasion.

Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks.

Time series data from environmental monitoring stations are often analysed with machine learning methods on an individual basis, however recent advances in the machine learning field point to the advantages of incorporating multiple related time series from the same monitoring network within a 'global' model. This approach provides the opportunity for larger training data sets, allows information to be shared across the network, leading to greater generalisability, and can overcome issues encountered in the individual time series, such as small datasets or missing data. We present a case study involving the analysis of 165 time series from groundwater monitoring wells in the Namoi region of Australia. Analyses of the multiple time series using a variety of different aggregations are compared and contrasted (with single time series, subsets, and all of the time series together), using variations of the multilayer perceptron (MLP), self-organizing map (SOM), long short-term memory (LSTM), and a recently developed LSTM extension (DeepAR) that incorporates autoregressive terms and handles multiple time series. The benefits, in terms of prediction performance, of these various approaches are investigated, and challenges such as differing measurement frequencies and variations in temporal patterns between the time series are discussed. We conclude with some discussion regarding recommendations and opportunities associated with using networks of environmental data to help inform future resource-related decision making.

Releasing incompatible males drives strong suppression across populations of wild and Wolbachia-carrying Aedes aegypti in Australia.

Releasing sterile or incompatible male insects is a proven method of population management in agricultural systems with the potential to revolutionize mosquito control. Through a collaborative venture with the "Debug" Verily Life Sciences team, we assessed the incompatible insect technique (IIT) with the mosquito vector Aedes aegypti in northern Australia in a replicated treatment control field trial. Backcrossing a US strain of Ae. aegypti carrying Wolbachia wAlbB from Aedes albopictus with a local strain, we generated a wAlbB2-F4 strain incompatible with both the wild-type (no Wolbachia) and wMel-Wolbachia Ae. aegypti now extant in North Queensland. The wAlbB2-F4 strain was manually mass reared with males separated from females using Verily sex-sorting technologies to obtain no detectable female contamination in the field. With community consent, we delivered a total of three million IIT males into three isolated landscapes of over 200 houses each, releasing ∼50 males per house three times a week over 20 wk. Detecting initial overflooding ratios of between 5:1 and 10:1, strong population declines well beyond 80% were detected across all treatment landscapes when compared to controls. Monitoring through the following season to observe the ongoing effect saw one treatment landscape devoid of adult Ae. aegypti early in the season. A second landscape showed reduced adults, and the third recovered fully. These encouraging results in suppressing both wild-type and wMel-Ae. aegypti confirms the utility of bidirectional incompatibility in the field setting, show the IIT to be robust, and indicate that the removal of this arbovirus vector from human-occupied landscapes may be achievable.

Trends in tuna carbon isotopes suggest global changes in pelagic phytoplankton communities.

Considerable uncertainty remains over how increasing atmospheric CO2 and anthropogenic climate changes are affecting open-ocean marine ecosystems from phytoplankton to top predators. Biological time series data are thus urgently needed for the world's oceans. Here, we use the carbon stable isotope composition of tuna to provide a first insight into the existence of global trends in complex ecosystem dynamics and changes in the oceanic carbon cycle. From 2000 to 2015, considerable declines in δ13 C values of 0.8‰-2.5‰ were observed across three tuna species sampled globally, with more substantial changes in the Pacific Ocean compared to the Atlantic and Indian Oceans. Tuna recorded not only the Suess effect, that is, fossil fuel-derived and isotopically light carbon being incorporated into marine ecosystems, but also recorded profound changes at the base of marine food webs. We suggest a global shift in phytoplankton community structure, for example, a reduction in 13 C-rich phytoplankton such as diatoms, and/or a change in phytoplankton physiology during this period, although this does not rule out other concomitant changes at higher levels in the food webs. Our study establishes tuna δ13 C values as a candidate essential ocean variable to assess complex ecosystem responses to climate change at regional to global scales and over decadal timescales. Finally, this time series will be invaluable in calibrating and validating global earth system models to project changes in marine biota.

Variation in Morphology and Airborne Dispersal of the Urticating Apparatus of Ochrogaster lunifer (Lepidoptera: Notodontidae), an Australian Processionary Caterpillar, and Implications for Livestock and Humans.

True setae borne on the abdominal tergites of Ochrogaster lunifer Herrich-Schӓffer caterpillars are the agents of an irritating contact dermatitis, osteomyelitis, ophthalmia, and severe allergic reactions in humans, and are the cause of Equine Amnionitis and Fetal Loss in Australia. The setae are detached and readily dislodge from the integument whereby they disperse throughout the environment. To better understand the true setae of O. lunifer as agents of medical and veterinary concern, we studied their characteristics and distance dispersed. Whereas members of the European Thaumetopoeinae have been widely studied, their southern-hemisphere counterparts such as O. lunifer are not well known despite their harmfulness and known medical and veterinary importance. The caterpillar's investment in true setae increased with age and size, and two distinct size classes co-occurred in setae fields. A previously undescribed morphological type of true seta was found on the first abdominal segment. All true setae were calculated to travel long distances in the air even under light breeze conditions. Our results show there is a high risk of exposure to airborne urticating setae within 100 m of elevated caterpillar activity, and a likely risk of exposure for some kilometers in the direction of the prevailing breeze. This information should be used to inform management strategies in areas where urticating processionary caterpillars are active, and especially during periods of an outbreak.