ORCID Profile
0000-0002-8966-9370
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Agricultural Economics | Environment and Resource Economics | Experimental Economics | Applied Economics |
Market-Based Mechanisms | Economic Incentives for Environmental Protection | Rural Land Policy
Publisher: Wiley
Date: 30-12-2019
DOI: 10.1111/EMR.12398
Publisher: Wiley
Date: 09-1998
Publisher: Elsevier BV
Date: 09-2020
Publisher: Wiley
Date: 09-2021
DOI: 10.1111/EMR.12510
Abstract: The Darwin Agreement is a collective response from Australian national restoration organisations to the United Nation's declaration of 2021–2030 as the UN Decade on Ecosystem Restoration. The agreement functions as terms of reference for a new alliance, the Restoration Decade Alliance, to optimise on‐ground actions and advocacy to retain native ecosystems, reduce impacts upon them and restore them to the highest extent practicable. The Restoration Decade Alliance is expected to grow in membership and influence throughout the Decade and to help galvanise increased action and improved policy across the whole of Australian society including government, industry and community sectors. The UN Decade initiative seeks to reinforce efforts of all players, small and large, to help shift the currently destructive trajectory of humankind to a trajectory of recovery for the benefit of humans and nature.
Publisher: Wiley
Date: 20-06-2007
Publisher: Elsevier BV
Date: 03-2018
Publisher: CSIRO Publishing
Date: 2005
DOI: 10.1071/WR05010
Abstract: Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low ( %) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.
Publisher: Wiley
Date: 03-04-2021
Abstract: Long‐term bio ersity monitoring programs provide important information about species' trajectories and broader environmental change. Often constrained by funding and organisational capability and commitment, monitoring programs need to be optimised to maximise ecological and economic efficiencies, as part of sound adaptive management. The monitoring design requirements for detecting bio ersity trends, across assemblages of species with different traits, can be informed by historical datasets. Using data from a landscape‐scale ( c . 2,500 km 2 ) bird monitoring program encompassing 151 sites visited three times annually over 16 years, we used res ling to simulate different monitoring designs. We quantified the capacity of modified monitoring regimes to detect population trends for 65 bird species with different densities, detectabilities and specialisations. The majority (58%) of species exhibited a significant decline in relative abundance, with the ability to detect trends proportional to the length of the time series used for analysis. The percentage of trends detected decreased as survey sites or sessions were dropped from the monitoring dataset. Statistically significant trends remained undetected for an additional 2.5 species for every 10% of sites excluded randomly from the program. As monitoring effort was reduced, the precision of trend estimates for rare species was particularly compromised. Conducting bird surveys every second year would produce better results than an equivalent reduction in effort achieved by surveying only half the sites each year, but could compromise the sustainability of the program. If the number of survey sites were reduced, trend detection would be optimised by retaining the spatial extent of the surveys (i.e. by dropping sites from well‐surveyed regions rather than excluding outlying, isolated sites), but the cost savings of this approach would be small. Synthesis and applications . Reduced monitoring effort will compromise trend detection for rare species or species that are difficult to observe, and declining species that will soon become rare. Consequently, monitoring effort that is considered ‘surplus’ today could provide critical data for detecting species‐level trends and prioritising conservation interventions in the future. Further, s ling efficiencies are not all‐important we must also consider the impacts of survey design modification on the social and political sustainability of existing monitoring programs.
Publisher: Elsevier BV
Date: 11-2017
Publisher: Elsevier BV
Date: 2019
DOI: 10.1016/J.ENVPOL.2019.113463
Abstract: Growing evidence suggests that metallic oxide nanoparticles can pose a severe risk to the health of invertebrates. Previous attention has been mostly paid to the effects of metallic oxide nanoparticles on the survival, growth and physiology of animals. In comparison, the effects on gut microbiota and incidence of antibiotic resistance genes (ARGs) in soil fauna remain poorly understood. We conducted a microcosm study to explore the responses of the non-target soil invertebrate Enchytraeus crypticus gut microbiota and resistomes to copper oxide nanoparticles (CuO NPs) and copper nitrate by using bacterial 16S rRNA gene licons sequencing and high throughput quantitative PCR. The results showed that exposure to Cu
Publisher: Informa UK Limited
Date: 02-01-2018
Publisher: Wiley
Date: 12-04-2021
DOI: 10.1111/GCB.15613
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 04-2019
DOI: 10.1016/J.SCITOTENV.2018.12.445
Abstract: Liming is a common agronomic practice used for alleviating soil acidification to improve plant growth. However, it is still unclear how liming can affect the gut microbiota composition of soil fauna, and subsequently the nutrient cycling and litter decomposition mediated by soil fauna. In the present study the effect of liming on the gut microbiota of two types of soil fauna, Folsomia candida, and Enchytraeus crypticus was investigated by using 16S rRNA gene high-throughput sequencing. The results revealed that there are differences between the gut microbial communities of the two types of soil fauna as well as between the gut microbiome of the soil fauna and the surrounding soil. Enterobacteriaceae and Bacillaceae were the predominant families in the gut microbiota of E. crypticus, while Rickettsiaceae and Moraxellaceae were the predominant families in the gut microbiota of F. candida. Liming affected the gut microbiota of E. crypticus at both the taxonomical and core microbiota level. The gut microbiota of F. candida was not affected by liming. Structural equation models suggest that 97% of the variation in the E. crypticus gut microbiota could be explained by liming-induced changes in soil properties and the soil microbial community. The indirect effects of liming, caused by a shift in the soil microbial community, contributed more in reshaping the gut microbiota of E. crypticus than the direct effects of the changed soil properties did. These findings suggest that the effects of liming on the gut microbiota composition in soil fauna are species-specific and are likely dependent on the response of the host to changes in soil properties and the soil microbial community.
Publisher: Wiley
Date: 08-05-2019
Publisher: American Chemical Society (ACS)
Date: 08-10-2019
Abstract: Microplastics pollution in the environment is now receiving worldwide attention however, the effects of copollution of antibiotics and microplastics on the gut microbiome of globally distributed and functionally important nontarget soil animals remain poorly understood. We studied a model collembolan (
Publisher: Wiley
Date: 29-10-2007
Publisher: Elsevier BV
Date: 04-2020
DOI: 10.1016/J.JHAZMAT.2019.122012
Abstract: It has been proved that nanoplastics can effectively adsorb pollutants and thus influence their behavior and availability. The combined toxic effects of nanoplastic and its adsorbed pollutant on the soil fauna are still not well known. We used high-throughput quantitative PCR to explore the effects of oral nanoscale polystyrene and tetracycline exposure on antibiotic resistance genes in the soil invertebrate Enchytraeus crypticus, and used bacterial 16S rRNA gene lification sequencing to examine the response of the microbiome of E. crypticus. After 14 days of tetracycline and nanoscale polystyrene exposure, we terminated exposure and monitored the restoration of ARGs and microbiome in the E. crypticus. Results showed that the number of ARGs, especially macrolide-lincosamide-streptogramin B (MLSB), tetracycline ARGs, as well as multidrug ARGs, increased with exposure to nanoscale polystyrene and tetracycline. The abundance of Aminoglycoside and Beta_Lactamase ARGs in E. crypticus also significantly increased. The exposure significantly perturbed the abundance of families Microbacteriaceae, Streptococcaceae, Enterobacteriaceae, Rhodocyclaceae and Sphinomonadaceae. After terminating exposure for 14 days, the ersity and abundance of ARGs were not completely restored, while the microbiome was not permanently changed but reversibly impacted.
Publisher: Now Publishers
Date: 06-11-2018
DOI: 10.1561/101.00000098
Publisher: Elsevier BV
Date: 12-2022
Publisher: MDPI AG
Date: 11-10-2020
DOI: 10.3390/W12102825
Abstract: Climate change can have critical impacts on ecosystem services (ESs) and their inter-relationships, especially for water-related services. However, there has been little work done on characterizing the current and future changes in these services and their inter-relationships under a changing climate. Based on the revised universal soil loss equation (RUSLE), the soil conservation service curve number model (SCS-CN), and the improved stochastic weather-generator-based statistical downscaled global climate models (GCMs), we examined two important water-related services, namely, the soil conservation (SC) service and the flood mitigation (FM) service, and their inter-relationship under baseline and future climate scenarios (Representative Concentration Pathways (RCPs) 4.5 and 8.5). We took the Upper Hanjiang River Basin (UHRB), which is the core water source area of the China’s South-to-North Water Diversion Project (S–NWDP), as an illustration. The findings revealed that (1) the SC and FM services will both decrease under the two climate scenarios examined (2) the SC and FM services showed a significant synergistic inter-relationship and the synergy will be improved by 16.48% and 2.95% under RCP 4.5 and RCP 8.5, respectively, which provides an opportunity for management optimization (3) the ecological degradation in the UHRB will likely have serious consequences for the middle and lower reaches of the Hanjiang river basin, and therefore impact the actual economic benefits of the S–NWDP. This study points to the necessity for understanding the dynamic changes and inter-relationships of ecosystem services under future climate change and provides information regarding the consequences of climate change, which is useful for policy and infrastructure investment.
No related organisations have been discovered for Patrick O'Connor.
Start Date: 07-2022
End Date: 06-2025
Amount: $614,817.00
Funder: Australian Research Council
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