Dingo baiting did not reduce fetal/calf loss in beef cattle in northern South Australia

2019 ◽  
Vol 59 (2) ◽  
pp. 319 ◽  
Author(s):  
Greg Campbell ◽  
Andrew Coffey ◽  
Heather Miller ◽  
John L. Read ◽  
Anthony Brook ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Vegetation Index ◽  
South Australia ◽  
Explanatory Factors ◽  
Direct Observations ◽  
Normalised Difference Vegetation Index ◽  
Beef Herds ◽  
Arid Rangelands ◽  
Time Of Year ◽  
Livestock Diseases

Beef cattle production is the major agricultural pursuit in the arid rangelands of Australia. Dingo predation is often considered a significant threat to production in rangeland beef herds, but there is a need for improved understanding of the effects of dingo baiting on reproductive wastage. We experimentally compared fetal/calf loss on baited and non-baited treatment areas within three northern South Australian beef herds over a 2–4-year period. At re-musters, lactation was used to determine the outcomes of known pregnancies. Potential explanatory factors for fetal/calf loss (dingo baiting, dingo activity, summer heat, cow age, seasonal conditions, activity of dingo prey and selected livestock diseases) were investigated. From 3145 tracked pregnancies, fetal/calf loss averaged 18.6%, with no overall significant effect of baiting. Fetal/calf loss averaged 27.3% for primiparous (first pregnancy) heifers and 16.8% for multiparous (2nd or later calf) cows. On average, dingo-activity indices were 59.3% lower in baited treatments than in controls, although background site differences in habitat, weather and previous dingo control could have contributed to these lower indices. The overall scale and timing of fetal/calf loss was not correlated with dingo activity, time of year, a satellite-derived measure of landscape greenness (normalised difference vegetation index), or activity of alternative dingo prey. Limited blood testing suggested that successful pregnancy outcomes, especially in primiparous heifers, may have been reduced by the livestock diseases pestivirus and leptospirosis. The percentage occurrence of cattle hair in dingo scats was higher when seasonal conditions were poorer and alternative prey less common, but lack of association between fetal/calf loss and normalised difference vegetation index suggests that carrion feeding, rather than calf predation, was the more likely cause. Nevertheless, during the fair to excellent prevailing seasons, there were direct observations of calf predation. It is likely that ground baiting, as applied, was ineffective in protecting calves, or that site effects, variable cow age and disease confounded our results.

scholarly journals Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Tasya Vadya Sarira ◽  
Kenneth Clarke ◽  
Philip Weinstein ◽  
Lian Pin Koh ◽  
Megan Lewis
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Multispectral Imaging ◽  
Imaging System ◽  
South Australia ◽  
Rapid Identification ◽  
Breeding Habitat ◽  
Mapping Accuracy ◽  
Normalised Difference Vegetation Index ◽  
Mosquito Breeding

Mosquito breeding habitat identification often relies on slow, labour-intensive and expensive ground surveys. With advances in remote sensing and autonomous flight technologies, we endeavoured to accelerate this detection by assessing the effectiveness of a drone multispectral imaging system to determine areas of shallow inundation in an intertidal saltmarsh in South Australia. Through laboratory experiments, we characterised Near-Infrared (NIR) reflectance responses to water depth and vegetation cover, and established a reflectance threshold for mapping water sufficiently deep for potential mosquito breeding. We then applied this threshold to field-acquired drone imagery and used simultaneous in-situ observations to assess its mapping accuracy. A NIR reflectance threshold of 0.2 combined with a vegetation mask derived from Normalised Difference Vegetation Index (NDVI) resulted in a mapping accuracy of 80.3% with a Cohen’s Kappa of 0.5, with confusion between vegetation and shallow water depths (< 10 cm) appearing to be major causes of error. This high degree of mapping accuracy was achieved with affordable drone equipment, and commercially available sensors and Geographic Information Systems (GIS) software, demonstrating the efficiency of such an approach to identify shallow inundation likely to be suitable for mosquito breeding.

scholarly journals Pasture herbage mass, quality and growth in response to three whole-farmlet management systems

2013 ◽  
Vol 53 (8) ◽  
pp. 685 ◽  
Author(s):  
L. M. Shakhane ◽  
C. Mulcahy ◽  
J. M. Scott ◽  
G. N. Hinch ◽  
G. E. Donald ◽  
...  
Keyword(s):  
Growth Rate ◽  
Soil Fertility ◽  
Vegetation Index ◽  
Seasonal Pattern ◽  
Ground Cover ◽  
The Other ◽  
Grazing Management ◽  
Management Systems ◽  
Explanatory Factors ◽  
Normalised Difference Vegetation Index

The effects of different whole-farm management systems were explored in a farmlet trial on the Northern Tablelands of New South Wales, Australia, between July 2000 and December 2006. The three systems examined were first, a moderate input farmlet with flexible grazing on eight paddocks considered ‘typical’ of the region (farmlet B), a second, also with flexible grazing on eight paddocks but with a high level of pasture renovation and increased soil fertility (farmlet A) and a third with the same moderate level of inputs as farmlet B but which practised intensive rotational grazing on 37 paddocks (farmlet C). The changes in herbage mass, herbage quality and pasture growth followed a seasonal pattern typical of the Northern Tablelands with generally higher levels recorded over spring–summer and lower levels in autumn–winter but with substantial differences between years due to the variable climate experienced. Over the first 18 months of the trial there were no significant differences between farmlets in total herbage mass. Although the climate was generally drier than average, the differences between farmlets in pasture herbage mass and quality became more evident over the duration of the experiment. After the farmlet treatments started to take effect, the levels of total and dead herbage mass became significantly lower on farmlet A compared with farmlets B and C. In contrast, the levels of green herbage were similar for all farmlets. Throughout most of the study period, pastures on farmlet A with its higher levels of pasture renovation and soil fertility, had significantly higher DM digestibility for both green and dead herbage components compared with pastures on either of the moderate input systems (B and C). Thus, when green herbage mass and quality were combined, farmlet A tended to have higher levels of green digestible herbage than either of the other farmlets, which had similar levels, suggesting that pasture renovation and soil fertility had more effect on the supply of quality pasture than did grazing management. This difference was observed in spite of the higher stocking rate supported by farmlet A after treatments took effect. Levels of legume herbage mass, while generally low due to the dry conditions, were significantly higher on farmlet A compared with the other two farmlets. While ground cover on farmlet A was found to be less than the other farmlets, this was largely associated with the higher level of pasture renovation. Generally, all three farmlets had ground cover levels well above 70% for the duration of the experiment, thus being above levels considered critical for prevention of erosion. A multivariate analysis showed that the main explanatory factors significantly linked (P < 0.01) with the supply of high quality herbage were, in decreasing order of importance, those related to season and weather, pasture renovation, grazing management and soil fertility. Measurements of net pasture growth conducted using a limited number of grazing exclosure cages on three paddocks per farmlet revealed clear seasonal trends but no significant (P > 0.05) differences between farmlets. However, post hoc estimates of potential pasture growth rate using remotely sensed MODIS satellite images of normalised difference vegetation index captured weekly from each farmlet revealed a significant (P < 0.001) relationship with the seasonal pattern observed in the measurements of pasture growth rate.

A field method for statewide ground-truthing of a spatial pasture growth model

2000 ◽  
Vol 40 (8) ◽  
pp. 1069 ◽  
Author(s):  
R. C. Hassett ◽  
H. L. Wood ◽  
J. O. Carter ◽  
T. J. Danaher
Keyword(s):  
Growth Model ◽  
Vegetation Index ◽  
South Australia ◽  
Basal Area ◽  
Field Method ◽  
Projective Cover ◽  
Efficient Manner ◽  
Related Data ◽  
Normalised Difference Vegetation Index ◽  
Ground Truthing

This paper describes an innovative method, commonly referred to as ‘spider mapping’, that allows pasture biomass and related data to be collected over large areas in a timely and efficient manner. Spider mapping was developed initially to collect data to allow calibration and validation of a spatial and temporal pasture growth model operating across Queensland on a 5 km grid basis. Two field officers made over 220 000 estimates and collected about 1300 samples of pasture biomass between January 1994 and August 1995. A number of selected biomass samples were analysed for nitrogen, phosphorus and carbon content. In addition, data were also collected on foliage projective cover and tree basal area for a range of woodland communities and both variables compared with mean long-term Normalised Difference Vegetation Index values derived from a time series of National Oceanographic and Atmospheric Administration satellite imagery. Both variables were strongly related to the satellite data with overstorey foliage projective cover having the strongest non-linear correlation (r2 = 0.91). The method described here is currently being used in related work in the rangelands of New South Wales, South Australia, Western Australia and the Northern Territory.

Ecological response of Eucalyptus camaldulensis (river red gum) to extended drought and flooding along the River Murray, South Australia (1997–2011) and implications for environmental flow management

2014 ◽  
Vol 65 (12) ◽  
pp. 1082 ◽  
Author(s):  
Tanya M. Doody ◽  
Simon N. Benger ◽  
Jodie L. Pritchard ◽  
Ian C. Overton
Keyword(s):  
Vegetation Index ◽  
Environmental Flows ◽  
Riparian Forest ◽  
South Australia ◽  
Eucalyptus Camaldulensis ◽  
Millennium Drought ◽  
Normalised Difference Vegetation Index ◽  
Floodplain Inundation ◽  
Flood Pulses ◽  
The Relationship

Riparian forest and woodlands of the lower River Murray floodplain are exhibiting deteriorating health as a result of anthropogenic alterations to flow regimes and south-eastern Australia’s long-term ‘Millennium Drought’ from 1997 to 2009. Extensive flooding in 2010/2011 brought the drought to an end, providing an opportunity to monitor ecological floodplain recovery. The relationship between flooding and lateral recharge and condition of the dominant riparian tree species, Eucalyptus camaldulensis, was determined between 2007 and 2011 using the Landsat (LTM5) Normalised Difference Vegetation Index (NDVI). Linking the river hydrograph with the River Murray Floodplain Inundation Model (RiM-FIM) allowed exploration of the relationship between inundation duration and E. camaldulensis water requirements. Results indicate lateral bank recharge is an important mechanism in the maintenance of vegetation condition along the River Murray channel. Higher in-channel irrigation water delivery during summer months was identified as critical to survival of trees adjacent to the channel during the drought. The research suggests that weir pool manipulation to create in-channel flood pulses will aid E. camaldulensis maintenance. Furthermore, release of environmental flows once every 3 to 5 years to create bank-full flow or preferably overbank flows, will increase hydrological connectivity between river banks, wetlands and riparian zones, providing positive ecological benefits to E. camaldulensis and other floodplain and aquatic ecological assets.

scholarly journals Status of Phenological Research Using Sentinel-2 Data: A Review

2020 ◽  
Vol 12 (17) ◽  
pp. 2760
Author(s):  
Gourav Misra ◽  
Fiona Cawkwell ◽  
Astrid Wingler
Keyword(s):  
Vegetation Index ◽  
Temporal Frequency ◽  
Short Wave ◽  
Current State ◽  
Red Edge ◽  
Natural Grasslands ◽  
Wide Range ◽  
Normalised Difference Vegetation Index ◽  
Satellite Sensors ◽  
Sentinel 2

Remote sensing of plant phenology as an indicator of climate change and for mapping land cover has received significant scientific interest in the past two decades. The advancing of spring events, the lengthening of the growing season, the shifting of tree lines, the decreasing sensitivity to warming and the uniformity of spring across elevations are a few of the important indicators of trends in phenology. The Sentinel-2 satellite sensors launched in June 2015 (A) and March 2017 (B), with their high temporal frequency and spatial resolution for improved land mapping missions, have contributed significantly to knowledge on vegetation over the last three years. However, despite the additional red-edge and short wave infra-red (SWIR) bands available on the Sentinel-2 multispectral instruments, with improved vegetation species detection capabilities, there has been very little research on their efficacy to track vegetation cover and its phenology. For example, out of approximately every four papers that analyse normalised difference vegetation index (NDVI) or enhanced vegetation index (EVI) derived from Sentinel-2 imagery, only one mentions either SWIR or the red-edge bands. Despite the short duration that the Sentinel-2 platforms have been operational, they have proved their potential in a wide range of phenological studies of crops, forests, natural grasslands, and other vegetated areas, and in particular through fusion of the data with those from other sensors, e.g., Sentinel-1, Landsat and MODIS. This review paper discusses the current state of vegetation phenology studies based on the first five years of Sentinel-2, their advantages, limitations, and the scope for future developments.

Assessment of changes in the state of the rangelands of Inner Mongolia, China between 1998 and 2007 using remotely sensed data

2012 ◽  
Vol 34 (1) ◽  
pp. 103 ◽  
Author(s):  
Z. M. Hu ◽  
S. G. Li ◽  
J. W. Dong ◽  
J. W. Fan
Keyword(s):  
Inner Mongolia ◽  
Vegetation Index ◽  
Net Primary Productivity ◽  
Temporal Dynamics ◽  
Remotely Sensed ◽  
The State ◽  
Mean Annual Precipitation ◽  
Aboveground Net Primary Productivity ◽  
Remotely Sensed Data ◽  
Normalised Difference Vegetation Index

The spatial annual patterns of aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of the rangelands of the Inner Mongolia Autonomous Region of China, a region in which several projects for ecosystem restoration had been implemented, are described for the years 1998–2007. Remotely sensed normalised difference vegetation index and ANPP data, measured in situ, were integrated to allow the prediction of ANPP and PUE in each 1 km2 of the 12 prefectures of Inner Mongolia. Furthermore, the temporal dynamics of PUE and ANPP residuals, as indicators of ecosystem deterioration and recovery, were investigated for the region and each prefecture. In general, both ANPP and PUE were positively correlated with mean annual precipitation, i.e. ANPP and PUE were higher in wet regions than in arid regions. Both PUE and ANPP residuals indicated that the state of the rangelands of the region were generally improving during the period of 2000–05, but declined by 2007 to that found in 1999. Among the four main grassland-dominated prefectures, the recovery in the state of the grasslands in the Erdos and Chifeng prefectures was highest, and Xilin Gol and Chifeng prefectures was 2 years earlier than Erdos and Hunlu Buir prefectures. The study demonstrated that the use of PUE or ANPP residuals has some limitations and it is proposed that both indices should be used together with relatively long-term datasets in order to maximise the reliability of the assessments.

Assessing the impact of seasonal precipitation and temperature on vegetation in a grass-dominated rangeland

2014 ◽  
Vol 36 (2) ◽  
pp. 185 ◽  
Author(s):  
Fang Chen ◽  
Keith T. Weber
Keyword(s):  
Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Vegetation Growth ◽  
Factors Affecting ◽  
Growing Seasons ◽  
Normalised Difference Vegetation Index ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact ◽  
Precipitation And Temperature

Changes in vegetation are affected by many climatic factors and have been successfully monitored through satellite remote sensing over the past 20 years. In this study, the Normalised Difference Vegetation Index (NDVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, was selected as an indicator of change in vegetation. Monthly MODIS composite NDVI at a 1-km resolution was acquired throughout the 2004–09 growing seasons (i.e. April–September). Data describing daily precipitation and temperature, primary factors affecting vegetation growth in the semiarid rangelands of Idaho, were derived from the Surface Observation Gridding System and local weather station datasets. Inter-annual and seasonal fluctuations of precipitation and temperature were analysed and temporal relationships between monthly NDVI, precipitation and temperature were examined. Results indicated NDVI values observed in June and July were strongly correlated with accumulated precipitation (R2 >0.75), while NDVI values observed early in the growing season (May) as well as late in the growing season (August and September) were only moderately related with accumulated precipitation (R2 ≥0.45). The role of ambient temperature was also apparent, especially early in the growing season. Specifically, early growing-season temperatures appeared to significantly affect plant phenology and, consequently, correlations between NDVI and accumulated precipitation. It is concluded that precipitation during the growing season is a better predictor of NDVI than temperature but is interrelated with influences of temperature in parts of the growing season.

Temporal and spatial heterogeneity of drought impact on vegetation growth on the Inner Mongolian Plateau

2018 ◽  
Vol 40 (2) ◽  
pp. 113 ◽  
Author(s):  
Miao Bailing ◽  
Li Zhiyong ◽  
Liang Cunzhu ◽  
Wang Lixin ◽  
Jia Chengzhen ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Severity Index ◽  
Drought Severity ◽  
Summer Drought ◽  
Desert Steppe ◽  
Vegetation Types ◽  
Mongolian Plateau ◽  
Typical Steppe ◽  
Recent Climate ◽  
Normalised Difference Vegetation Index

Drought frequency and intensity have increased in recent decades, with consequences for the structure and function of ecosystems of the Inner Mongolian Plateau. In this study, the Palmer drought severity index (PDSI) was chosen to assess the extent and severity of drought between 1982 and 2011. The normalised difference vegetation index (NDVI) was used to analyse the responses of five different vegetation types (forest, meadow steppe, typical steppe, desert steppe and desert) to drought. Our results show that during the last 30 years, the frequency and intensity of droughts have increased significantly, especially in summer and autumn. The greatest decline in NDVI in response to drought was observed in typical steppe and desert steppe vegetation types. Compared with other seasons, maximum decline in NDVI was observed in summer. In addition, we found that NDVI in the five vegetation types showed a lag time of 1–2 months from drought in the spring and summer. Ancillary soil moisture conditions influenced the drought response, with desert steppe showing a stronger lag effect to spring and summer drought than the other vegetation types. Our results show that drought explains a high proportion of changes in NDVI, and suggest that recent climate change has been an important factor affecting vegetation productivity in the area.

Sign in / Sign up

Export Citation Format

Share Document