Animal Census Research Articles

Use of antibiotics among small-scale cattle farmers in rural areas in Queretaro, Mexico

The inappropriate use of antibiotics in the livestock sector has been described as one of the causes of the emergence of antimicrobial resistance. Information on antibiotic use in small-scale farms is limited. Our objective was to identify patterns of antibiotic use in small-scale cattle farms in Queretaro, Mexico. Cross-sectional study with 50 small-scale cattle farmers from rural areas surveyed in the municipality of Tequisquiapan, Queretaro between May–October 2022. Convenience sampling, non-probabilistic, small-scale cattle farms were selected using respondent-driven sampling methodology. A face-to-face survey was applied, structured in five sections: i) small-scale cattle farmers´ profile, ii) characteristics of small-scale cattle farms, iii) antibiotic use, iv) antibiotic prescription, and v) inventory of stored antibiotics vials. The data collected were processed and analyzed. Ninety-two percent of the small-scale cattle farmers were male, with an age range of 23 to 88 years (median 58.5, IQR 49–64.5). Seventy-four percent of the small-scale cattle farmers had a basic level of schooling. The animal census consisted of 968 animals. A total of 142 stored antibacterial products from nine antibiotic classes were recorded: 34.5 % were penicillin, 19 % oxytetracycline, 13.4 % gentamicin, 9.8 % florfenicol, and 8.4 %enrofloxacin. About 50 % of the stored antibiotics have a "watch" classification in the WHO AWaRe tool. Seventy-eight percent of small-scale cattle farmers throw empty antibiotic vials in the trash. Our study showed that small-scale cattle farmers had an important use of third generation cephalosporins, tetracyclines, and fluoroquinolones; antibiotics considered “watch” by the WHO.

Characterization of the domestic canine and feline population in the city of Mineiros/GO, Brazil

The aim of the present study was to qualitatively and quantitatively characterize the domiciled population of dogs and cats in the city of Mineiros/GO. It is a basic, descriptive quali-quantitative research, through a population survey (animal census type). A total of 20,623 animals were counted, with 16,091 dogs and 4,532 cats. 43% were female dogs, 35.02% male dogs, 12.21% female cats, and 9.77% male cats. 73.89% of the population in this census is characterized as adult and 8.35% as elderly. 84.39% of dogs and cats are not neutered. Only 0.30% of animals have some form of identification (microchip or tattoo). 73.15% of animals were adopted, and 11.02% were born at home. 33.54% have supervised access, and in 27.91% of cases, access is unsupervised. 80.15% received some form of antiparasitic treatment in the last year. 58.57% of animals were vaccinated for rabies. 22.84% have never taken their pets to the veterinarian. The data found provide insights for the development of public policies aimed at controlling zoonoses, urban planning, and animal health in the municipality of Mineiros/GO.

Use of drone technology in animal health and management

In recent years, drone technology has become an important tool in animal health and management. In this study, the use of drone technology in animal health and management is analyzed and prominent applications are discussed. Drones have been observed to be useful in various fields such as monitoring the health status of animals, early diagnosis of diseases, monitoring grazing areas, search and rescue, animal census and inventory management. However, some challenges and limitations still need to be overcome for the effective application of drone technology. In conclusion, although the positive effects of drone technology on animal health and management are evident, further steps are needed to expand the application areas and to fully utilize the potential of the technology.

Anopheles blood meal sources and entomological indicators related to Plasmodium transmission in malaria endemic areas of Colombia

Malaria is an important public health problem, caused by Plasmodium parasites which are transmitted by female Anopheles mosquitoes that bite humans to obtain blood. The aim of this work was to identify the blood feeding sources of Anopheles female mosquitoes and calculate their entomological indices in relation to Plasmodium transmission. Mosquitoes were collected in malaria endemic localities of the Bajo Cauca and Pacific regions of Colombia using human landing catch and barrier screens, from 18:00 to 24:00 hr, in 2018–2021. Animal censuses within a radius of ∼250 m were carried out at each sampling site. A total of 2018 Anopheles specimens were collected and the most abundant species were Anopheles (Nys.) darlingi and Anopheles (Nys.) nuneztovari. The highest human biting rate was 77.5 bites per person per night (b/p/n) for An. nuneztovari in Córdoba-Pacific and 17.5 b/p/n for An. darlingi in Villa Grande-Bajo Cauca. Both species were active mainly in indoor unwalled rooms of the houses. Only An. nuneztovari from Córdoba-Pacific was infected with Plasmodium, with an entomological inoculation rate of 91.25 infective bites per year. Detection of blood feeding sources demonstrate that humans were the most common host, however, An. nuneztovari showed a preference for feeding on dogs and An. darlingi on pigs, dogs and Galliformes, rather than humans. These results contribute to entomological surveillance information and provide valuable data that can be used to tailor effective control interventions to minimize human-vector contact in these malaria endemic regions.

Community Engagement in the Diagnosis and Control of a Bovine Paralytic Rabies Outbreak in Two Rural Communities of Mexico

ABSTRACT Rabies is a neglected zoonosis with adverse public health effects. We describe the community engagement in containing a bovine paralytic rabies outbreak in two rural communities of Mexico. We carried out a participatory rapid appraisal using different community participation techniques for 2 weeks, including information sharing, community meetings, prioritization of activities, and training. In addition to the animal census and vaccination, necropsy and immunofluorescence tests were performed to diagnose rabies. Cattle mortality during the outbreak of bovine paralytic rabies was 4.5% (15/331); 1446 anti-rebies vacines were applied, directly benefiting 94 families. Members of two rural communities were trained. The continuous exchange of information among the stakeholders allowed us to inform, consult, involve, and empower community members. Community participation played an essential role in identifying a common problem, implementing activities to contain it, and successfully safeguarding public health, animal production, and food security.

Analysis of environmental dust in goat and sheep farms to assess Coxiella burnetii infection in a Q fever endemic area: Geographical distribution, relationship with human cases and genotypes.

Real-time PCR analysis of environmental samples (dust and aerosols) is an easy tool to investigate the presence of Coxiella burnetii in the farm environment. The aim of this study was to assess the distribution of C.burnetii DNA in dust collected inside animal premises from 272 small ruminant farms in Bizkaia (northern Spain), a region with recent reports of human Q fever cases and outbreaks. Within each farm, 5 samples of dust were collected from difference surfaces, and data on animal census, management procedures, characteristics of the premises and geographic location were collected. Real-time PCR analysis of the dust samples detected presence of C.burnetii DNA in 98 farms (36.0%), flock-prevalence being higher in sheep (38.9%) or mixed ovine-caprine production systems (36.8%), compared to goats (25.0%). Larger bacterial burdens were observed in mixed farms, compared to sheep (p<.05). Single nucleotide polymorphism (SNP) analysis identified 5 different genotypes, with SNP8 being the predominant genotype (73%), followed by SNP6 (11%), SNP2 (9%), SNP4 (5%) and SNP1 (2%). Proportion of farms where C.burnetii DNA was detected differed among the different agricultural counties, and a higher proportion of C.burnetii DNA positive farms was associated with the occurrence of recent human Q fever outbreaks at several geographical locations. Dust sampling in domestic ruminant farms coupled with real-time PCR to screen for the presence of C.burnetii and estimate bacterial load can be a useful tool to identify herds and regions with high prevalence, define priority actions and monitor the effect of control measures. If combined with molecular genotyping and spatial distribution maps, it can help to identify farm contamination sources and trace the origin of human outbreaks.

Factors Contributing to the Springbok Population Decline in the Kalahari, Botswana

Nationwide aerial animal censuses of Botswana between 1992 and 2012, conducted by the Department of Wildlife and National Parks, have highlighted a 71% decline in the national springbok (Antidorcas marsupialis) population and a contraction of their range. The reasons for this decline remain unknown. We investigated possible drivers of this decline in the southern Kalahari of Botswana. We assessed springbok resource selection levels, movement behaviour and seasonal and spatial effects on the juvenile:adult female ratio. Springbok displayed high levels of forage and habitat selection. Their dependency on pan habitats renders their distribution predictable, which could expose them to high levels of predation and poaching. Springbok moved shorter daily distances during the hot dry and longer distances during wet seasons. High temperatures during the hot dry season could limit movement and prevent exploitation of spatially and temporally heterogeneous resources. We recorded a ratio of 0.37 juvenile:1 adult female in the wet season months followed by a ratio decline to 0.10:1 in the subsequent cold dry season, indicating a low recruitment rate that could be contributing to the springbok population decline. Environmental changes and anthropogenic disturbances, exacerbated by climate change, will likely exert a negative influence on selective foragers like springbok.

Surveying Wild Animals from Satellites, Manned Aircraft and Unmanned Aerial Systems (UASs): A Review

This article reviews studies regarding wild animal surveys based on multiple platforms, including satellites, manned aircraft, and unmanned aircraft systems (UASs), and focuses on the data used, animal detection methods, and their accuracies. We also discuss the advantages and limitations of each type of remote sensing data and highlight some new research opportunities and challenges. Submeter very-high-resolution (VHR) spaceborne imagery has potential in modeling the population dynamics of large (&gt;0.6 m) wild animals at large spatial and temporal scales, but has difficulty discerning small (&lt;0.6 m) animals at the species level, although high-resolution commercial satellites, such as WorldView-3 and -4, have been able to collect images with a ground resolution of up to 0.31 m in panchromatic mode. This situation will not change unless the satellite image resolution is greatly improved in the future. Manned aerial surveys have long been employed to capture the centimeter-scale images required for animal censuses over large areas. However, such aerial surveys are costly to implement in small areas and can cause significant disturbances to wild animals because of their noise. In contrast, UAS surveys are seen as a safe, convenient and less expensive alternative to ground-based and conventional manned aerial surveys, but most UASs can cover only small areas. The proposed use of UAS imagery in combination with VHR satellite imagery would produce critical population data for large wild animal species and colonies over large areas. The development of software systems for automatically producing image mosaics and recognizing wild animals will further improve survey efficiency.

Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning

Knowledge over the number of animals in large wildlife reserves is a vital necessity for park rangers in their efforts to protect endangered species. Manual animal censuses are dangerous and expensive, hence Unmanned Aerial Vehicles (UAVs) with consumer level digital cameras are becoming a popular alternative tool to estimate livestock. Several works have been proposed that semi-automatically process UAV images to detect animals, of which some employ Convolutional Neural Networks (CNNs), a recent family of deep learning algorithms that proved very effective in object detection in large datasets from computer vision. However, the majority of works related to wildlife focuses only on small datasets (typically subsets of UAV campaigns), which might be detrimental when presented with the sheer scale of real study areas for large mammal census. Methods may yield thousands of false alarms in such cases. In this paper, we study how to scale CNNs to large wildlife census tasks and present a number of recommendations to train a CNN on a large UAV dataset. We further introduce novel evaluation protocols that are tailored to censuses and model suitability for subsequent human verification of detections. Using our recommendations, we are able to train a CNN reducing the number of false positives by an order of magnitude compared to previous state-of-the-art. Setting the requirements at 90% recall, our CNN allows to reduce the amount of data required for manual verification by three times, thus making it possible for rangers to screen all the data acquired efficiently and to detect almost all animals in the reserve automatically.

The effects of fires on plants and wildlife species diversity and soil physical and chemical properties at Aberdare Ranges, Kenya

Njeri WF, Githaiga JM, Mwala AK. 2018. The effects of fires on plant and wildlife species diversity and soil physical and chemical properties at Aberdare Ranges, Kenya. Asian J For 2: 25-38. This study was aimed to determine the effects of fires on species diversity (plants, animals, birds), and soil physical and chemical properties at the Aberdare Ranges forest, Kenya. Data were collected on five sites that experienced fires in 2002, 2009, 2012, 2013, and 2014 from both burnt and unburnt areas. Point Centered Quarter and quadrant methods were used for woody vegetation sampling and herbaceous vegetation sampling, respectively. Foot count was done for animal census and point count for birds. The data showed that the herbaceous vegetation in burnt sites had significantly higher species diversity than the unburnt sites in the areas that experienced fire before 2014. The fire had triggered the regeneration of the herbaceous plants. The burnt sites had a significantly higher percentage cover. The fire has an immediate adverse effect on the population of animals as demonstrated on the site consumed in 2014. No animal species was found on the site seven days after the fire when data was collected. The animal diversity was proportional to the vegetation density caused by the vegetation regeneration due to fires. All the burnt sites had fewer birds than the unburnt sites. Effects of fires were prominent in the upper layer of the soil for all the soil properties under study. Burning caused an increase in pH, potassium, organic carbon and cation exchange capacity. The study demonstrated that fires lead to an immediate adverse effect on vegetation, wildlife and soil chemical properties. Postfire management is necessary on sites that have recently experienced fires to rehabilitate them. Authorities responsible for the management of forests must ensure that people are kept out of those sites to allow vegetation to recover without interference. Reforestation can also be done on the burnt sites to increase plant and habitat for the wildlife.

An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates.

BackgroundThis paper presents the development of an agent-based model (ABM) to incorporate climatic drivers which affect tsetse fly (G. m. morsitans) population dynamics, and ultimately disease transmission. The model was used to gain a greater understanding of how tsetse populations fluctuate seasonally, and investigate any response observed in Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission, with a view to gaining a greater understanding of disease dynamics. Such an understanding is essential for the development of appropriate, well-targeted mitigation strategies in the future.MethodsThe ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The model incorporates climatic factors that affect pupal mortality, pupal development, birth rate, and death rate. In combination with fine scale demographic data such as ethnicity, age and gender for the human population in the region, as well as an animal census and a sample of daily routines, we create a detailed, plausible simulation model to explore tsetse population and disease transmission dynamics.ResultsThe seasonally-driven model suggests that the number of infections reported annually in the simulation is likely to be a reasonable representation of reality, taking into account the high levels of under-detection observed. Similar infection rates were observed in human (0.355 per 1000 person-years (SE = 0.013)), and cattle (0.281 per 1000 cattle-years (SE = 0.025)) populations, likely due to the sparsity of cattle close to the tsetse interface. The model suggests that immigrant tribes and school children are at greatest risk of infection, a result that derives from the bottom-up nature of the ABM and conditioning on multiple constraints. This result could not be inferred using alternative population-level modelling approaches.ConclusionsIn producing a model which models the tsetse population at a very fine resolution, we were able to analyse and evaluate specific elements of the output, such as pupal development and the progression of the teneral population, allowing the development of our understanding of the tsetse population as a whole. This is an important step in the production of a more accurate transmission model for rHAT which can, in turn, help us to gain a greater understanding of the transmission system as a whole.

Feeding Traits and Body Dimensions of Lime and Parkote Buffaloes Raised by Small-Scale Farms in Kaski, Nepal

Thirty farms that raised Lime or Parkote female buffaloes in Kaski were selected for the survey of animal census, feeding traits and body dimensions in the rainy season and the dry season. The average number per farm was 0.76 in Lime and 0.27 in Parkote. The average of age and parity was 8.2 years old and 4.4 in Lime, and 6.6 years old and 2.8 in Parkote, respectively. The mean dry matter (DM) supply of roughage, supplemental feed and total feed was higher in the dry season than in the rainy season (11.8 kg/head/day vs. 10.3 kg/head/day, 1.2 kg/head/day vs. 0.8 kg/head/day, 13.0 kg/head/day vs. 11.1 kg/head/day, respectively, P&lt;0.05). Although the average DM supply of roughage per body weight (BW) and total feed supply per BW had no significant differences between the seasons, the mean DM supply of supplemental feed per BW was higher in the dry season than in the rainy season (0.35% of BW vs. 0.22% of BW, P&lt;0.01). The BW, heart girth (HG) and hip born width (HW) of Parkote were higher than those of Lime (401.7 kg vs. 368.0 kg, 185.7 cm vs. 179.8 cm, 50.4 cm vs. 48.4 cm, respectively, P&lt;0.05). However, the body length, wither height (WH) and criss-cross height showed no significant differences between Lime and Parkote (127.4 cm and 129.8 cm, 118.7 cm and 119.5 cm, 118.0 cm and 119.4 cm, respectively). The BW estimation using body dimensions may play a significant role to know about the buffalo body condition. With the measured BW, HG, WH and HW in this survey, the formulae to estimate BW of Lime and Parkote buffaloes were established.

Node Density based Energy Conservation in Information Gathering Wireless Sensor Networks

As energy availability is insufficient to meet the global requirements, it is highly desirable to employ energy conservation measures in every social system that consume large amount of energy. Wireless Sensor Networks (WSN) consists of numerous number of nodes fitted with energy reserves to collect social information such as animal census and environmental monitoring. Density of nodes in clustered wireless sensor networks plays a vital role in determining the amount of energy consumed by the network. Higher density of nodes accumulated to a smaller area would result in cluster head being depleted of energy quickly. Similarly lower densities may lead to wasting of unused energy. In both the above cases, life-time of the wireless sensor network gets diminished alarmingly. In this work we put forward an efficient node density based cluster construction so that the energy expended by individual clusters are optimal and enhances overall network lifetime. Circular sensing region is sectored based on range of nodes to reach the base station. Density of nodes were computed for individual sectors by which if the density is high in the sense that there may be more number of unreachable nodes for the cluster head, then the sectors were further subdivided to make them optimally dense. This avoids the hot-spot problem in which information loss can be prevented and saves energy. We compared the energy consumption results of the proposed system Dynamic Unequal Clustered Routing (D-UCR) with other existing clustering protocols and found that this system conserves more energy thereby increases lifetime of the network.

Imagining wildlife: New technologies and animal censuses, maps and museums

By enabling the creation of networks of electronic sensors and human participants, new technologies have shaped the ways in which conservation-related organisations monitor wildlife. These networks enable the capture of data perceived as necessary to evidence conservation strategies and foster public support. We collected interview and archival data from UK-based conservation organisations with regard to their use of digital technologies for wildlife monitoring. As a conceptual device to examine these efforts, we used Benedict Anderson’s (1991) work on censuses, maps and museums as social instruments that enabled the imagining of communities. Through a critical application of this framework, the technologically-aided acquisition of wildlife data was shown to inform the new ways in which conservation organisations identify and quantify wildlife, conceptualise animal spaces, and curate conservation narratives. In so defining, delineating and displaying the non-human animal world with the backing of organisational authority, new technologies aid in the representational construction of animal censuses, maps and museums. In terms of practice, large amounts of new data can now be gathered and processed more cost-effectively. However, the use of technologies may also be the result of pressures on organisations to legitimise conservation by being seen as innovative and popular. Either way, human participants are relegated to supporting rather than participatory roles. At a more abstract level, the scale of surveillance associated with instrumentation can be read as an exercise of human dominance. Nonetheless, new technologies present conservation organisations with the means necessary for defending wildlife against exploitation.

Design of a New Energy Efficient L4 Leach Protocol based Visual Sensor Network for Forest Monitoring System

Current Forest area monitoring systems often rely on building regulations for maximum sensor nodes to maintaining proper logging. However, in many situations, there are sensor nodes that are used infrequently, and may be drained or detached from the network needlessly. Having knowledge regarding power consumption and being able to accurately predict usage patterns may allow significant energy-savings by intelligent control of the management systems. In this paper, we report on the deployment of a grid based wireless visual sensor network architecture for collecting data which may be used to detect unauthenticated logging, animal census, weather monitoring in a large multi-forest environment that estimates livelihood with an accuracy of 70%. The framework system consist improved L4 Leach protocol for promoting effective energy consumption. Using data collected from this framework, we can construct agent based models for predicting mobility patterns in the forest with support of our L4 Leach protocol. Our simulation indicates a 14% reduction in energy usage by having an optimal control strategy based on energy draining parameters estimates and usage patterns.

Methane emission and bioenergy potential from livestock manures in Mexico

Methane is an important greenhouse gas contributing to the global climate change leading to global warming and livestock accounts as one of the major sources of methane emission. Although, Intergovernmental Panel on Climate Change has developed guidelines to quantify emissions from enteric fermentation and manure management, it is recently reported that the National methane emission in U.S. is underestimated by a factor of 1.5–1.7. This study estimated the emission of methane in Mexico based on the animal census data from 2012. On an average, the total livestock in Mexico produced about 344 275 t·d−1 of animal manure. Further, a manure map of different states of Mexico was developed, and their potential methane emission was estimated. It is calculated that the total methane emission from enteric fermentation and manure is about 40 447.68 and 1307.04 Gg CO2 Eq., respectively. In the case of animal manures, beef and swine manures, respectively, contributed about 47% and 27% of total methane emission. Based on the data obtained, the bioenergy potential of Mexico by way of manure treatment using anaerobic digestion was calculated and is approximately 5910.35 TJ, which can generate 410.41 GWh of electricity and reduce emissions of methane by 2240.64 Gg CO2 Eq. The data clearly suggest that anaerobic digestion is a sustainable technology, not only for generation of renewable bioenergy but also for significant reduction in methane emission from animal manures.

Spatio-temporal patterns of leptospirosis in Thailand: is flooding a risk factor?

We studied the temporal and spatial patterns of leptospirosis, its association with flooding and animal census data in Thailand. Flood data from 2010 to 2012 were extracted from spatial information taken from satellite images. The incidence rate ratio (IRR) was used to determine the relationship between spatio-temporal flooding patterns and the number of human leptospirosis cases. In addition, the area of flood coverage, duration of waterlogging, time lags between flood events, and a number of potential animal reservoirs were considered in a sub-analysis. There was no significant temporal trend of leptospirosis over the study period. Statistical analysis showed an inconsistent relationship between IRR and flooding across years and regions. Spatially, leptospirosis occurred repeatedly and predominantly in northeastern Thailand. Our findings suggest that flooding is less influential in leptospirosis transmission than previously assumed. High incidence of the disease in the northeastern region is explained by the fact that agriculture and animal farming are important economic activities in this area. The periodic rise and fall of reported leptospirosis cases over time might be explained by seasonal exposure from rice farming activities performed during the rainy season when flood events often occur. We conclude that leptospirosis remains an occupational disease in Thailand.

Conducting animal censuses amongst abrupt topography; aGIS‐based alternative toDistance

AbstractManagement often bases decisions on estimates of animal density and population size. Aerial sampling is expensive whilst current ground methods, noticeablyDistancesampling, assume a single detection function for each habitat and that visibility in a given habitat type declines in a smooth, increasing manner with distance from the observer. If the visibility within a habitat varies widely or is suddenly cut off, as amongst abrupt topography, these assumptions are invalidated. We present an affordable, accessible and accurate method for conducting repeated annual censuses on large herbivores in such terrain. We used aGIShabitat‐based approach. Monthly, over a two year period, we conducted repeated road transects inIthalaGameReserve,SouthAfrica, usingGPSto record the geographic position of each sighting. These records (n = 8742) were then imported into aGISand overlaid onto an existing habitat‐typeGISlayer. With the sampled area thus defined as an irregular polygon in theGISencompassing all records, we calculated densities of each herbivore species by habitat type and extrapolated total population size estimates. Estimates of maximum population size for wildebeest and zebra correlated (±15%) with management's estimates based on aerial surveys, walked transects and experience. White rhino are individually counted in the reserve and our estimates (year 1: 52; year 2: 57) matched these known numbers (year 1: 50; year 2: 53). Our method also yielded realistic numbers for impala, but unrealistic numbers for kudu and warthog. OurGIS‐based census technique produced realistic maximum population estimates for abundant grazing and mixed‐feeder mesoherbivores and for scarce, but highly visible, megaherbivores, but not for cryptic species. With the increasing availability ofGISdata, the technique is recommended to those working in abrupt terrain frustrated by the inability of current ground census techniques, principallyDistancesampling, to produce realistic population estimates.

Online appendix 1:Vegetation change (1988–2010) in Camdeboo National Park (South Africa), using fixed-point photo monitoring: The role of herbivory and climate

Fixed-point photo monitoring supplemented by animal census data and climate monitoring potential has never been explored as a long-term monitoring tool for studying vegetation change in the arid and semi-arid national parks of South Africa. The long-term (1988–2010), fixed-point monitoring dataset developed for the Camdeboo National Park, therefore, provides an important opportunity to do this. Using a quantitative estimate of the change in vegetation and growth form cover in 1152 fixed-point photographs, as well as series of step-point vegetation surveys at each photo monitoring site, this study documented the extent of vegetation change in the park in response to key climate drivers, such as rainfall, as well as land use drivers such as herbivory by indigenous ungulates. We demonstrated the varied response of vegetation cover within three main growth forms (grasses, dwarf shrubs [&lt; 1 m] and tall shrubs [&gt; 1 m]) in three different vegetation units and landforms (slopes, plains, rivers) within the Camdeboo National Park since 1988. Sites within Albany Thicket and Dwarf Shrublands showed the least change in vegetation cover, whilst Azonal vegetation and Grassy Dwarf Shrublands were more dynamic. Abiotic factors such as drought and flooding, total annual rainfall and rainfall seasonality appeared to have the greatest influence on growth form cover as assessed from the fixed-point photographs. Herbivory appeared not to have had a noticeable impact on the vegetation of the Camdeboo National Park as far as could be determined from the rather coarse approach used in this analysis and herbivore densities remained relatively low over the study duration.Conservation implications: We provided an historical assessment of the pattern of vegetation and climatic trends that can help evaluate many of South African National Parks’ biodiversity monitoring programmes, especially relating to habitat change. It will help arid parks in assessing the trajectories of vegetation in response to herbivory, climate and management interventions.

Estimated net application of ammoniacal and organic N from manure, and potential for mitigating losses of ammonia in Canada

Manure nitrogen (N) includes what can be generalized as organic N, which includes undigested N from the feeds; ammoniacal and easily hydrolysable N, which includes urea and uric acid; and nitrate/nitrite species, which are the least abundant. From excretion to landspreading, the largest change in N concentration occurs because of volatilization of ammonia (NH3) from the ammoniacal and easily hydrolysable fraction. This process can be highly dependent on manure management, and some management strategies such as manure injection are largely designed to decrease NH3 loss. This paper utilizes recent models of NH3 emission from beef, dairy, swine and poultry production to estimate the net organic and ammoniacal N content of manure in Canadian Ecoregions before and after land spreading. Confinement versus grazing for beef is a major factor for overall net manure N application, and slurry versus solid manure is next most important. There are distinct differences among Ecoregions in the proportions of organic and ammoniacal N, so that generic assumptions are not appropriate. The estimates are mapped for all of Canada based on 2006 animal census. Several best management practices (BMPs) are evaluated using recent costing information (dollars per kg of NH3-N saved from emission). Relatively low-cost BMPs related to slurry manure applied nation-wide could save 16GgNH3-Nyear−1 for an estimated cost of $13M. Other low-cost BMPs could increase this to a saving of 79GgNH3-Nyear−1 or 26% of present emissions.