An estimated 68 million households in the United States owned at least one dog according to a 2024/25 pet owners survey, making them the most widely owned type of pet across the U.S. at this time. Cats and freshwater fish ranked in second and third places, with around 49 million and 10 million households owning such pets, respectively. Freshwater vs. salt water fish Freshwater fish spend most or all their lives in fresh water. Fresh water’s main difference to salt water is the level of salinity. Freshwater fish have a range of physiological adaptations to enable them to live in such conditions. As the statistic makes clear, Americans keep a large number of freshwater aquatic species at home as pets. American pet owners In 2023, around 66 percent of all households in the United States owned a pet. This is a decrease from 2020, but still around a 10 percent increase from 1988. It is no surprise that as more and more households own pets, pet industry expenditure has also witnessed steady growth. Expenditure reached over 136 billion U.S. dollars in 2022, almost a sixfold increase from 1998. The majority of pet product sales are still made in brick-and-mortar stores , despite the rise and evolution of e-commerce in the United States.

This dataset is about book series. It has 1 row and is filtered where the books is The people with the dogs. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Description

This dataset comprises a collection of images that are categorized into two main classes: cats and dogs. Each class further contains subcategories based on color, namely white and black.

The dataset includes the following structure:

Cats
  White: Images of cats with white fur.
  Black: Images of cats with black fur.
Dogs
  White: Images of dogs with white fur.
  Black: Images of dogs with black fur.

The dataset is well-structured and labeled, making it suitable for tasks like image classification. It is particularly useful for training and evaluating models designed to classify animal types (cats or dogs) and distinguish their colors (white or black). Contents

Cats (White): [Number of images: 400]
Cats (Black): [Number of images: 400]
Dogs (White): [Number of images: 400]
Dogs (Black): [Number of images: 400]

These images are sourced from diverse collections, ensuring a wide variety of cat and dog breeds across various backgrounds and environments. The dataset's labeling and diversity provide a robust foundation for developing and testing image classification models. Potential Use Cases

Image classification: Developing models capable of accurately distinguishing between cats and dogs based on their colors.
Color-based analysis: Identifying the prevalence or distinguishing features of different fur colors in cats and dogs.

The dataset's diversity, labeling, and balanced distribution among classes make it a valuable resource for both training and evaluating machine learning models, especially those focused on image classification tasks related to pets' color and type.

This is a data set of individuals in the United States that have pets. Data can be segmented and ordered based on State, City, Individual age, and gender. Data also includes first name, last name, email, address, zip code, and phone number. The dates the data was collected were from 07/01/2022 - 10/04/2022.

This dataset provides figures for the number of animals imported (from third countries) or consigned (from the European Union (EU)) into Great Britain in 2016. These datasets cover a number of livestock species. The layout and structure of the dataset is the same for each species. The data have been gathered from intra-community trade animal health certificates (ITAHC) for trade from the EU, and Community Veterinary Entry Document - Animals (CVED-A) for imports from third countries outside the EU that must accompany a consignment.

Structure: The datasets contain information for England, Wales and Scotland. The top row of the spreadsheet indicates which country the figures relate to. Please note: figures given in these datasets may vary to those produced by HMRC. This is because APHA's data is taken directly from certificates, while HMRC calculate statistical figures based on other sources.

Data Fields in Imports Datasets:

Certified Purpose:

The second row of the spreadsheet lists the purpose for import as indicated on the certificate. Animals can be imported/consigned for a number of reasons:-

Breeding: Have to comply with certain disease requirements and be resident in the place of origin for 30 days before export. They are consigned for purposes of breeding.

Fattening: Have to comply with certain disease requirements and be resident in the place of origin for 30 days before export. They are consigned for purposes of food production.

Slaughter: There are fewer animal health guarantees on animals consigned for slaughter as they must travel directly to slaughter.

Approved Bodies: Animals imported under Balai regulations can be exempted from rabies quarantine if imported from an approved premises.

Country: The left column indicates which country the animals were imported/consigned from. This may include an assembly centre where animals have been resident for no longer than 6 days.

Number of Consignments: Under each certified purpose, figures are given for the number of consignments received from the country listed into England, Wales or Scotland.

Number of Animals: Under each certified purpose, figures are given for the number of animals received from the country listed into England, Wales or Scotland.

Total Animals: The total number of animals imported/consigned from the country listed into England, Wales and Scotland, across all consignments.

Date: The dataset indicates the date as of which the data are correct. Attribution statement:

Dogs and cats number managed by the Barcelona Pet Animals Welfare Center (CAACB). The data show those who have been collected from the public road, rescued by its owner or adopted.

The data set is a extract consisting of information about cattle individuals registered with the Norwegian Food Safety Authority as of the specified date. Data in the Housing Register reflect what has been reported at all times.
There may be discrepancies between what appears in the Norwegian Food Safety Authority’s Housing Register and what is actually the case by direct observation. Deviations can be due to everything from misrepresentations, via delays, to inadequate reporting. The Norwegian Food Safety Authority cannot guarantee that all actors meet their reporting obligations.Nor can the Norwegian Food Safety Authority accept that all data has been correctly filled in by those who have reported.

See here for a detailed description of what should be reported and who is subject to the reporting obligation: HTTP://WWW.MATTILSYNET.NO/DYR_OG_DYREHOLD/PRODUKSJONSDYR/MERKING_OG_REGISTRERING_AV_PRODUKSJONSDYR/RAPPORTERING_TIL_HUSDYRREGISTERET_STORFE.4942 Legal basis for reporting:HTTPS://LOVDATA.NO/DOKUMENT/SF/FORSKRIFT/2010-07-09-1131

Explanation to the individual fields Original label: For Norwegian-born individuals, this is a combination of the first eight digits from the producer number (see Manufacturer No.) from where the animal is born and a four-digit individual number. Cattle from countries other than Norway may have a label of origin built up in a different way.

• Country of origin:**

Name of the country of origin of the individual Individ brand: This is a combination of either 1) the first eight digits of the producer number (see this) from where the animal is born and a four-digit individual number, or 2) a seven-digit animal husbandry ID and a five-digit individual number. If the individual is born in Norway, the individual mark is identical to that of origin.

Individ status:

Examples of status are &Complete &, &Dyr transferred. Lack of report from buyer &, &Dyr transferred. Lack of report from the seller., "Dyr slaughtered. Lacks report from the slaughterhouse., "Dyr reported transferred from the live animal dealer/slaquot.Lacks report from buyer and seller. Lack of report from animal husbandry.

Individuals have a status that depends on the events that have been reported.Many events are individual events, which means that they are reported by only one party using one event. An example of this is 'Newborn animals marked the first time. These events have status complete and either cause an animal to be created with status complete or if the animal already exists, the animal’s status is not affected.

Events involving displacement require two, three, or possibly four events.This is because all interested parties should report both when an animal enters the animal husbandry and when it exits the animal husbandry. This applies to movement between animal husbandry, with or without animal dealers, and transfer to slaughterhouse and slaughter.

All events relating to transfer between animal husbandry or slaughter require that the status of the animal is complete before the first event in the movement can be recorded. An individual’s status can be representative only at the moment the data has been extracted from the Housing Register.That an individual appears as “complete »”; or with ‘laquo’; Missing reports & may result in correctness at the moment the data was extracted, but perhaps not immediately afterwards.

Born:*

Date of birth in the format dd.mm.ååå

Gender:*

The gender of the individual is either ‘quick’/ku »for female or & &Okse » for the masculine Rase code:

Consists of the text “LANDDYR$” + a number code For explanation of the number code see http://www.mattilsynet.no/integrasjonsstotte/KODEVERK_RASETYPE_no.html

Race:

Race is the term for race code & in plain text.

Rase designation:

Here the breed can appear to the father (the first 16 digits) and the mother (the last 16 digits respectively). There are two and two digits in pairs that make up the code. For an overview of the two-digit codes see here: HTTP://WWW.MATTILSYNET.NO/INTEGRASJONSSTOTTE/KODEVERK_RASETYPE_I_TEXTCODE_NO.HTML

Mormark:

If the individual’s mother was born in Norway, the mother’s mark is built up in the same way as the individual mark.

Manufacturer:

Contains 10-digit manufacturer number. Construction of producer number: Municipal number 4 digits + farm number 4 digits + a sequential number 2 digits.

Company No.:

This corresponds to what is referred to in the Brønnøysund Register as ‘Organisation Number & Raquo’.

Calving date:

This is the last calving date recorded in the Animal Register of an individual.

Calving as such is not a notifiable event. It is the event of a newborn calf marked for the first time that is subject to notification. Information about the date of birth and the mother’s mark of origin are among the mandatory

🇬🇧 영국 English This dataset provides figures for the number of animals imported (from third countries) or consigned (from the European Union (EU)) into Great Britain in 2016. These datasets cover a number of livestock species. The layout and structure of the dataset is the same for each species. The data have been gathered from intra-community trade animal health certificates (ITAHC) for trade from the EU, and Community Veterinary Entry Document - Animals (CVED-A) for imports from third countries outside the EU that must accompany a consignment. Structure: The datasets contain information for England, Wales and Scotland. The top row of the spreadsheet indicates which country the figures relate to. Please note: figures given in these datasets may vary to those produced by HMRC. This is because APHA's data is taken directly from certificates, while HMRC calculate statistical figures based on other sources. Data Fields in Imports Datasets: Certified Purpose: The second row of the spreadsheet lists the purpose for import as indicated on the certificate. Animals can be imported/consigned for a number of reasons:- Breeding: Have to comply with certain disease requirements and be resident in the place of origin for 30 days before export. They are consigned for purposes of breeding. Fattening: Have to comply with certain disease requirements and be resident in the place of origin for 30 days before export. They are consigned for purposes of food production. Slaughter: There are fewer animal health guarantees on animals consigned for slaughter as they must travel directly to slaughter. Approved Bodies: Animals imported under Balai regulations can be exempted from rabies quarantine if imported from an approved premises. Country: The left column indicates which country the animals were imported/consigned from. This may include an assembly centre where animals have been resident for no longer than 6 days. Number of Consignments: Under each certified purpose, figures are given for the number of consignments received from the country listed into England, Wales or Scotland. Number of Animals: Under each certified purpose, figures are given for the number of animals received from the country listed into England, Wales or Scotland. Total Animals: The total number of animals imported/consigned from the country listed into England, Wales and Scotland, across all consignments. Date: The dataset indicates the date as of which the data are correct. Attribution statement:

Animal Services Provides for the care and control of animals in the Louisville Metro area, including pet licensing and pet adoption. Data Dictionary: violation number - Number automatically generated when a citation, civil penalty or violation is stored in Chameleon violation type CIT CRUEL Uniform Citation where 525.130 has been charged CIT DD/PDD Uniform Citation where 91.150 or 91.152 has been charged CITATION Uniform Citation CITE71 Uniform Citation issued in the field for someone contesting the requirements of 91.071 CIVIL PEN Civil Penalty CRIM COMP Criminal Complaint V71/CITE When a offender does not comply with a VIOL 71 and a CITATION is issued in its place for noncompliance. V71/CP When a offender does not comply with a VIOL 71 and a CIVIL PEN is issued in its place for noncompliance. V71/CRIM When a offender does not comply with a VIOL 71 and a CRIM COMP is issued in its place for noncompliance. VET Violation Notice issued for vet care or grooming needs VET/CRIM When a offender does not comply with a VET and a CRIM COMP is issued in its place for noncompliance. VIOL 71 Violation Notice issued when an animal has been impounded in the field and returned to it's owner. Charges can include 91.002, 91.020, 91.071. VIOL CTER Violation Notice issued when a pet that was impounded at the shelter is redeemed by its owner. Charges can include 91.002, 91.020, 91.071. VIOL NOTIC Violation Notice VIOL RED Violation Notice issued when a pet that was impounded at the shelter is redeemed by its owner but a vet is not present to complete the requirements of 91.071. Owner is given time to complete the requirements. Charges can include 91.002, 91.020, 91.071. VIOL/CP When a offender does not comply with a VIOL NOTIC and a CIVIL PEN is issued in its place for noncompliance. VIOL/CRIM When a offender does not comply with a VIOL NOTIC, or WARNING and a CRIM COMP is issued in its place for noncompliance. VN/CITE When a offender does not comply with a VIOL NOTIC and a CITATION is issued in its place for noncompliance. VOTC/CITE When an offender is issued a VIOL CTER but contest the requirements of 91.071 so a CITATION is issued. VOTC/CP When a offender does not comply with a VIOL CTER and a CIVIL PEN is issued in its place for noncompliance. VOTC/CRIM When a offender does not comply with a VIOL CTER and a CRIM COMP is issued in its place for noncompliance. VRED/CITE When a offender does not comply with a VIOL RED and a CITATION is issued in its place for noncompliance. VRED/CP When a offender does not comply with a VIOL RED and a CIVIL PEN is issued in its place for noncompliance. VRED/CRIM When a offender does not comply with a VIOL RED and a CRIM COMP is issued in its place for noncompliance. WARN/CITE When a offender does not comply with a WARNING or VET and a CITATION is issued in its place for noncompliance. WARN/CP When a offender does not comply with a WARNING and a CIVIL PEN is issued in its place for noncompliance. WARNING Violation Notice where no fee is charged or owner is required to comply with a particular requirement such as fixing a fence, getting a dog house, etc. form - Unique number on each citation, civil penalty or violation used to identify the particular form violation date - Date the citation, civil penalty or violation was issued case number - Activity number associated with the citation and the sequence number associated with the run. This number shows how many times an officer has worked that particular run case type ALLEY CAT TRAP A call where an animal control officer and a member of Alley Cat Advocates works together to trap cats for TNR. ASSIST Any call where assistance is needed from an animal control officer. ASSIST ACO Any call where an animal control officer requires assistance from another animal control officer. ASSIST FIRE Any call where Fire requires assistance from the animal control officer. ASSIST OTHER Any call where another emergency responder or government employee requires assistance from the animal control officer. ASSIST POLICE Any call where Police requires assistance from the animal control officer. ASSIST SHERIFF Any call where an sheriff requires assistance from the animal control officer. CONVERT A call created when a officer is converting a violation notice to a citation or a civil penalty for noncompliance. CONVERT CITATION A call created when a officer is converting a violation notice to a citation or a civil penalty for noncompliance. INVESTIGAT Any complaint where an investigation is needed that does not fit into a category already in use. INVESTIGAT # POULTRY Any complaint where the caller states the owner has more poultry than allowed by the ordinance. INVESTIGAT ABAN Any call for an owner leaving an animal for a period in excess of 24 hours, without the animal's owner or the owners’ designated caretaker providing all provisions of necessities. INVESTIGAT ABUSE A cruelty/abuse/neglect situation where the health and safety of an animal is in jeopardy because of exposure to extreme weather, or other neglect/abuse factors. Examples include reports of beating, hitting, kicking, burning an animal, dog currently suffering from injury or illness and could die if treatment not provided INVESTIGAT ANI ATACK Any call for an attack on an animal by another animal. INVESTIGAT BARKLETTER Any barking complaint where the caller wishes to remain anonymous. INVESTIGAT BITE Any call for a bite from an animal to a person INVESTIGAT BITEF This is used when an animal control officer is following up on a bite investigation. INVESTIGAT CHAINING Any complaint of a dog tethered illegally. The dispatcher must verify with the caller that the dog is not in distress and has necessities such as water, shelter etc. INVESTIGAT CROWLET Any crowing complaint where the caller wishes to remain anonymous. INVESTIGAT DOGFIGHT Any call where a person or persons in engaged in fighting dogs or have fought dogs in the past. INVESTIGAT ENCLOSURE Any complaint made due to an animal not being confined securely in an enclosure. Examples being holes in fences, jumping a fence. INVESTIGAT FECES LET Any complaint concerning a citizen not picking up after their animal where the caller wishes to remain anonymous. INVESTIGAT FOLLOW UP This call is used when an animal control officer is following up on an investigation. INVESTIGAT LIC LETTER Any complaint to check license not reported by the Health Dept. or supervisor. INVESTIGAT NEGLI A cruelty/abuse/neglect situation where the health and safety of an animal is in jeopardy because of exposure to extreme weather, or other neglect/abuse factors. Examples include reports of failure to provide vet care, thin animal, no shelter , no water/food. INVESTIGAT OTHER Any complaint where an investigation is needed that does not fit into a category already in use. INVESTIGAT PET IN CAR Any complaint of an animal left in a car INVESTIGAT TNR Any complaint of stray unowned cats MAS A run made to meet a caller at Metro Animal Services MAS TRAP Calls made by animal control officers when they are trapping cats for TNR. NUISANCE BARK Any complaint on a barking dog where the complainant wants to be contacted and give a statement NUISANCE CROWING Any crowing complaint where the complainant wants to be contacted and give a statement. NUISANCE OTHER Any complaint other than barking, crowing, and restraint issues where the complainant wants to be contacted and give a statement. NUISANCE RESTRAINT Any restraint complaint where the complainant wants to be contacted and give a statement. OTHER This category is used for a variety of calls including picking up tags, speaking at events, calls that do not have a category already OWNED Any call for an owned animal that does not fit in one of the other categories. OWNED AGGRESSIVE Any aggressive loose animal that is owned. Aggressive behavior includes growling, showing teeth, lunging forward or charging at the person or other animal. PERMIT INS A call for an animal control officer to conduct a permit inspection at a particular location. RESCUE DOMESTIC A call for an domestic animal in distress, typically dogs and cats. These calls include dogs in lakes, animals in sewers or drains, cats in car engines, etc. RESCUE LIVESTOCK A call for livestock in distress. This includes cattle stuck in ponds, cattle near a busy roadway, etc. RESCUE OTHER A call for an domestic animal in distress, typically any other domestic animal or any call that does not fit in the other categories. RESCUE WILDLIFE This call is typically used for a bat in someone's home or business. STRAY Any call for an animal that is stray that does not fit a specific category STRAY AGGRS Any aggressive loose animal that is stray. Aggressive behavior includes growling, showing teeth, lunging forward or charging at the person or other animal. STRAY CONF Any call for an unowned, non-aggressive animal, excluding a bat, confined by a citizen that is not in a trap. STRAY INJURED Any call for a sick/injured animal that is life threatening i.e. – vomiting or defecating blood, trouble breathing, unable to move, hit by a car, visible wounds, bleeding profusely, unable to stand. This includes sick or injured community cats. STRAY POSS OWNED Any animal running loose that has an owner or possible owner. This is used when the caller does not want to give a statement or be contacted. STRAY ROAM Any animal running loose that has no known owner, excluding cats. Will be closed out after 72 hours if no further calls and no call back number. STRAY SICK Any call for a sick/injured animal that is life threatening i.e. – vomiting or defecating blood, trouble breathing, unable to move, hit by a car, visible wounds, bleeding profusely, unable to stand. This includes sick or injured community cats. STRAY TRAP Any call for a dog or cat, excluding a bat, confined in a trap. This includes checking a trap set by LMAS daily. SURRENDER A call to pick up an owned animal that the owner wants to surrender. SURRENDER

The data presented here comprise a catalogue of 11633 trap camera images obtained during the period November 2020 to March 2021; this period is described within the dataset as setup 2. Following the explosion at the Chernobyl nuclear power plant in April 1986 an approximately 5000 km2 exclusion zone surrounding the plant was created; people and farm animals were subsequently evacuated from the area. In April 2020 there were severe wildfires within the Ukrainian part of the exclusion zone (2600 km2) where approximately 870 km2 was burnt. The NERC funded CHAR project conducted a study which involved placing motion activated digital trap cameras at three sites (each covering an area of 80 km2) within the Ukrainian exclusion zone from June 2020 - August 2021 to assess large mammal activity following the fire. Thirteen cameras were randomly located at each site; all camera deployment locations had been used in a previous study 2014-2015 (https://www.ceh.ac.uk/our-science/projects/chernobyl-images). All the images obtained during November 2020-March 2021 (setup 2) are included as part of the dataset with the exception of those containing people, vehicles or members of the CHAR research team setting up and servicing the cameras; these images (n= 692) have been catalogued but the images are not included in the dataset to protect privacy. Information on camera deployment periods, site characteristics and descriptions of each camera location (e.g. geographic coordinates, estimates of ambient dose rate, description of animal trails or tracks and the extent of fire damage in vicinity of where the camera is mounted) have also been included as part of the dataset. Staff from the Chornobyl Center for Nuclear Safety deployed, maintained and downloaded images and associated metadata from the trap cameras in March 2021. Using the images and associated metadata, the image catalogue was populated by Chornobyl Center staff with: species identified in image, number of animals visible in image, the number of triggering events (cumulative by camera) and any relevant notes; the image catalogue (MSExcel) and trap camera images (.jpeg) were subsequently supplied to UKCEH. Site descriptions and camera information were provided by Chornobyl Center staff and supplied to UKCEH by staff as MSExcel files; the same person from the Chornobyl Center recorded all descriptive parameters. The information provided includes: site field notes, habitat descriptions, camera location (latitude and longitude, WGS84), estimates of ambient dose rate (µSv h-1), camera deployment dates and the number of days each camera was deployed. The data and images were quality checked by a member of UKCEH staff and any queries were investigated and amended where necessary. This dataset contains data related to setup 2; for data related to setup 1 see: https://doi.org/10.5285/9bd7754d-ea87-4b35-bec1-f39d5cc76db6

This dataset provides an overview of the decline in the BSE (Bovine Spongiform Encephalopathy) epidemic in reported cases by comparing full calendar years, and including number restricted, percent reduction from the previous year and the same for confirmed cases. The dataset includes the fields: Year; Restricted (number of animals where movement restrictions have been imposed); Percent reduction year on year of those restricted (i.e 2011vs2010, 2010vs2009, 2009vs2008 etc.); Of which confirmed (number of cases confirmed positive for BSE); Percent reduction year on year of those confirmed ( (i.e 2011vs2010, 2010vs2009, 2009vs2008 etc.). This table does not include other BSE confirmations as part of survey and/or private submissions. Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk. Attribution statement: ©Crown Copyright, APHA 2016

This table contains data on land use, arable farming, horticulture, grassland, grazing livestock and housed animals, at regional level, by general farm type.

The figures in this table are derived from the agricultural census. Data collection for the agricultural census is part of a combined data collection for a.o. agricultural policy use and enforcement of the manure law.

Regional breakdown is based on the main location of the holding. Due to this the region where activities (crops, animals) are allocated may differ from the location where these activities actually occur.

The agricultural census is also used as the basis for the European Farm Structure Survey (FSS). Data from the agricultural census do not fully coincide with the FSS. In the FSS years (2000, 2003, 2005, 2007 and 2010) additional information was collected to meet the requirements of the FSS.

Reference date for livestock is 1 April and for crops 15 May.

In 2022, equidae are not part of the Agricultural Census. This affects the farm type and the total number of farms in the Agricultural Census. Farms with horses, ponies and donkeys that were previously classified as ‘specialist grazing livestock' could be classified, according to their dominant activity, as another farm type in 2022.

From 2020 onwards, the SO2017, based on the years 2015 to 2019, will apply (see also the explanation for SO: Standard Output).

From 2018 onwards the number of calves for fattening, pigs for fattening, chicken and turkey are adjusted in the case of temporary breaks in the production cycle (e.g. sanitary cleaning). The agricultural census is a structural survey, in which adjustment for temporary breaks in the production cycle is a.o. relevant for the calculation of the economic size of the holding, and its farm type. In the livestock surveys the number of animals on the reference day is relevant, therefore no adjustment for temporary breaks in the production cycle are made. This means that the number of animals in the tables of the agricultural census may differ from those in the livestock tables (see ‘links to relevant tables and relevant articles).

From 2017 onwards, animal numbers are increasingly derived from I&R registers (Identification and Registration of animals), instead of by means of the combined data collection. The I&R registers are the responsibility of RVO (Netherlands Enterprise Agency). Since 2017, cattle numbers are derived from I&R cattle, and from 2018 sheep, goats and poultry are also derived from the relevant I&R registers. The registration of cattle, sheep and goats takes place directly at RVO. Poultry data is collected via the designated database Poultry Information System Poultry (KIP) from Avined. Avined is a branch organization for the egg and poultry meat sectors. Avined passes the data on to the central database of RVO. Due to the transition to the use of I&R registers, a change in classification will occur for sheep and goats from 2018 onwards.

Since 2016, information of the Dutch Business Register is used to define the agricultural census. Registration in the Business Register with an agricultural standard industrial classification code (SIC), related to NACE/ISIC, (in Dutch SBI: ‘Standaard BedrijfsIndeling’) is leading to determine whether there is an agricultural holding. This aligns the agricultural census as closely as possible to the statistical regulations of Eurostat and the (Dutch) implementation of the definition of 'active farmer' as described in the common agricultural policy.

The definition of the agricultural census based on information from the Dutch Business Register mainly affects the number of holdings, a clear deviation of the trend occurs. The impact on areas (except for other land and rough grazing) and the number of animals (except for sheep, horses and ponies) is limited. This is mainly due to the holdings that are excluded as a result of the new delimitation of agricultural holdings (such as equestrian centres, city farms and organisations in nature management).

In 2011 there were changes in geographic assignment of holdings with a foreign main seat. This may influence regional figures, mainly in border regions.

Until 2010 the economic size of agricultural holdings was expressed in Dutch size units (in Dutch NGE: 'Nederlandse Grootte Eenheid'). From 2010 onwards this has become Standard Output (SO). This means that the threshold for holdings in the agricultural census has changed from 3 NGE to 3000 euro SO. For comparable time series the figures for 2000 up to and including 2009 have been recalculated, based on SO coefficients and SO typology. The latest update took place in 2016.

Data available from: 2000

Status of the figures: The figures are final.

Changes as of March 28, 2025: the final figures for 2024 have been added.

When will new figures be published? According to regular planning provisional figures are published in November and the definite figures will follow in March of the following year.

The Indonesian island province of Bali experienced its first rabies incursion in 2008. Mass vaccination of the dog population has proven effective and rabies cases in dogs and people have decreased, however the virus is still circulating among the dog population. Vaccination coverage must be maintained until rabies elimination. Increasing efficiency and effectiveness of vaccination campaigns is therefore desired. Community engagement leading to preventative health actions by community members can reduce disease incidence and costs of control. Here we evaluate 2 years of a novel community-based dog welfare and rabies control project (Program Dharma) in the Sanur sub-district. The project engaged the services of people living in the project area with an interest or experience in dogs or community health services. These people spoke with owners within their own community about dog welfare and health, monitored owned and unowned dogs and increased owner and carer efforts to access vaccination and further veterinary services. The evaluation focused on a sample of dogs whose owners had been regularly engaged with project. Vaccination coverage was increased and there were no dog or human rabies cases reported in the project area; the percentage of the dogs that had never been vaccinated was reduced by an average 28.3% (baseline unvaccinated 41–49%, post-project unvaccinated 11–19%). The welfare of dogs improved from an average of 20.7% of dogs with visible welfare problems at baseline to 2.7% after project implementation. Roaming dog density observed on street surveys also decreased in all project areas (24–47% reduction dependent on desa). A participatory evaluation event with a sample of Program Dharma community-based agents highlighted several additional successes, including that the community appeared to welcome and value their services and were beginning to support the cost of project activities. Conversely, challenges included identifying dogs in the database during revisits, sustaining the costs of community member time spent working on Program Dharma activities and the costs of veterinary care, whilst avoiding dependency of owners on free veterinary services. The benefits revealed by the evaluation were judged to be sufficient to extend Program Dharma to new areas, whilst evolving activities to resolve challenges.

Crossmodal correspondences are intuitively held relationships between non-redundant features of a stimulus, such as auditory pitch and visual illumination. While a number of correspondences have been identified in humans to date (e.g. high pitch is intuitively felt to be luminant, angular, and elevated in space), their evolutionary and developmental origins remain unclear. Here we investigated the existence of audio-visual crossmodal correspondences in domestic dogs, and specifically, the known human correspondence in which high auditory pitch is associated with elevated spatial position. In an audio-visual attention task, we found that dogs engaged more with audio-visual stimuli that were congruent with human intuitions (high auditory pitch paired with a spatially elevated visual stimulus) compared to incongruent (low pitch paired with elevated visual stimulus). This result suggests that crossmodal correspondences are not a uniquely human or primate phenomenon, and that they cannot easily be dismissed as merely lexical conventions (i.e., matching ‘high’ pitch with ‘high’ elevation).

Methods Data was collected by video recording the dogs' reactions during the presentation of audio-visual stimuli. Each row in the data set represents a trial (one 8 second audio-visual animation presented to a dog). The presentations were projected onto a wall with an overhead projector (Eiki Brilliant Projector LC-XB28) and a MacBook Pro laptop. The sound was played using two Behringer Europort MPA40BT speakers placed adjacent and on both sides of the wall onto which the animations were projected. An audio-visual animation of moving insects was projected in between each trial as a means of attracting the dogs’ attention to the screen. Dogs’ behaviour was recorded using a SONY (Handycam XAVC 5 AVCHD Progressive) camera placed on a tripod in front and to the left of the dog. There was another camera (SONY Handycam AVCHD Progressive) placed in front and to the right of the dog which was sending a live feed to a screen monitor placed behind the dog and owner. Data was coded using Gamebreaker 10 by two independent raters, blind to the condition.

A within subject design was used with each dog seeing both the congruent and incongruent version of the audio-visual stimulus once. We compared congruent and incongruent conditions, with three dependent measures: the duration-of-looking at the stimulus (time in seconds each dog spent with its gaze focused on the stimulus), time-spent-tracing the stimulus (evidenced by the amount of time in seconds each dog spent moving its head up and down to follow the stimulus) and the percentage of time the dog spent tracing, out of the total time he/she spent looking; i.e., (time-spent-tracing/ duration-of-looking) x100. A linear mixed model was run using SPSS v.25 (SPSS Inc., Chicago, IL, USA) and the differences in means were considered significant at an alpha level of 0.05.

Data sets containing information from applications for production subsidies to agricultural enterprises in the application period 2024. The information was retrieved at the end of October 2024. For each enterprise, the organisation number, name, municipality number and number of animals and decares listed in the individual code are shown in the application form. The application process of 2024 consists of two parts: Part 1 – March: O Contains application information on the number of animals on the date of 1 March. Part 2 – October: O Contains application information on the number of animals by the date of 1 October (including conservation livestock breeds), grazing animals, grass and potato production, and predisposed areas and which crops are grown on the land. Please note that information on animals collected from pastures after 15 October and on vegetable and potato production traded after 15 October can be retro-registered until 10 January, so that final figures must be expected to be somewhat higher than those published here. Grants for pigs, chickens offal, geese, turkeys and ducks are given for the number of animals slaughtered during the year of application, and are given on the basis of the number of slaughtered animals reported from the slaughterhouses to the Delivery Database. The number of slaughtered animals is not included in this dataset, but will be included in datasets published in March. The data set published in March will also include subsidy amounts.

This table contains data on the number of cattle, sheep, goats, chickens, turkeys, ducks for slaughter and pigs on Dutch agricultural holdings. The number of animals is determined on April 1st and December1st . The number of animals can differ from those in the tables of the agricultural census (see ‘links to relevant tables and relevant articles). In the agricultural census the number of veal calves, fattening pigs, chicken and turkey are, from 2018 onwards, adjusted in the case of temporary breaks in the production cycle (e.g. sanitary cleaning). The agricultural census is a structural survey, in which adjustment for temporary breaks in the production cycle is a.o. relevant for the calculation of the economic size of the holding, and its farm type. In the livestock surveys the number of animals on the reference day is relevant, therefore no adjustment for temporary breaks in the production cycle are made.

Data available from: 1 April 2018.

Status of the figures: New figures on the number of animals are first published as 'provisional' and when more complete figures of the Agricultural Census become available, they are adjusted accordingly from provisional to 'definitive'.

Changes as of May 14, 2025: The final figures for April 2024 and December 2024 have been added.

When will new figures be published? The provisional figures of April are published in September. The provisional figures of December are published in February of the subsequent year. The definite figures of April are published in May of the subsequent year and the definite figures of December are published in September of the subsequent year.

This dashboard shows aggregated statistics from the Manitoba Animal Welfare Program on the number of cases reported, inspections conducted, and non-compliances to The Animal Care Act. This dashboard illustrates aggregated statistics from the Manitoba Animal Welfare Program on the number of cases reported, the number of inspections conducted and the number of non-compliances to The Animal Care Act. The Manitoba government’s Animal Health and Welfare Branch, under the direction of the Chief Veterinary Officer (CVO), is responsible for enforcing The Animal Care Act, Manitoba’s animal welfare legislation. This act is designed to protect the welfare of all animals under possession, care or control of people, including livestock, companion animals and non-domestic species, such as reptiles and pocket pets. Each variable, the number of cases reported, number of inspections conducted, and number of non-compliances found, is represented by a line on the graph. The count for each variable is shown by year, from 2016 to present, to visualize the program trends. Data from this dashboard will be updated on a quarterly basis and all data comes from the Provincial Animal Welfare Database. The data table used for this dashboard is Manitoba Animal Welfare Program - Trends. There is one chart on this dashboard that breaks down the number of cases reported, the number of inspections conducted and the number of non-compliances to The Animal Care Act by year, beginning in 2016, to the current quarter. For more information, please refer to the Animal Welfare Main Page.

Datasets necessary to reproduce the following Figures:

Figure 1. OrV accumulation dynamics. (a) Log₁₀ RNA2 genomes/ng of total RNA measured every 2 h during 24 hpi. The abscissa shows hph. The first molting period (M1) is highlighted by a pink rectangle, and the second molting period (M2) by a lime green one. Blue lines and symbols represent the viral load for nematodes inoculated at 0 hph while green ones represent those inoculated at 6 hph. (b) Same data as in (a) but rescaled according to hpi.

Figure 2. Identification of infected cells and viral presence in the intestinal lumen. (b) Percentage of nematodes with smiFISH signal. Nematodes inoculated at 0 hph are shown in blue, and nematodes inoculated at 6 hph are shown in green. Points represent biological replicates (each one corresponding to a plate of animals, each plate containing 40 animals). Mean is represented as a horizontal line, and standard deviation (SD) as a vertical line. (c) Percentage of animals according to the number of infected intestinal cells. Nematodes inoculated at 0 hph are shown in blue, and nematodes inoculated at 6 hph are shown in green. Error bars represent ±95% confidence interval (CI). (d) Percentage of smiFISH signal on cells (in green), lumen (in purple), or both (in yellow), in 0 hph and 6 hph inoculated nematodes. Error bars represent ±95% CI. On this experiment, four replicates were done for each condition, 40 animals per replicate.

Figure 3. Impact of viral infection on the expression of development-related genes. (c) Expression profiles of developmental-related genes let-7, lin-42 and nhr-23 along time. Expression profiles of control animals are shown in purple circles and lines, while blue triangles and lines indicate infected animals. Shadowed areas represent ±1 SE. Three replicates per timepoint were done.

Figure 4. Impact of viral infection on C. elegans development. (c) Duration of intermolt stages (I1 - I4). (d) Duration of molts (M1 - M4). (e) Time from the last molt (M4) until hatching of progeny. (f) Time from the first intermolt period (I1) until hatching of progeny. In panels (c) - (f) mean value are represented by black horizontal bars. Control nematodes are represented by purple circles while infected ones are represented by blue triangles.

This Open Data Record is comprised of datasets that document human-wildlife coexistence incidents and response actions by Parks Canada Agency from 2010 to 2023. A human-wildlife coexistence (HWC) “incident” is any potential conflict situation between people and wildlife that was assigned to Parks Canada staff to manage to help ensure the safety and wellbeing of people and wildlife. The vast majority of HWC incidents are minor and staff are able to manage them safely with low risk to people, however, a small subset of the dataset is comprised of more hazardous incidents between people and wildlife that can potentially result in injury or death of either wildlife or people. HWC incident data inform Parks Canada Agency policies, programs, and operations, and enable evaluation of HWC patterns to help Parks Canada ensure safe and enjoyable visitor experiences while conserving wildlife and integrity of ecosystems across our national system of protected heritage areas. For any single HWC incident, there may be multiple management actions taken or multiple animals involved, and therefore this Open Data Record includes separate datasets for incidents, responses, animals involved, and human activities. These four datasets include many shared fields, including a unique alphanumeric “Incident Number” that can be used to look-up records between the tables or to join the tables in a relational database. There are also thirteen derived datasets provided to summarize the total number of incidents, animal species involved, animals killed (by human causes), aggressive encounters, unnatural attractants, and response actions taken. Please note: these datasets include some incidents that Parks Canada staff were involved outside of park boundaries on surrounding lands or waters. All HWC incident data remain subject to ongoing revisions as more information comes available or for quality control purposes. All protected, personal, private or confidential information has been removed from these datasets.

ObjectivesSeveral studies have indicated that early pet keeping could protect the infant from later allergy development. Here, we investigate if there is a dose-dependent association between cat- and dog-keeping during the first year of life and subsequent allergy development.MethodsTwo cohorts were investigated: a cross-sectional questionnaire-based study of 7- to 8-year-old children (N = 1029) from Mölndal and Kiruna, and a birth-cohort of children from the Västra Götaland county clinically evaluated for asthma and allergy by paediatricians up to the age of 8–9 years (N = 249). The cross-sectional study asked validated questions on asthma and allergy that had been used in two previous studies of children from the same areas. In the birth-cohort study, a diagnosis of asthma and allergy was based on predefined clinical criteria, and laboratory evaluation included blood eosinophils, skin-prick tests and specific immunoglobulin E analyses. Information on pets during first year of life was collected retrospectively in the Cross-Sectional Cohort and prospectively in the Birth Cohort.ResultsA dose-response association was seen, with less allergic manifestations (any of asthma, allergic rhinoconjunctivitis, or eczema) with increasing number of household cats and dogs during the first year of life. In the Cross-Sectional Cohort, allergy ever decreased from 49% in those with no pets to zero in those with five or more pets (P-value for trend 0.038), and from 32% to zero for allergy last year (P-value for trend 0.006). The same pattern was seen in Birth Cohort. Sensitization to animals, as well as pollens, also decreased with increasing number of animals in the household.ConclusionThe prevalence of allergic disease in children aged 7–9 years is reduced in a dose-dependent fashion with the number of household pets living with the child during their first year of life, suggesting a “mini-farm” effect, whereby cats and dogs protect against allergy development.