Welfare Evaluation Research Articles

Personality matters – The interplay between consistent individual differences and mouse welfare in female C57BL6/J mice

To ensure good welfare of animals in human hands, it is essential to modify housing conditions according to the animals’ needs. Traditionally, the effects of such modifications are studied by means of group-level comparisons, thereby widely neglecting consistent inter-individual differences (i.e., so-called ‘animal personalities’). However, as animals with distinct personality types might differ in their environmental needs and hence react differently to the same environment, such systematic inter-individual differences might have important welfare consequences. This becomes particularly apparent under laboratory conditions, where animals are typically housed under highly standardized and barren environments. Against this background, we here aim to investigate personality-dependent welfare consequences in response to different housing conditions in laboratory mice. Female C57BL/6J mice were characterized for their personality type in exploration behavior and the most and the least explorative individuals were set up in either simple or in highly complex housing conditions that included constantly changing environmental enrichment items. We monitored individual welfare by studying behavioral, physiological, and immunological outcome measures. Besides personality-dependent differences in immune parameters and overall improved welfare under complex housing conditions, we indeed found hints that individual mice were differently affected in their welfare depending on the specific combination of personality type and housing condition. Specifically, highly explorative mice appeared to be more adversely affected by simple housing, but also profited more from complex housing compared to low explorative mice. These findings indicate that welfare promoting adjustments do not necessarily benefit all individuals equally and therefore, call for a shift of perspectives in the evaluation of animal welfare.

Welfare evaluation of fat-rumped lambs under stall feeding condition with different feeder design

Animal welfare is directly related to animal performance and farm profit. It is associated with their autonomy to take feed and water along with a lack of discomfort. Feeding welfare determines farm profit as major cost of a farm is associated with feed. The objective of the study was to investigate the effect of feeder design on lamb welfare evaluated through feeding behaviour and lamb performance. Sixteen growing fat-rumped lambs of 3-4 months of age were categorized into two groups with an average weight of 23.20±0.25 kg. Group I lambs were fed in conventional feeder, i.e. without divider and group II in designed feeder, i.e. with divider, respectively. The eating time was significantly low in group I with longer and strong agonistic behaviour suggesting intense competition within the group. This group showed minimal weight gain and maximal feed wastage due to extreme struggle for food during the period of the study. The time spent in comfort behaviours like lying rumination was more and agonistic behaviour was less in group II lambs. They showed significantly higher bodyweight gain. It can be concluded from the study that group feeding of growing lambs in feeder with divider allocates designated space for individual lamb, reduces agonistic behaviour and brings better growth in lambs under stall feeding conditions.

Indirect Effects of Access to Finance

We created experimental variation across markets in China in the share of firms having access to a new loan product. Access to finance had a large positive direct effect on the performance of treated firms but a similar-sized negative indirect effect on that of firms with treated competitors, leading to nondetectable gains in producer surplus. Access to finance had a positive direct effect on business quality and consumer satisfaction and a negative effect on price, which were not offset by indirect effects, implying net gains in consumer surplus. We document other indirect effects and combine effects in a welfare evaluation. (JEL D22, G21, G32, L81, O16, P31, P34)

Fairness with unequal productive skills among other-regarding individuals

AbstractThis paper deals with the fair ranking of allocations when individuals endowed with heterogeneous skills have other-regarding preferences over the average consumption of the other members of society. By assuming that such preferences matter for equality, we construct three social ordering functions that aim to reduce differences which originate in unequal productivities. These functions seek to maximise the smallest value of an interpersonally comparable measure of individual well-being that is related to a situation which involves neither unfair opportunities nor inequalities in consumption. More importantly, they provide society with different options at the time of making welfare evaluations when individuals are endowed with unequal productive skills and heterogeneous preferences.

Financial crises, bailouts and monetary policy in open economies

I jointly study the optimal bailout policy and monetary policy in open economies that borrow in foreign currency from international lenders. A policy dilemma emerges during financial crises. Policymakers trade off the benefit of more bailouts alleviating firms’ financial constraints against the cost of larger currency devaluation, which tightens firms’ financial constraints. I embed the optimal bailout in an otherwise standard “sudden stop” model with nominal rigidities. The model sheds light on the role of bailouts and currency mismatch in driving the exchange rate dynamics, firms’ balance sheets and economic recovery. Quantitatively, the model matches key business cycle moments. A welfare evaluation shows that there are in general welfare gains from the systemic bailout policy despite ex ante moral hazard problems of firms.

Raising America’s future: Search for optimal child-related transfers

The US differs from other OECD countries in terms of family policy size and composition. This study examines the welfare and macroeconomic effects of family policy reforms. I explore three policy instruments: child-related tax credits, childcare subsidies, and child allowances. The children are merit good due to pay-as-you-go social security structure. I show that expanding family policy, like the American Rescue Plan, improves welfare. I also define the optimal family policy for the United States. It accounts for about 3% of GDP, three times larger than the existing policy, and primarily focused on childcare subsidies. Family policy structure is critical for welfare evaluation because similar expenditure levels can result in contrasting welfare outcomes depending on policy composition. This study emphasizes the importance of carefully designed family policies, as well as the need for ongoing research and policy innovation to maximize societal benefits and promote equitable economic growth.

Model Based Clustering for Regency/City Grouping Based on Community Welfare Indicators in North Sumatra

This thesis aims to apply model-based clustering in grouping regencies/cities in North Sumatra based on Community Welfare Indicators to determine the number of groups (clusters) formed based on community welfare indicators in regencies/cities in North Sumatra and to understand the level of community welfare from this grouping in planning and managing community welfare in regencies/cities in North Sumatra, with the hope of achieving equal welfare in every region. The research method used is Model-Based Clustering, which uses 5 research data variables: HDI, Poor Population, Unemployment Rate, GDP, and Health. In this millennial era, the assessment of community welfare requires more attention. Rapid social, technological, and environmental changes have created new dynamics that can affect community welfare. The evaluation of community welfare is not only limited to economic parameters but also considers health, unemployment, and other factors. By using Model-Based Clustering, it is possible to determine the optimal number of groups (clusters) from various and possibly correlated variables, and the results are easier to understand, making the analysis and understanding of the results easier. Readers can learn about the level of community welfare, and the community and government can evaluate their welfare for future improvements. The research results show that among the groups of regencies/cities formed, five cities consistently show lower Gross Regional Domestic Product (GDP) and Human Development Index (HDI) than other cities. Therefore, a sustainable approach is needed to improve these cities' economic conditions and social welfare.

Long-Term Effects of Assisted Reproductive Technologies on the Health and Productivity of Animals in Ethiopia

Purpose: The aim of the study was to long-term effects of assisted reproductive technologies on the health and productivity of animals in Ethiopia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that the long-term effects of assisted reproductive technologies (ARTs) on the health and productivity of animals in Ethiopia present both opportunities and challenges. ARTs have the potential to improve livestock breeding programs, enhance genetic diversity, and increase productivity, their implementation requires careful consideration of various factors to ensure sustainable outcomes. While these technologies offer the possibility of overcoming reproductive challenges and genetic limitations, they may also pose risks such as increased rates of reproductive disorders, stress associated with handling and manipulation, and potential transmission of infectious diseases. Therefore, ongoing monitoring and evaluation of animal health and welfare are essential to mitigate any adverse effects and ensure the ethical use of ARTs in livestock production systems. Unique Contribution to Theory, Practice and Policy: Life course theory & epigenetic theory may be used to anchor future studies on long-term effects of assisted reproductive technologies on the health and productivity of animals in Ethiopia. Implement rigorous monitoring and evaluation programs to assess the long-term health, welfare, and productivity outcomes of animals produced through ART. Utilize comprehensive datasets to track indicators such as disease incidence, reproductive performance, growth rates, and longevity over multiple generations. Develop evidence-based guidelines and regulations governing the ethical and responsible use of ART in animal breeding programs. Establish standards for the welfare, monitoring, and management of animals produced through reproductive technologies to ensure compliance with ethical principles and animal welfare standards.

PROMINENCE AND MARKET POWER: ASYMMETRIC OLIGOPOLY WITH SEQUENTIAL CONSUMER SEARCH

AbstractThis article presents a new perspective on the nature of market power through the lens of firm prominence. We build a model of oligopolistic price competition with sequential consumer search, showing that a larger firm sets a higher price than its smaller competitors. Consumers are more likely to encounter sellers from a larger firm both immediately and in future interactions, resulting in less‐elastic demand for that firm. Small firms can free‐ride on the prominent firm's market power to raise their prices and earn higher profits. The Herfindahl–Hirschman Index provides a useful guide for welfare evaluation.

Rhamnolipid biosurfactant as robust inhibiting agent for Colletotrichum gloeosporioides-pathogen of Capsicum chinense and evaluation of general welfare of the host plant

Rhamnolipid biosurfactant as robust inhibiting agent for Colletotrichum gloeosporioides-pathogen of Capsicum chinense and evaluation of general welfare of the host plant

Dolphin-WET-Development of a Welfare Evaluation Tool for Bottlenose Dolphins (Tursiops truncatus) under Human Care.

Ensuring high standards of animal welfare is not only an ethical duty for zoos and aquariums, but it is also essential to achieve their conservation, education, and research goals. While for some species, animal welfare assessment frameworks are already in place, little has been done for marine animals under human care. Responding to this demand, the welfare committee of the European Association for Aquatic Mammals (EAAM) set up a group of experts on welfare science, cetacean biology, and zoo animal medicine across Europe. Their objective was to develop a comprehensive tool to evaluate the welfare of bottlenose dolphins (Tursiops truncatus), named Dolphin-WET. The tool encompasses 49 indicators that were either validated through peer review or management-based expertise. The first of its kind, the Dolphin-WET is a species-specific welfare assessment tool that provides a holistic approach to evaluating dolphin welfare. Inspired by Mellor's Five Domains Model and the Welfare Quality®, its hierarchical structure allows for detailed assessments from overall welfare down to specific indicators. Through combining 37 animal-based and 12 resource-based indicators that are evaluated based on a two- or three-level scoring, the protocol offers a detailed evaluation of individual dolphins. This approach allows for regular internal monitoring and targeted welfare management, enabling caretakers to address specific welfare concerns effectively.

Does sedation with AQUI-S® mitigate transport stress and post transport mortality in ballan wrasse (Labrus bergyltae)?

Ballan wrasse (Labrus bergylta) are commonly used as cleaner fish in salmon farms as a biological treatment to mitigate sea lice infestation. Improved welfare for cleaner fish both during production of these fish and when in sea-cages with salmon is crucial for the industry's development. A common operational procedure in ballan wrasse production is transporting juveniles from one land-based farm to another for further on-growing. Episodes of increased mortality have been reported after such transportations. In this study, the relationship between transport stress and post-transport mortality at the on-growing facility was examined. It was also investigated if light sedation with AQUI-S® can mitigate stress during transport. Stress was quantified by measuring cortisol release rate to the tank water during transport. This was investigated in 10 commercial live carrier truck transports (6 without AQUI-S® sedation and 4 with sedation during loading and transport). The total time of transport varied between 12 and 21 h. In general, mortality was significantly higher (1.0 ± 0.6% day-1) the first five days post-transport compared to 15-20 days post transport (0.5% day-1). There was also a strong relationship between fish weight at transport and post-transport mortality, where higher mean weight at transport reduced mortality. In contrast to what was expected, AQUI-S® treatment during transport procedures increased cortisol excretion rate, suggesting a stimulating effect of AQUI-S® on the stress axis in ballan wrasse. Considering these results, the value of using AQUI-S® to reduce stress during transport of juvenile ballan wrasse might be questioned. However, there was no relationship between cortisol release rate during transport and post-transport mortality. Furthermore, this study emphasizes that water cortisol measurements can be used as a none-invasive tool for monitoring stress and can be integrated into the welfare evaluation during commercial fish transports.

Intestinal parasites infecting captive non-human primates in Italy.

Non-human primates (NHPs) living in captive conditions are susceptible to intestinal parasites that can contribute to mortality and morbidity, and cause zoonotic infections. Thus, parasite surveys on NHP populations under human care are relevant as part of the evaluation of NHPs welfare and in the zoonotic disease risk assessment, as well as in the exploration of parasite transmission pathways, according to the One-Health concept. This study aimed to identify intestinal parasites infecting NHPs living in two wildlife recovery centers and in a zoological garden, in Italy. Ninety-three fecal samples from Macaca tonkeana, Macaca fascicularis, Sapajus apella, Chlorocebus aethiops, Macaca fuscata, Macaca sylvanus, and Cebus capucinus were collected at Piano dell'Abatino Park (Lazio), and fecal smears and flotation were performed in order to identify parasites according to morphological keys. Additionally, one carcass of M. fuscata from the Bioparco Zoological Garden of Rome (Lazio) and one of M. fascicularis from the Center for the Recovery of Exotic and Maremma Wild Animals (Tuscany) were necropsied and intestinal adult nematodes were collected and characterized at morphological and molecular level, using the mitochondrial cox1 and rrnL markers. Protozoans (Entamoeba coli, Iodamoeba bütschlii, Dientamoeba fragilis-like, Giardia sp.), chromists (Balantidium/Buxtonella sp.) and nematodes (Capillaria sp., Trichuris sp., strongyliform larvae and Oesophagostomum sp.) were found through fecal smears and flotation. The collected adult nematodes from dead NHPs were morphologically identified as whipworms (genus Trichuris). Phylogenetic analyses grouped Trichuris specimens into the Trichuris trichiura complex of species, with specimens from M. fuscata clustering into a host-specific branch, and whipworms from M. fascicularis clustering within a clade formed by Trichuris infecting several primate species, including humans. The results here collected revealed the presence of potentially zoonotic parasites circulating in captive primates in Italy, providing useful information for the formulation of management and care plans for captive NHPs, and for the elaboration of safety measures for visitors and animal keepers.

Exploring positive welfare measures: preliminary findings from a prototype protocol in loose housing dairy cattle farms.

Following the increasing interest about the development of indicators of positive welfare and affective state in farm animals, the aim of this research is to present some preliminary results on the application of a prototype protocol based exclusively on positive welfare measures and to suggest potential benefits that can promote positive welfare. The protocol was applied in 20 loose housing dairy cattle farms (6 on deep litter with straw, 14 in cubicles) and included only indicators of positive welfare and emotional states: feeding and resting synchronization, rumination during resting, comfortable lying postures, no visible eye white, relaxed ear postures, percentage of cow contacts with humans in the Avoidance Distance test. Potential benefits in terms of housing, feeding and management were then related to these variables (Mann-Whitney U test). Qualitative Behavior Assessment (QBA) was also carried out and analyzed by Principal Component Analysis to explore the effect of factors that were not evenly distributed in our sample (number of feed distributions, access to pasture, presence of paddock or environmental enrichments, automatic milking systems). When hay was included in the diet, higher feeding synchronization (93.7 ± 1.6 vs. 52.2 ± 4.7%; p < 0.01), percentage of cows with relaxed ear postures (35.8 ± 5.4 vs. 15.5 ± 2.1%; p < 0.01) and percentage of cows with no visible eye white (55.9 ± 17.0 vs. 36.6 ± 4.1%; n.s.) were recorded. A higher level of feeding synchronization was observed also when the feeding places/cow ratio was > 1 (72.1 ± 9.9 vs. 53.8 ± 5.8%), although differences were not significant (p = 0.14). Deep litter had a more positive effect than cubicles on comfort at resting, with a significantly higher percentage of ruminating cows (65.8 ± 10.2 vs. 34.2 ± 3.7%; p < 0.01), a higher percentage of cows with no visible eye white (55.6 ± 9.9 vs. 33.1 ± 3.7%; p < 0.05) and a higher percentage of cows in a more comfortable posture, with stretched legs (14.3 ± 5.1 vs. 5.6 ± 1.6%; p = 0.09). QBA highlighted the most positive emotional state in the only farm that allowed access to pasture. This study represents a first attempt to apply a protocol for on-farm welfare evaluation based exclusively on the use of positive welfare indicators and provides suggestions on possible benefits (e.g., deep litter, feeding places/cow ratio > 1, hay in the diet and access to pasture) to enhance dairy cattle welfare.

A systematic approach to defining and verifying descriptors used in the Qualitative Behavioural Assessment of sows.

Qualitative Behaviour Assessment (QBA) is a welfare evaluation tool that uses a holistic approach to capturing an animal's emotional state. Lists of QBA descriptors validated to assess pig welfare exist, but their definitions are often not described in peer-reviewed literature and the processes used to develop definitions are lacking. The objective of this study is to detail a systematic approach to creating clear definitions for a pre-existing fixed list of QBA descriptors and test their application. A fixed list of 20 descriptors from the EU Welfare Quality® assessment protocol for pigs was modified, and ten pig experts were recruited to assist with defining these descriptors in a focus group-style discussion. Half of the experts involved in creating descriptor definitions partook in a subsequent step, where the newly developed definitions were tested by implementing QBA on a video library of post-weaned sows selected to capture the breadth of sow behaviour. Experts displayed excellent agreement in identifying a PCA dimension interpreted as the valence of descriptors and good agreement for another reflecting arousal. Inter-observer reliability was also measured for each descriptor. Only two descriptors exhibited less than moderate agreement between experts whereas half of the descriptors evoked substantial agreement or better. These findings support our process to delineate clear definitions for a fixed list of QBA descriptors in pigs. This study is the first of its kind detailing the in-depth process of creating and verifying descriptor definitions for future use in sow welfare assessment.

Welfare evaluation of dairy cows reared in the East of Algeria.

The aim of the study was to evaluate the welfare status of dairy cows raised in local conditions through health criteria. Important health problems have been identified as well as their effect on the milk yield. One hundred seven farms in eastern Algeria were visited. Data on health, productivity, and management practices were collected. Clinical examination of 1210 dairy cows was conducted to assess health scores. The relationship between herd health and milk yield was investigated using multiple linear regression models. The average milk yield per cow was 16.1 kg/day, and the average prevalence of thin cows (body condition score ≤ 2) was 35.1%. The cow dirtiness was a sign of poor facility hygiene, with 24.3% of cows had dirty udders, 44.5% had dirty flanks/upper legs, and 59.6% had dirty hind legs. The mean prevalence of clinical lameness (locomotion score ≥ 3) and severe lameness (locomotion score ≥ 4) were 24.7% and 8.7%, respectively. The prevalence of hocks, knees, and neck injuries (score > 1) with wound and/or swelling ranged from 0 to 46.2%, 0 to 71.4%, and 0 to 14.3%, respectively. The clinical examination showed a percentage of cows with mastitis of 15.4%, diarrhea of 6.9%, cough of 3.2%, nasal discharge of 7.5%, and ocular discharge of 1.8%. Thus, the milk yield had associated with severe lameness, mastitis, thinness, and dystocia. In conclusion, the welfare indicators in this study reflect the serious health problems in dairy farming which influence the expression of the cow genetic potential.

Social welfare evaluation during demand response programs execution considering machine learning-based load profile clustering

In the last decade, with the introduction of smart meters to smart grids, demand response programs (DRPs) have been widely adopted to establish a generation and consumption balance. DRPs provide many benefits for efficient grid management. However, these programs are conducive to higher levels of dissatisfaction by changing grid customers' consumption patterns. This paper aims to investigate the effects of DRPs on social welfare (SW). To this end, the paper presents a mathematical model for SW during the implementation of DRPs. In the proposed model, the level of customer satisfaction is assumed the main factor contributing to SW. This mathematical model considers different types of DRPs in terms of their impacts on SW. The paper also seeks to obtain linear and nonlinear models of DRPs and the coefficient of participation (CoP). CoP as an indicator shows the percentage of customers who actively participate in each DRP and plays a significant role in the assessment of the SW level. Moreover, owing to the sparsity and variety of distribution network customers, load patterns are classified into different clusters to take the load types into account. As a matter of fact, this process aims to identify similar patterns and thus, the same level of satisfaction for each separate cluster. The classification process is performed by using a machine learning-based clustering method known as the Affinity Propagation (AP) algorithm. Then, the model calculates the level of SW for the clusters based on the usage of electrical equipment and the time of day when they are turned on. The obtained levels of SW help operators select the best programs for every cluster in terms of customer satisfaction, and achieve the highest performance of DRPs. Lastly, the model is evaluated using real data of a distribution network to ensure the effectiveness and accuracy of the model.

Study of the Feasibility of Proposed Measures to Assess Animal Welfare for Zebu Beef Farms within Pasture-Based Systems under Tropical Conditions

Pasture-based production systems are predominant in major beef-producing countries; however, these systems lack validated protocols to assess animal welfare under commercial conditions. The objective of this study was to test the feasibility of the proposed measures and methodology for the evaluation of animal welfare in fattening cattle under pasture conditions. The initial methodology was developed with the participation of producers, professionals, the general public, and the Colombian health authority, through workshops with a participatory approach and collaborative knowledge management. The study was carried out in 24 pasture-based commercial Zebu cattle farms in the middle Magdalena region of Colombia. Visits were made with an average duration of 2.5 h, which included the evaluation of 788 fattening cattle. The methodology evaluated animal-based, resource-based, and management-based indicators through a questionnaire-guided interview to evaluate cattle handling and health, animal-based measurements, and documentation management. A protocol validation process was carried out by selecting indicators that remained unchanged, adjusting those that were feasible to implement, and removing inadequate indicators. The application of the methodology demonstrated that there are feasible measures to include in the evaluation protocols of pasture-based fattening systems. Likewise, the active participation of producers is crucial to achieving a greater commitment to the implementation of this methodology for the assessment of animal welfare in cattle under pasture conditions.

An Exploration of the Factors Influencing the Public Good of College Students under the Entropy Approach

In order to make China's public welfare activities develop better, this paper establishes a college students' public welfare evaluation model by entropy weight method through the study of the influencing factors of college students' public welfare, and examines the accuracy of the model by using BP neural network.The public welfare of university students is mainly affected by economic, epidemiological and academic factors.

Measuring dairy cow welfare with real-time sensor-based data and farm records: a concept study

Welfare assessment of dairy cows by in-person farm visits provides only a snapshot of welfare and is time-consuming and costly. Possible solutions to reduce the need for in-person assessments would be to exploit sensor data and other routinely collected on-farm records. The aim of this study was to develop an algorithm to classify dairy cow welfare based on sensors (accelerometer and/or milk meter) and farm records (e.g. days in milk, lactation number). In total, 318 cows from six commercial farms located in Finland, Italy and Spain (two farms each) were enrolled for a pilot study lasting 135 days. During this time, cows were routinely scored using 14 animal-based measures of good feeding, health and housing based on the Welfare Quality® (WQ®) protocol. WQ® measures were evaluated daily or approximately every 45 days, using disease treatments from farm records and on-farm visits, respectively. WQ® measures were supplemented with daily temperature-humidity index to account for heat stress. The severity and duration of each welfare measure were evaluated, and the final welfare index was obtained by summing up the values for each cow on each pilot study day, and stratifying the result into three classes: good, moderate and poor welfare. For model building, a machine-learning (ML) algorithm based on gradient-boosted trees (XGBoost) was applied. Two model versions were tested: (1) a global model tested on unseen herd, and (2) a herd-specific model tested on unseen part of the data from the same herd. The version (1) served as an example on the model performance on a herd not previsited by the evaluator, while version (2) resembled a custom-made solution requiring in-person welfare evaluation for model training. Our results indicated that the global model had a low performance with average sensitivity and specificity of 0.44 and 0.68, respectively. For the herd-specific version, the model performance was higher reaching an average of 0.64 sensitivity and 0.80 specificity. The highest classification performance was obtained for cows in poor welfare, followed by cows in good and moderate welfare (balanced accuracy of 0.77, 0.71 and 0.68, respectively). Since the global model had low classification accuracy, the use of the developed model as a stand-alone system based solely on sensor data is infeasible, and a combination of in-person and sensor-based welfare evaluation would be preferable for a reliable welfare assessment. ML-based solutions, even with fair discriminative abilities, have the potential to enhance dairy welfare monitoring.