Abstract: Group turnout provides important socializing opportunities for horses, particularly those that are primarily stalled. A high percentage of equine injuries occur during group turnout, which could partly be due to the physical constraints of fencing. To investigate appropriate paddock sizes for group turnouts, horses (n = 12) from a single herd were divided into groups of 4, stalled for 24 hours, and then turned out for 1 hour into one of three differently sized pens: 342, 263, and 184 m2 per horse. Groups rotated through pens across 3 days, receiving one treatment per day. Blood was sampled for cortisol concentrations at 08:00 hours each morning, and then at 15 and 60 minutes into the turn out sessions, and 60 minutes after return to individual stalls. Groups rotated through three turnout times: 09:00, 12:00, 14:00 hours. Counts of agonistic behaviors (chasing, contact biting, and kicking) and low-level threats (pinned ears, tail swishing, bite and kick threats) were recorded. When turned out in pens that provided 342 m2 per horse, horses exhibited reduced plasma cortisol concentrations by 15 minutes after turnout and at 1 hour after return to their stalls (P < .05). Horses in pens providing 184 m2 per horse exhibited greater agonistic (P < .001) and low-level threat (P < .01) behaviors than horses in larger pens. These data provide insight into appropriate pen sizes for horses from established herds. Providing at least 342 m2 per horse may reduce the chance of injury in horses accustomed to group turnout.

Abstract: Abstract Obtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species- and study-specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set-up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data.

Abstract: Summary Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence?absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. Most studies estimating density used capture?recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.

Abstract: This paper describes how man can enter the social hierarchy of the horse by mimicking the behaviour and stance it uses to establish dominance. A herd is organised according to a dominance hierarchy established by means of ritualised conflict. Dominance relationships are formed through these confrontations: one horse gains the dominant role and others identify themselves as subordinates. This study was conducted using five females of the Haflinger breed, totally unaccustomed to human contact, from a free-range breeding farm. The study methods were based on the three elements fundamental to the equilibrium of the herd: flight, herd instinct and hierarchy. The trainer-horse relationship was established in three phases: retreat, approach and association. At the end of the training sessions, all of the horses were able to respond correctly to the trainer. These observations suggest that it is possible to manage unhandled horses without coercion by mimicking their behaviour patterns.

Abstract: The EU-funded Animal Welfare Indicators (AWIN) research project (2011-2015) aimed to improve animal welfare through the development of practical on-farm animal welfare assessment protocols. The present study describes the application of the AWIN approach to the development of a welfare assessment protocol for horses (Equus caballus). Its development required the following steps: (i) selection of potential welfare indicators; (ii) bridging gaps in knowledge; (iii) consulting stakeholders; and (iv) testing a prototype protocol on-farm. Compared to existing welfare assessment protocols for other species, the AWIN welfare assessment protocol for horses introduces a number of innovative aspects, such as implementation of a two-level strategy focused on improving on-farm feasibility and the use of electronic tools to achieve standardised data collection and so promote rapid outcomes. Further refinement to the AWIN welfare assessment protocol for horses is needed in order to firstly gather data from a larger reference population and, secondly, enhance the welfare assessment protocol with reference to different horse housing and husbandry conditions.