Clinal versus disruptive latitudinal variation in fruit traits of a South American mistletoe.

Fruit traits have historically been interpreted as plant adaptations to their seed dispersers. On the other hand, different environmental factors, which vary spatially and temporally, can shape fruit-trait variation. The mistletoe Tristerix corymbosus has a latitudinal distribution along the South American Pacific rim that encompasses two different biomes, the matorral of central Chile and the temperate forest that extends south of the matorral. This mistletoe shows contrasting fruiting phenology (spring vs summer), fruit color (yellow vs green), and seed dispersers (birds vs marsupial) in these two biomes. We characterized geographic variation of morphological and nutritional fruit traits of T. corymbosus to evaluate which macroecological factor, biome or latitude, better explains spatial variation in these variables. For each of 22 populations, we obtained environmental data (temperature, precipitation, and canopy cover), measured fruit and seed morphology traits (size, shape, and weight), and pulp moisture and nutritional content (fiber, protein, fat, carbohydrates, ash, and caloric content). Patterns of variation for each variable were described by fitting and comparing five different simple models varying in slope, intercept or both. Fruit morphology showed a clear biome-related disruptive pattern, seed morphological traits were unrelated to either biome or latitude, whereas nutritional variables showed diverse patterns. Different environmental factors seem to affect fruit development and phenology, determining the observed fruit characteristics, with seed dispersers playing a minor role in shaping these patterns. More generally, the contrasting plant-seed disperser associations we addressed can be interpreted as the outcome of an ecological-fitting rather than of a coevolutionary process.

An "orientation sphere" visualization for examining animal head movements.

Animal behavior is elicited, in part, in response to external conditions, but understanding how animals perceive the environment and make the decisions that bring about these behavioral responses is challenging.Animal heads often move during specific behaviors and, additionally, typically have sensory systems (notably vision, smell, and hearing) sampling in defined arcs (normally to the front of their heads). As such, head-mounted electronic sensors consisting of accelerometers and magnetometers, which can be used to determine the movement and directionality of animal heads (where head "movement" is defined here as changes in heading [azimuth] and/or pitch [elevation angle]), can potentially provide information both on behaviors in general and also clarify which parts of the environment the animals might be prioritizing ("environmental framing").We propose a new approach to visualize the data of such head-mounted tags that combines the instantaneous outputs of head heading and pitch in a single intuitive spherical plot. This sphere has magnetic heading denoted by "longitude" position and head pitch by "latitude" on this "orientation sphere" (O-sphere).We construct the O-sphere for the head rotations of a number of vertebrates with contrasting body shape and ecology (oryx, sheep, tortoises, and turtles), illustrating various behaviors, including foraging, walking, and environmental scanning. We also propose correcting head orientations for body orientations to highlight specific heading-independent head rotation, and propose the derivation of O-sphere-metrics, such as angular speed across the sphere. This should help identify the functions of various head behaviors.Visualizations of the O-sphere provide an intuitive representation of animal behavior manifest via head orientation and rotation. This has ramifications for quantifying and understanding behaviors ranging from navigation through vigilance to feeding and, when used in tandem with body movement, should provide an important link between perception of the environment and response to it in free-ranging animals.

Monitoring canid scent marking in space and time using a biologging and machine learning approach.

For canid species, scent marking plays a critical role in territoriality, social dynamics, and reproduction. However, due in part to human dependence on vision as our primary sensory modality, research on olfactory communication is hampered by a lack of tractable methods. In this study, we leverage a powerful biologging approach, using accelerometers in concert with GPS loggers to monitor and describe scent-marking events in time and space. We performed a validation experiment with domestic dogs, monitoring them by video concurrently with the novel biologging approach. We attached an accelerometer to the pelvis of 31 dogs (19 males and 12 females), detecting raised-leg and squat posture urinations by monitoring the change in device orientation. We then deployed this technique to describe the scent marking activity of 3 guardian dogs as they defend livestock from coyote depredation in California, providing an example use-case for the technique. During validation, the algorithm correctly classified 92% of accelerometer readings. High performance was partly due to the conspicuous signatures of archetypal raised-leg postures in the accelerometer data. Accuracy did not vary with the weight, age, and sex of the dogs, resulting in a method that is broadly applicable across canid species' morphologies. We also used models trained on each individual to detect scent marking of others to emulate the use of captive surrogates for model training. We observed no relationship between the similarity in body weight between the dog pairs and the overall accuracy of predictions, although models performed best when trained and tested on the same individual. We discuss how existing methods in the field of movement ecology can be extended to use this exciting new data type. This paper represents an important first step in opening new avenues of research by leveraging the power of modern-technologies and machine-learning to this field.

Drivers of bird-window collisions in southern South America: a two-scale assessment applying citizen science.

Bird-window collisions are one of the main causes of avian mortality worldwide, with estimations reaching up to almost one billion of dead individuals annually due to this cause in Canada and the USA alone. Although this is a growing conservation problem, most of the studies come from North America, evidencing the lack of knowledge and concern in countries with high biodiversity and growing population development. Our objectives were: (1) to estimate the current situation of bird-window collisions in Argentina, a country with around 10% of the world's avian biodiversity, and, (2) to identify drivers of bird-window collisions at a national and local scale, focusing on a city surrounded by a protected area. We used a citizen science project called "Bird-Window Collisions in Argentina" that consisted of an online survey that collected data on collision metrics and risk factors. We found that more than half of participants reported at least one collision during the last year, suggesting this issue is common and widespread. In addition, our data show that the number of windows and the presence of vegetation reflected in windows are factors that strongly influence the risk of collision at national scale. On the other hand, the environment surrounding buildings affects the rate of bird-window collisions at local scale, being greater in buildings surrounded by tall vegetation than in buildings surrounded by a greater proportion of urbanization (human-made structures). We call for attention on a topic that has been poorly evaluated in South America. We also encourage future scientific studies to evaluate additional risk factors and mitigation strategies accordingly, to provide a better understanding of bird-window collisions particularly in a highly biodiverse region as South America.

Luck in Food Finding Affects Individual Performance and Population Trajectories.

Energy harvesting by animals is important because it provides the power needed for all metabolic processes. Beyond this, efficient food finding enhances individual fitness [1] and population viability [2], although rates of energy accumulation are affected by the environment and food distribution. Typically, differences between individuals in the rate of food acquisition are attributed to varying competencies [3], even though food-encounter rates are known to be probabilistic [4]. We used animal-attached technology to quantify food intake in four disparate free-living vertebrates (condors, cheetahs, penguins, and sheep) and found that inter-individual variability depended critically on the probability of food encounter. We modeled this to reveal that animals taking rarer food, such as apex predators and scavengers, are particularly susceptible to breeding failure because this variability results in larger proportions of the population failing to accrue the necessary resources for their young before they starve and because even small changes in food abundance can affect this variability disproportionately. A test of our model on wild animals indicated why Magellanic penguins have a stable population while the congeneric African penguin population has declined for decades. We suggest that such models predicting probabilistic ruin can help predict the fortunes of species operating under globally changing conditions.

Synergy between roads and disturbance favour Bromus tectorum L. invasion.

BACKGROUND: Global change produces pervasive negative impacts on biodiversity worldwide. Land use change and biological invasions are two of the major drivers of global change that often coexist; however, the effects of their interaction on natural habitats have been little investigated. In particular, we aimed to analyse whether the invasion of an introduced grass (Bromus tectorum; cheatgrass) along roads verges and the disturbance level in the natural surrounding habitat interact to influence the degree of B. tectorum invasion in the latter habitats in north-western Patagonia. METHODS: Along six different roads, totalling approximately 370 km, we set two 50 m × 2 m sampling plots every 5 km (73 plots in total). One plot was placed parallel to the road (on the roadside) and the other one perpendicular to it, towards the interior of the natural surrounding habitat. In each plot, we estimated the B. tectorum plant density in 1 m2 subplots placed every 5 m. In the natural habitat, we registered the vegetation type (grassy steppe, shrub-steppe, shrubland, and wet-meadow) and the disturbance level (low, intermediate, and high). Disturbance level was visually categorized according to different signs of habitat degradation by anthropogenic use. RESULTS: B. tectorum density showed an exponential decay from roadsides towards the interior of natural habitats. The degree of B. tectorum invasion inside natural habitats was positively related to B. tectorum density on roadsides only when the disturbance level was low. Shrub-steppes, grassy steppes and shrublands showed similar mean density of B. tectorum. Wet-meadows had the lowest densities of B. tectorum. Intermediate and highly disturbed environments presented higher B. tectorum density than those areas with low disturbance. DISCUSSION: Our study highlights the importance of the interaction between road verges and disturbance levels on B. tectorum invasion in natural habitats surrounding roads of north-western Patagonia, particularly evidencing its significance in the invasion onset. The importance of invasion in road verges depends on disturbance level, with better conserved environments being more resistant to invasion at low levels of B. tectorum density along road verges, but more susceptible to road verges invasion at higher levels of disturbance. All the habitats except wet-meadows were invaded at a similar degree by B. tectorum, which reflects its adaptability to multiple habitat conditions. Overall, our work showed that synergies among global change drivers impact native environments favouring the invasion of B. tectorum.

Multi-dimensional Precision Livestock Farming: a potential toolbox for sustainable rangeland management.

BACKGROUND: Precision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits. METHODS: For this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space. RESULTS: The combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography. DISCUSSION: The quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.

The importance of individual variation in the dynamics of animal collective movements.

Animal collective movements are a key example of a system that links two clearly defined levels of organization: the individual and the group. Most models investigating collective movements have generated coherent collective behaviours without the inclusion of individual variability. However, new individual-based models, together with emerging empirical information, emphasize that within-group heterogeneity may strongly influence collective movement behaviour. Here we (i) review the empirical evidence for individual variation in animal collective movements, (ii) explore how theoretical investigations have represented individual heterogeneity when modelling collective movements and (iii) present a model to show how within-group heterogeneity influences the collective properties of a group. Our review underscores the need to consider variability at the level of the individual to improve our understanding of how individual decision rules lead to emergent movement patterns, and also to yield better quantitative predictions of collective behaviour.This article is part of the theme issue 'Collective movement ecology'.

Towards evenly distributed grazing patterns: including social context in sheep management strategies.

Background. A large proportion of natural grasslands around the world is exposed to overgrazing resulting in land degradation and biodiversity loss. Although there is an increasing effort in the promotion of sustainable livestock management, rangeland degradation still occurs because animals' foraging behaviour is highly selective at different spatial scales. The assessment of the ecological mechanisms modulating the spatial distribution of grazing and how to control it has critical implications for long term conservation of resources and the sustainability of livestock production. Considering the relevance of social interactions on animals' space use patterns, our aim was to explore the potential effects of including animals' social context into management strategies using domestic sheep grazing in rangelands as case study. Methods. We used GPS data from 19 Merino sheep (approximately 10% of the flock) grazing on three different paddocks (with sizes from 80 to 1000 Ha) during a year, to estimate resource selection functions of sheep grazing in flocks of different levels of heterogeneity. We assessed the effects of sheep class (i.e., ewes, wethers, and hoggets), age, body condition and time since release on habitat selection patterns. Results. We found that social rank was reflected on sheep habitat use, where dominant individuals (i.e., reproductive females) used more intensively the most preferred areas and low-ranked (i.e., yearlings) used less preferred areas. Our results showed that when sheep grazed on more heterogeneous flocks, grazing patterns were more evenly distributed at all the paddocks considered in this study. On the other hand, when high-ranked individuals were removed from the flock, low-ranked sheep shifted their selection patterns by increasing the use of the most preferred areas and strongly avoided to use less preferred sites (i.e., a highly selective grazing behaviour). Discussion. Although homogenization and segregation of flocks by classes are common practices to increase flock productivity, we are proposing an alternative that employs behavioural interactions in heterogeneous flocks to generate more evenly distributed grazing patterns. This practice can be combined with other practices such as rotational grazing and guardian dogs (to decrease mortality levels that may be generated by sheep grazing on more risky habitats). This does not imply any modifications of livestock stocking rates and densities or any additional investments for labour and materials. Considering livestock behaviour is critical for the design of sustainable management practices that balance landscape conservation and livestock productivity.

Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in 'Daily Diary' tags.

BACKGROUND: Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information. DESCRIPTION: This work presents Framework4, an all-encompassing software suite which operates on smart sensor data to determine the 4 key elements considered pivotal for movement analysis from such tags (Endangered Species Res 4: 123-37, 2008). These are; animal trajectory, behaviour, energy expenditure and quantification of the environment in which the animal moves. The program transforms smart sensor data into dead-reckoned movements, template-matched behaviours, dynamic body acceleration-derived energetics and position-linked environmental data before outputting it all into a single file. Biologists are thus left with a single data set where animal actions and environmental conditions can be linked across time and space. CONCLUSIONS: Framework4 is a user-friendly software that assists biologists in elucidating 4 key aspects of wild animal ecology using data derived from tags with multiple sensors recording at high rates. Its use should enhance the ability of biologists to derive meaningful data rapidly from complex data.