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Mutualism effectiveness, the contribution of an interacting organism to its partner's fitness, is defined as the number of immediate outcomes of the interactions (quantity component) multiplied by the probability that an immediate outcome results in a new individual (quality component). These components form a two‐dimensional effectiveness landscape with each species' location determined by its values of quantity (x‐axis) and quality (y‐axis). We propose that the evolutionary history of mutualistic interactions leaves a footprint that can be identified by three properties of the spatial structure of effectiveness values: dispersion of effectiveness values, relative contribution of each component to the effectiveness values and correlation between effectiveness components. We illustrate this approach using a large dataset on synzoochory, seed dispersal by seed‐caching animals. The synzoochory landscape was clumped, with effectiveness determined primarily by the quality component, and with quantity and quality positively correlated. We suggest this type of landscape structure is common in generalised coevolved mutualisms, where multiple functionally equivalent, high‐quality partners exert similarly strong selection. Presumably, only those organisms located in high‐quality regions will impact the evolution of their partner. Exploring properties of effectiveness landscapes in other mutualisms will provide new insight into the evolutionary and ecological consequences of mutualisms. [ABSTRACT FROM AUTHOR]

Modern, high‐throughput animal tracking increasingly yields 'big data' at very fine temporal scales. At these scales, location error can exceed the animal's step size, leading to mis‐estimation of behaviours inferred from movement. 'Cleaning' the data to reduce location errors is one of the main ways to deal with position uncertainty. Although data cleaning is widely recommended, inclusive, uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is relatively scarce.A pipeline for cleaning massive high‐throughput datasets must balance ease of use and computationally efficiency, in which location errors are rejected while preserving valid animal movements. Another useful feature of a pre‐processing pipeline is efficiently segmenting and clustering location data for statistical methods while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time‐consuming, and to boost reproducibility, pre‐processing pipelines must be automated.We provide guidance on building pipelines for pre‐processing high‐throughput animal tracking data to prepare it for subsequent analyses. We apply our proposed pipeline to simulated movement data with location errors, and also show how large volumes of cleaned data can be transformed into biologically meaningful 'residence patches', for exploratory inference on animal space use. We use tracking data from the Wadden Sea ATLAS system (WATLAS) to show how pre‐processing improves its quality, and to verify the usefulness of the residence patch method. Finally, with tracks from Egyptian fruit bats Rousettus aegyptiacus, we demonstrate the pre‐processing pipeline and residence patch method in a fully worked out example.To help with fast implementation of standardised methods, we developed the R package atlastools, which we also introduce here. Our pre‐processing pipeline and atlastools can be used with any high‐throughput animal movement data in which the high data‐volume combined with knowledge of the tracked individuals' movement capacity can be used to reduce location errors. atlastools is easy to use for beginners while providing a template for further development. The common use of simple yet robust pre‐processing steps promotes standardised methods in the field of movement ecology and leads to better inferences from data. [ABSTRACT FROM AUTHOR]

Author(s): Ran Nathan (corresponding author) [1]; Gabriel G. Katul [2]; Henry S. Horn [3]; Suvi M. Thomas [3]; Ram Oren [2]; Roni Avissar [4]; Stephen W. Pacala [3]; Simon A. [...]

For migratory species, seasonal movements complicate local climate adaptation, as it is unclear whether individuals track climate niches across the annual cycle. In the migratory songbird yellow warbler (Setophaga petechia), we find a correlation between individual‐level wintering and breeding precipitation, but not temperature. Birds wintering in the driest regions of the Neotropics breed in the driest regions of North America. Individuals from drier regions also possess distinct morphologies and population responses to varying rainfall. We find a positive association between bill size and breeding season precipitation which, given documented climate‐associated genomic variation, might reflect adaptation to local precipitation regimes. Relative abundance in the breeding range is linked to interannual fluctuations in precipitation, but the directionality of this response varies across geography. Together, our results suggest that variation in climate optima may exist across the breeding range of yellow warblers and provide a mechanism for selection across the annual cycle. [ABSTRACT FROM AUTHOR]

Large animals provide crucial seed dispersal services, yet face continued threats and are susceptible to changes in landscape composition and configuration. Thus, there is a growing imperative to improve understanding of animal‐generated seed dispersal using models that incorporate spatial complexity in a realistic, yet tractable, way.We developed a spatially explicit agent‐based seed dispersal model, with disperser movements informed by biotelemetry data, to evaluate how landscape composition and configuration affect seed dispersal patterns. We illustrated this approach for the world's second largest ratite, the emu (Dromaius novaehollandiae), a highly mobile generalist frugivore considered an important long‐distance disperser for many plant species across Australia.When animal movement is unrestricted, model parameters related to seed gut passage largely determine seed dispersal kernels. However, as habitat loss and fragmentation increase, the extent of long‐distance dispersal events is reduced and seed shadows became progressively more aggregated. This effect is due to the emu not being able to move between disconnected parts of the landscape, with small changes in habitat structure causing decreased long‐distance dispersal.We simulated seed dispersal patterns generated by three commonly used generic models of animal movement – unbiased and biased correlated random walks and Lévy walks – to evaluate how different representations of movement affect estimations of animal movements and emergent seed dispersal patterns. Simulated movements informed by the emu biotelemetry data resulted in longer median seed dispersal distances than do the three generic models.Synthesis. Changes in landscape composition and configuration can dramatically alter patterns of zoochorous seed dispersal as they influence animal movement. However, when models are used to simulate the patterns of seed dispersal, decisions about how animal movement is represented also affect estimates of seed dispersal. [ABSTRACT FROM AUTHOR]

1 Long-distance dispersal (LDD) of seeds by wind plays an important role in population survival and structure, especially in naturally patchy or human-fragmented metapopulations. However, no study has tested its effects using a realistic dispersal kernel in a metapopulation context with explicit spatial structure and local extinctions. 2 We incorporated such kernels into a newly proposed simulation model, which combines within-patch (population) demographic processes and a simplified maternally inherited single-locus, two-allele genetic make-up of the populations. As a test case, we modelled a typical conservation scenario of Aleppo pine (Pinus halepensis) populations. 3 The effects of LDD were rather diverse and depended on initial population conditions and local extinction rates. LDD increased metapopulation survival at intermediate local-extinction probabilities. LDD helped maintain higher total genetic variability in populations that were initially drifted, but facilitated random genetic loss through drift in initially 'well mixed' populations. LDD prevented population differentiation in low extinction rates but increased it at intermediate to high extinction rates. 4 Our results suggest that LDD has broader evolutionary implications and would be selected for in populations facing intermediate local-extinction pressures. Our modelling approach provides a strong tool to test the effects of LDD on metapopulation survival and genetic variability and to identify the parameters to which such effects are most sensitive, in ecological and conservational scenarios.

1 Although, in nature, seed dispersal usually declines with distance from the source, seedling establishment patterns are highly variable. An increase in seed survival can lead to either hump-shaped (Janzen-Connell (J-C) pattern) or declining (Hubbell pattern) establishment with distance from seed source, but declining establishment can also be generated if survival decreases with distance (McCanny pattern). Pathogens and seed predators are considered to be major mortality agents structuring recruitment patterns, but it is unclear how well predation alone can explain variation in these patterns. 2 We introduce a simple mechanistic model showing that distance and density-dependent seed predation can generate all of the observed recruitment patterns. Our approach provides the first mathematical reconstruction of conceptual models previously considered to be based on contrasting underlying mechanisms. Three easily measurable quantities (the proportion of seeds escaping predation at the source, and the mean distance from the source of dispersed seeds and of predators' activity) can be used to test for consistency with the J-C pattern. The association between recruitment patterns and plant (dispersal) and animal (predation) characteristics is robust with respect to parameter values and various functional forms. 3 The model shows that the J-C pattern can occur only if the mean distance over which predators are active is lower than that over which seeds are dispersed, corresponding to a system with host-specific, or immobile, seed predators (often invertebrates) that are restricted to areas of high seed density near adult plants, and therefore selecting for longer dispersal distances of seeds. 4 The Hubbell pattern is generated by the model when dispersal and predation distances are of equivalent magnitudes. The McCanny pattern emerges if more generalized, or more mobile, seed predators (often vertebrates) are attracted to the adult trees but also tend to forage farther away, thereby selecting for short dispersal distances that generate high densities needed to satiate seed predators. 5 The model also predicts that the total number of seeds surviving predation is lowest at intermediate distances, suggesting that distance-dependent predation promotes either short or long dispersal distances, or both (dimorphism).

Despite the importance of seed dispersal in a plant's life cycle, global patterns in seed dispersal distance have seldom been studied. This paper presents the first geographically and taxonomically broad quantification of the latitudinal gradient in seed dispersal distance. Although there is substantial variation in the seed dispersal distances of different species at a given latitude, seeds disperse on average more than an order of magnitude further at the equator than towards the poles. This pattern is partially explained by plant life‐history traits that simultaneously associate with seed dispersal distance and latitude, including dispersal mode and plant height. The extended seed shadow of tropical plants could increase the distance between conspecific individuals. This could facilitate species coexistence and contribute to the maintenance of high plant diversity in tropical communities. The latitudinal gradient in dispersal distance also has implications for species' persistence in the face of habitat fragmentation and climate change. [ABSTRACT FROM AUTHOR]

Animals typically adjust their behaviour to their changing environment throughout the annual cycle, modulating key processes such as the timing of breeding and the onset of migration. Such behavioural changes are commonly manifested in the movements and the energetic balance of individuals in relation to their species‐specific physiological characteristics, habitat attributes and the environmental properties of their distribution ranges. We used GPS and acceleration data collected using transmitters on free‐ranging birds to quantify annual movement patterns and estimate energy expenditure of the Dalmatian Pelican Pelecanus crispus, a large, soaring avian species which performs short‐distance migration and spends its entire annual cycle in mid‐latitudes. To assess the representativeness of our results, the transmitter effect was also tested. We found that daily trends in the overall dynamic body acceleration (ODBA; a proxy for energy expenditure) differed among seasons, with the highest values occurring during spring and the lowest during winter. Long inter‐lake flights were very rare in winter, and the number of flights and ODBA during spring was higher than during summer, suggesting greater motivation to move in spring. Although transmitters may have affected the birds, as none of the tagged birds bred, we found seasonal differences in behaviour and activity level. The observed patterns in differences in activity levels, long‐distance flights and flight characteristics between seasons suggest an annual rhythm of energy expenditure. These findings allow a better understanding of bird phenology, specifically regarding adaptations to wintering in a cold climate by reducing movement‐driven energy expenditure. Finally, the identification of periods with high and low energy expenditure may guide future conservation efforts by adjusting conservation plans in accordance with changing needs during the annual cycle. [ABSTRACT FROM AUTHOR]

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population‐level characteristics are tied with individual‐level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous‐time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion (Puma concolor; in Colorado, USA) and African buffalo (Syncerus caffer; in Kruger National Park, South Africa) recharge dynamics. [ABSTRACT FROM AUTHOR]

Early arrival at breeding grounds is of prime importance for migrating birds as it is known to enhance breeding success. Adults, males and higher quality individuals typically arrive earlier, and across years, early arrival has been linked to warmer spring temperatures. However, the mechanisms and potential costs of early arrival are not well understood.To deepen the understanding of arrival date differences between individuals and years, we studied them in light of the preceding spring migration behaviour and atmospheric conditions en route.GPS and body acceleration (ACC) data were obtained for 35 adult white storks (Ciconia ciconia) over five years (2012–2016). ACC records were translated to energy expenditure estimates (overall dynamic body acceleration; ODBA) and to behavioural modes, and GPS fixes were coupled with environmental parameters.At the interindividual level (within years), early arrival was attributed primarily to departing earlier for migration and from more northern wintering sites (closer to breeding grounds), rather than to migration speed. In fact, early‐departing birds flew slower, experienced weaker thermal uplifts and expended more energy during flight, but still arrived earlier, emphasizing the cost and the significance of early departure. Individuals that wintered further south arrived later at the breeding grounds but did not produce fewer fledglings, presumably due to positive carry‐over effects of advantageous wintering conditions (increased precipitation, vegetation productivity and daylight time). Therefore, early arrival increased breeding success only after controlling for wintering latitude. Males arrived slightly ahead of females. Between years, late arrival was linked to colder temperatures en route through two different mechanisms: stronger headwinds causing slower migration and lower thermal uplifts resulting in longer stopovers.This study showed that distinct migratory properties underlie arrival time variation within and between years. It highlighted (a) an overlooked cost of early arrival induced by unfavourable atmospheric conditions during migration, (b) an important fitness trade‐off in storks between arrival date and wintering habitat quality and (c) mechanistic explanations for the negative temperature–arrival date correlation in soaring birds. Such understanding of arrival time can facilitate forecasting migrating species responses to climate changes. Early arrival at breeding grounds enhances bird breeding success. The authors found that between individual white storks, early arrival was primarily attributed to departing earlier for spring migration, but this had a cost of more strenuous migration under unfavourable atmospheric conditions. They also described a tradeoff between arrival time and wintering site quality. [ABSTRACT FROM AUTHOR]

We present a temporally and spatially explicit mechanistic model of tree seed dispersal by wind, incorporating full stochasticity based on natural variation. The model simulates the dispersal of each individual seed by integrating the temporal effects of climatic conditions on the rate of seed release, and the spatial effects of wind direction and horizontal and vertical velocities, the terminal velocity of seeds (i.e., the constant descent velocity in calm air), and the height of seed release, partitioned into tree height and the distribution of seeds with tree height. The model was tested for two Pinus halepensis stands within the Mediterranean region of Israel, in which seed dispersal has been extensively monitored by seed traps. The predicted dispersal curve verified expectations of a positively skewed leptokurtic distribution and of peak location at some distance from a point source and at zero distance from an area source. Long-distance dispersal events occurred with very low frequency, but given the large seed crop in P. halepensis, even a small fraction should result in a considerable number of seeds dispersed far from their source. The model reliably simulates the observed dispersal pattern in a spatial resolution of 1 [m.sup.2] ([R.sup.2] between 60% and 90%), as revealed from comparisons of the predicted and observed proportions of seed dispersed to seed traps. A sensitivity analysis using Latin hypercube sampling along with stepwise multiple rank regression showed that the effects of the horizontal and vertical wind velocities on the dispersal distance override those of the biotic factors. This suggests that the synchronization of seed release with favorable winds is the most effective plant-controlled mechanism to increase the distance of dispersal in wind-dispersed species such as P. halepensis. Key words: dispersal curve; dispersal distance; height of release; long-distance dispersal; mechanistic models; model evaluation; Pinus halepensis; seed dispersal by wind; seed traps; stochasticity; terminal velocity; wind profile.

RAN NATHAN [1,3] URIEL N. SAFRIEL [1] IMANUEL NOY-MEIR [1,4] GABRIEL SCHILLER [2] Abstract. Spatiotemporal variation in the wind-generated dispersion pattern of Aleppo pine (Pin us halepensis) seeds was examined [...]