The problem and promise of scale in multilayer animal social networks

Scale remains a foundational concept in ecology.Spatial scale,for instance,has become a central consideration in the way we understand landscape ecology and animal space use.Meanwhile,scale-dependent social processes can range from fine scale interactions to co-occurrence and overlapping home ranges.Furthermore,sociality can vary within and across seasons.Multilayer networks promise the explicit integration of the social,spatial,and temporal contexts.Given the complex interplay of sociality and animal space use in heterogeneous landscapes,there remains an important gap in our understanding of the influence of scale on animal social networks.Using an empirical case study,we discuss ways of considering social,spatial,and temporal scale in the context of multilayer caribou social networks.Effective integration of social and spatial processes,including biologically meaningful scales,within the context of animal social networks is an emerging area of research.We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.     

Potential of a no‐take marine reserve to protect home ranges of anadromous brown trout (Salmo trutta)

The extent to which no‐take marine reserves can benefit anadromous species requires examination. Here, we used acoustic telemetry to investigate the spatial behavior of anadromous brown trout (sea trout, Salmo trutta) in relation to a small marine reserve (~1.5 km²) located inside a fjord on the Norwegian Skagerrak coast. On average, sea trout spent 42.3 % (±5.0% SE) of their time in the fjord within the reserve, a proportion similar to the area of the reserve relative to that of the fjord. On average, sea trout tagged inside the reserve received the most protection, although the level of protection decreased marginally with increasing home range size. Furthermore, individuals tagged outside the reserve received more protection with increasing home range size, potentially opposing selection toward smaller home range sizes inflicted on fish residing within reserves, or through selective fishing methods like angling. Monthly sea trout home ranges in the marine environment were on average smaller than the reserve, with a mean of 0.430 (±0.0265 SE) km². Hence, the reserve is large enough to protect the full home range of some individuals residing in the reserve. Synthesis and applications: In general, the reserve protects sea trout to a varying degree depending on their individual behavior. These findings highlight evolutionary implications of spatial protection and can guide managers in the design of marine reserves and networks that preserve variation in target species' home range size and movement behavior.     

An evaluation of behavior inferences from Bayesian state‐space models: A case study with the Pacific walrus

State‐space models offer researchers an objective approach to modeling complex animal location data sets, and state‐space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state‐space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two‐state discrete‐time continuous‐space Bayesian state‐space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state‐space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two‐state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state‐space models, and reconcile these parameters with the study species and its expected behaviors.     

The digging‐in effect on ant studies with pitfall traps: influence of type of habitat and sampling time

Pitfall traps are among the most common sampling methods used for the study of ants. There are many types of traps and many possible ways of using them. The various methodologies may introduce biases in sampling. One possible bias may be caused by the digging‐in effect (DE), resulting in higher catches of ants immediately after traps are set in the ground which subsequently decline. In this study, we performed two experiments to verify the consequences of the DE for ants in a Mediterranean ecosystem. In the first experiment we distinguished between two types of habitats: closed and open (i.e., with or without shrub or tree cover). The second experiment was carried out in a homogeneous pasture where the time of prevalence of the DE was verified, investigating the duration of the effect. The results indicate differences between communities in the first 24 h after setting of the traps, which had disappeared after 48 h. This does not dismiss the possibility of certain species being affected either positively (increase in captures) or negatively (decrease). Changes in species composition, determining whether the DE was manifested or not, differed among habitat types.     

Spatio‐temporal variation of biting flies,Stomoxys spp. (Diptera: Muscidae), along a man‐made disturbance gradient,from primary forest to the city of Makokou (North‐East,Gabon)

Understanding the pattern of abundance of vector populations is important to control the potential of transmission of associated pathogens. The pattern of abundance of Stomoxys Geoffroy, an ubiquitous blood‐sucking fly, is poorly known in tropical Africa. In this study, we investigated the spatio‐temporal pattern of abundance of the Stomoxys genus along a gradient of man‐made disturbance in north‐eastern Gabon. Three sites (one in primary forest, one in secondary forest and one in a man‐made environment) were monitored during 13 months using Vavoua traps. Seven species and subspecies were found to live in sympatry, but with distinct patterns of abundance with respect to space and time. The most abundant species was Stomoxys transvittatus Villeneuve, whereas the rarest species was S. xanthomelas Roubaud. Stomoxys calcitrans Linné was preferentially found in man‐made environments, whereas S. xanthomelas was preferentially found in primary forest. Stomoxys abundance was the greatest in secondary forest, then in man‐made environments and finally in primary forest. A seasonal variation in Stomoxys abundance was also found. In conclusion, forest degradation and deforestation are likely both to favour the concentration of populations of Stomoxys, and to change the specific composition of the Stomoxys community.     

The effects of sex hormones on immune function: a meta‐analysis

The effects of sex hormones on immune function have received much attention, especially following the proposal of the immunocompetence handicap hypothesis. Many studies, both experimental and correlational, have been conducted to test the relationship between immune function and the sex hormones testosterone in males and oestrogen in females. However, the results are mixed. We conducted four cross‐species meta‐analyses to investigate the relationship between sex hormones and immune function: (i) the effect of testosterone manipulation on immune function in males, (ii) the correlation between circulating testosterone level and immune function in males, (iii) the effect of oestrogen manipulation on immune function in females, and (iv) the correlation between circulating oestrogen level and immune function in females. The results from the experimental studies showed that testosterone had a medium‐sized immunosuppressive effect on immune function. The effect of oestrogen, on the other hand, depended on the immune measure used. Oestrogen suppressed cell‐mediated immune function while reducing parasite loads. The overall correlation (meta‐analytic relationship) between circulating sex hormone level and immune function was not statistically significant for either testosterone or oestrogen despite the power of meta‐analysis. These results suggest that correlational studies have limited value for testing the effects of sex hormones on immune function. We found little evidence of publication bias in the four data sets using indirect tests. There was a weak and positive relationship between year of publication and effect size for experimental studies of testosterone that became non‐significant after we controlled for castration and immune measure, suggesting that the temporal trend was due to changes in these moderators over time. Graphical analyses suggest that the temporal trend was due to an increased use of cytokine measures across time. We found substantial heterogeneity in effect sizes, except in correlational studies of testosterone, even after we accounted for the relevant random and fixed factors. In conclusion, our results provide good evidence that testosterone suppresses immune function and that the effect of oestrogen varies depending on the immune measure used.     

The mid‐domain effect matters: simulation analyses of range‐size distribution data from Mount Kinabalu,Borneo

Aim In simulation exercises, mid‐domain peaks in species richness arise as a result of the random placement of modelled species ranges within simulated geometric constraints. This has been called the mid‐domain effect (MDE). Where close correspondence is found between such simulations and empirical data, it is not possible to reject the hypothesis that empirical species richness patterns result from the MDE rather than being the outcome (wholly or largely) of other factors. To separate the influence of the MDE from other factors we therefore need to evaluate variables other than species richness. The distribution of range sizes gives different predictions between models including the MDE or not. Here, we produce predictions for species richness and distribution of range sizes from one model without the MDE and from two MDE models: a classical MDE model encompassing only species with their entire range within the domain (range‐restricted MDE), and a model encompassing all species with the theoretical midpoint within the domain (midpoint‐restricted MDE). These predictions are compared with observations from the elevational pattern of range‐size distributions and species richness of vascular plants. Location Mount Kinabalu, Borneo. Methods The data set analysed comprises more than 28,000 plant specimens with information on elevation. Species ranges are simulated with various assumptions for the three models, and the species simulated are subsequently subjected to a sampling that simulates the actual collection of species on Mount Kinabalu. The resulting pattern of species richness and species range‐size distributions are compared with the observed pattern. Results The comparison of simulated and observed patterns indicates that an underlying monotonically decreasing trend in species richness with elevation is essential to explain fully the observed pattern of richness and range size. When the underlying trend is accounted for, the MDE model that restricts the distributions of theoretical midpoints performs better than both the classical MDE model and the model that does not incorporate geometric constraints. Main conclusions Of the three models evaluated here, the midpoint‐restricted MDE model is found to be the best for explaining species richness and species range‐size distributions on Mount Kinabalu.     

The importance of rare species: a trait‐based assessment of rare species contributions to functional diversity and possible ecosystem function in tall‐grass prairies

The majority of species in ecosystems are rare, but the ecosystem consequences of losing rare species are poorly known. To understand how rare species may influence ecosystem functioning, this study quantifies the contribution of species based on their relative level of rarity to community functional diversity using a trait‐based approach. Given that rarity can be defined in several different ways, we use four different definitions of rarity: abundance (mean and maximum), geographic range, and habitat specificity. We find that rarer species contribute to functional diversity when rarity is defined by maximum abundance, geographic range, and habitat specificity. However, rarer species are functionally redundant when rarity is defined by mean abundance. Furthermore, when using abundance‐weighted analyses, we find that rare species typically contribute significantly less to functional diversity than common species due to their low abundances. These results suggest that rare species have the potential to play an important role in ecosystem functioning, either by offering novel contributions to functional diversity or via functional redundancy depending on how rare species are defined. Yet, these contributions are likely to be greatest if the abundance of rare species increases due to environmental change. We argue that given the paucity of data on rare species, understanding the contribution of rare species to community functional diversity is an important first step to understanding the potential role of rare species in ecosystem functioning.     

Range position and climate sensitivity: The structure of among‐population demographic responses to climatic variation

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long‐term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long‐term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species‐interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.     

The extraordinary journey of Peperomia subgenus Tildenia (Piperaceae): insights into diversification and colonization patterns from its cradle in Peru to the Trans‐Mexican Volcanic Belt

Aim Peperomia subgenus Tildenia consists of c. 60 species growing in seasonal habitats of Neotropical mountain areas from Mexico to Argentina. The subgenus can be split geographically, with almost equal diversity in the Northern Hemisphere (centred in Mexico and Guatemala) and in the Southern Hemisphere (centred in Peru and Bolivia). Only a few species are known from a limited number of localities between these two hotspots. As such, Tildenia is an ideal candidate with which to test time, direction and mode of migration of high mountain taxa against the background of the ‘Great American Biotic Interchange’. Location The Andes with focus on the Central Andes, and the Mexican mountain chains, especially the Trans‐Mexican Volcanic Belt. Methods To elucidate the spatio‐temporal origin, subsequent colonization and radiation of Tildenia, we combine Bayesian phylogenetics based on the chloroplast trnK–matK–psbA region, georeferenced distribution data, and fossil calibrated molecular dating approaches using both penalized likelihood and relaxed phylogenetics. Reconstruction of the ancestral distribution area was performed using dispersal–vicariance analysis and dispersal–extinction–cladogenesis. Results Peperomia subgenus Tildenia is subdivided into six Andean clades and one Mexican and Central American clade originating from a north/central Peruvian ancestor. Molecular dating approaches converge on a stem age of c. 38 Ma for Tildenia and a mostly Miocene diversification and colonization. Main conclusions We detect a strong correlation between diversification of Tildenia and orogenetic events in the respective distribution centres. In the Andes, distribution was influenced by the Altiplano–Eastern Cordillera System as well as the Amotape‐Huancabamba Zone, where the latter serves as both migration barrier and migration bridge for different clades. In contrast to most studies of high‐elevation taxa, we provide support for a south–north colonization towards Central America and Mexico, and provide additional, independent evidence for the latest view on the timing of the Great American Biotic Interchange. In Mexico, the Trans‐Mexican Volcanic Belt has played a major role in more recent radiations together with climatic oscillation and the formation of refugia.