On the scaling of activity in tropical forest mammals

Activity range – the amount of time spent active per day – is a fundamental aspect contributing to the optimization process by which animals achieve energetic balance. Based on their size and the nature of their diet, theoretical expectations are that larger carnivores need more time active to fulfil their energetic needs than do smaller ones and also more time active than similar‐sized non‐carnivores. Despite the relationship between daily activity, individual range and energy acquisition, large‐scale relationships between activity range and body mass among wild mammals have never been properly addressed. This study aimed to understand the scaling of activity range with body mass, while controlling for phylogeny and diet. We built simple empirical predictions for the scaling of activity range with body mass for mammals of different trophic guilds and used a phylogenetically controlled mixed model to test these predictions using activity records of 249 mammal populations (128 species) in 19 tropical forests (in 15 countries) obtained using camera traps. Our scaling model predicted a steeper scaling of activity range in carnivores (0.21) with higher levels of activity (higher intercept), and near‐zero scaling in herbivores (0.04). Empirical data showed that activity ranges scaled positively with body mass for carnivores (0.061), which also had higher intercept value, but not for herbivores, omnivores and insectivores, in general, corresponding with the predictions. Despite the many factors that shape animal activity at local scales, we found a general pattern showing that large carnivores need more time active in a day to meet their energetic demands. Introduction Activity range – the amount of time, in hours, spent active per day – is a fundamental outcome of the complex physiological and behavioral optimization process by which animals ensure that energy input keeps pace with energy output. In addition to basal metabolism, animals face costs of foraging, acquiring mates and shelter, building reserves for lean times and escaping predators (Carbone et al. 2007, Halle and Stenseth 2012). Environmental and ecological factors that vary through the day (e.g. luminosity, temperature, predation risk and competition avoidance) constrain activity to certain times, depending on morpho‐physiological limitations (Castillo‐Ruiz et al. 2012, Hut et al. 2012). In addition, animals need time to rest in order to recover their cognitive or physical condition (Siegel 2005). Thus, they must optimize their activity range to meet their resource requirements, while dealing with natural daily cycles and saving time for sleep/rest (Downes 2001, Siegel 2005, Cozzi et al. 2012). The resource requirements of mammals are related to basal metabolic rate, which scales positively with body mass (Kleiber 1932, Isaac and Carbone 2010), while predation risk decreases with body mass (Sinclair et al. 2003, Hopcraft et al. 2009). Because high predation risk constrains activity while high resource needs increases activity range (Cozzi et al. 2012, Suselbeek et al. 2014), the question arises whether and how activity range also scales with body mass. Day range (total distance travelled in a day) and home range (area in which animals perform their daily activities) scales positively with body mass and are key metrics to understand the resource requirements of an animal (McNab 1963, Kelt and Van Vuren 2001, Carbone et al. 2005, Tamburello et al. 2015). As activity range is related to space‐use metrics (i.e. home range and day range), it is hence, also related to the acquisition of energy. Given that, one might expect activity range to increase with body mass. However, we have a poor understanding of how this relationship actually looks. Previous work developed predictions of body mass scaling with day range (Garland 1983, Carbone et al. 2005) and travel speed (Carbone et al. 2007, Rowcliffe et al. 2016). From a simple physical viewpoint, activity range should equal the day range divided by average travel speed. It should thus be possible to infer the scaling of activity range with body mass from these relationships. Some of the variation in space use across species that is not explained by body mass is associated with different evolutionary histories and ecological traits (McNab 1963, Kelt and Van Vuren 2001, Price and Hopkins 2015, Tamburello et al. 2015). Diet is the most conspicuous of these, because primary and secondary productivity present different overall yields and accessibility for consumers (Jetz et al. 2004), which in turn influence individual movements (Carbone et al. 2005) and potentially activity range, when exploiting resources at different trophic levels. The nature of the diet aggravates the higher energetic demands of larger carnivores. Predators have considerable energetic constraints related to hunting and handling their prey (Gorman et al. 1998, Carbone et al. 1999) as animal prey can be rare, widely dispersed, unpredictable in time and space and not storable (Jetz et al. 2004, Carbone et al. 2007). Therefore, carnivores have the lowest energy supply rates (supply rate of usable resources available inside the home range), independent of body mass, when compared to other diet categories (Jetz et al. 2004) besides exploring larger areas and traveling greater daily distances (McNab 1963, Kelt and Van Vuren 2001, Carbone et al. 2005, Tamburello et al. 2015). Therefore, larger animals occupy larger areas than small ones, and carnivores occupy larger areas than do similar‐sized non‐carnivores (Jetz et al. 2004, Tamburello et al. 2015). To date, few studies have considered interspecific variation in activity range with body mass and other species traits. For example, van Schaik and Griffiths (1996) and Gómez et al. (2005) anecdotally suggested that larger mammal species are cathemeral (i.e. active day and night), which implies that they can be active during a larger proportion of the 24‐h cycle. Rowcliffe et al. (2014) found that activity range is positively correlated with body mass in tropical forest mammals in Panama. Ramesh et al. (2015) found a negative relationship between body mass and activity concentration (i.e. how concentrated in few hours is the activity of an animal during the day) in Indian mammals, also equating to a positive association between activity range and body mass. However, no study has explored variation in activity range across a diverse range of species, while controlling for phylogeny and diet. This has been, at least in part, due to a lack of consistent data available on a wide range of species. Recent work using camera traps (Oliveira‐Santos et al. 2013, Rowcliffe et al. 2014), however, has demonstrated that accurate estimates of activity range can be obtained from photographic records from camera traps. Given the large and rapidly increasing volume of camera‐trapping data available globally (Burton et al. 2015), these approaches, consistently applied across a wide range of studies, can provide an important basis for the large‐scale study of activity. Here, we provided simple empirical predictions for the scaling of activity range with body mass for mammals of different trophic guilds. To test these predictions, we estimated the activity range for 249 populations of 128 terrestrial mammal species across 19 tropical forests, and used a phylogenetically controlled mixed model to determine how activity range scales with body mass by diet. As larger animals occupy larger areas than small ones, and carnivores occupy larger areas than do similar‐sized non‐carnivores (Jetz et al. 2004), we hypothesize that carnivores will present a higher scaling of activity range with body mass and also higher activity ranges for a given mass (higher intercept) when compared to herbivores, omnivores and insectivores

Standardized Assessment of Biodiversity Trends in Tropical Forest Protected Areas: The End Is Not in Sight

Extinction rates in the Anthropocene are three orders of magnitude higher than background and disproportionately occur in the tropics, home of half the world’s species. Despite global efforts to combat tropical species extinctions, lack of high-quality, objective information on tropical biodiversity has hampered quantitative evaluation of conservation strategies. In particular, the scarcity of population-level monitoring in tropical forests has stymied assessment of biodiversity outcomes, such as the status and trends of animal populations in protected areas. Here, we evaluate occupancy trends for 511 populations of terrestrial mammals and birds, representing 244 species from 15 tropical forest protected areas on three continents. For the first time to our knowledge, we use annual surveys from tropical forests worldwide that employ a standardized camera trapping protocol, and we compute data analytics that correct for imperfect detection. We found that occupancy declined in 22%, increased in 17%, and exhibited no change in 22% of populations during the last 3–8 years, while 39% of populations were detected too infrequently to assess occupancy changes. Despite extensive variability in occupancy trends, these 15 tropical protected areas have not exhibited systematic declines in biodiversity (i.e., occupancy, richness, or evenness) at the community level. Our results differ from reports of widespread biodiversity declines based on aggregated secondary data and expert opinion and suggest less extreme deterioration in tropical forest protected areas. We simultaneously fill an important conservation data gap and demonstrate the value of large-scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional sites, ecosystems, and monitoring methods. In an era of catastrophic biodiversity loss, robust indicators produced from standardized monitoring infrastructure are critical to accurately assess population outcomes and identify conservation strategies that can avert biodiversity collapse. © 2016 Beaudrot et al

Amazonia Camtrap: a data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest.

Abstract : The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scatteredacross the published, peer-reviewed, and gray literature and in unpublishedraw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazonregions to compile the most extensive data set of inventories of mammal,bird, and reptile species ever assembled for the area. The complete data setcomprises 154,123 records of 317 species (185 birds, 119 mammals, and13 reptiles) gathered from surveys from the Amazonian portion of eightcountries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru,Suriname, and Venezuela). The most frequently recorded species per taxawere: mammals:Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles:Tupinambis teguixin(716 records). The infor-mation detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a moreaccurate evaluation of the effects of habitat loss, fragmentation, climatechange, and other human-mediated defaunation processes in one of themost important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when usingits data in publications and we also request that researchers and educator sinform us of how they are using these data

Pan-tropical prediction of forest structure from the largest trees

Aim Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location Time period Pan-tropical. Early 21st century. Major taxa studied Methods Woody plants. Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results Main conclusions Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50-70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change

Amazonia camtrap: A dataset of mammal, bird, and reptile species recorded with camera traps in the Amazon forest.

The Amazon forest has the highest biodiversity on earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed and grey literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive dataset of inventories of mammal, bird and reptile species ever assembled for the area. The complete dataset comprises 154,123 records of 317 species (185 birds, 119 mammals and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname and Venezuela). The most frequently recorded species per taxa were: mammals - Cuniculus paca (11,907 records); birds - Pauxi tuberosa (3,713 records); and reptiles - Tupinambis teguixin (716 records). The information detailed in this data paper opens-up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The dataset is not copyright restricted; please cite this data-paper when using its data in publications and we also request that researchers and educators inform us of how they are using this data. [Abstract copyright: This article is protected by copyright. All rights reserved.

Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan-tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change