Bruno Vilela

letsR: a new R package for data handling and analysis in macroecology

Summary 1. The current availability of large ecological data sets and the computational capacity to handle them have fostered the testing and development of theory at broad spatial and temporal scales. Macroecology has particularly benefited from this era of big data, but tools are still required to help transforming this data into information and knowledge. 2. Here, we present ‘letsR’, a package for the R statistical computing environment, designed to handle and analyse macroecological data such as species’ geographic distributions (polygons in shapefile format and point occurrences) and environmental variables (in raster format). The package also includes functions to obtain data on species’ habitat use, description year and current as well as temporal trends in conservation status as provided by the IUCN RedList online data base. 3. ‘letsR’ main functionalities are based on the presence–absence matrices that can be created with the package’s functions and from which other functions can be applied to generate, for example species richness rasters, geographic mid-points of species and species- and site-based attributes. 4. We exemplify the package’s functionality by describing and evaluating the geographic pattern of species’ description year in tailless amphibians. All data preparation and most analyses were made using the ‘letsR ’f unctions. Our example illustrates the package’s capability for conducting macroecological analyses under a single computer platform, potentially helping researchers to save time and effort in this endeavour.

Using Ecological Niche Models and Niche Analyses to Understand Speciation Patterns: The Case of Sister Neotropical Orchid Bees

The role of past connections between the two major South American forested biomes on current species distribution has been recognized a long time ago. Climatic oscillations that further separated these biomes have promoted parapatric speciation, in which many species had their continuous distribution split, giving rise to different but related species (i.e., different potential distributions and realized niche features). The distribution of many sister species of orchid bees follow this pattern. Here, using ecological niche models and niche analyses, we (1) tested the role of ecological niche differentiation on the divergence between sister orchid-bees (genera Eulaema and Eufriesea) from the Amazon and Atlantic forests, and (2) highlighted interesting areas for new surveys. Amazonian species occupied different realized niches than their Atlantic sister species. Conversely, species of sympatric but distantly related Eulaema bees occupied similar realized niches. Amazonian species had a wide potential distribution in South America, whereas Atlantic Forest species were more limited to the eastern coast of the continent. Additionally, we identified several areas in need of future surveys. Our results show that the realized niche of Atlantic-Amazonian sister species of orchid bees, which have been previously treated as allopatric populations of three species, had limited niche overlap and similarity. These findings agree with their current taxonomy, which treats each of those populations as distinct valid species.

Body size, extinction risk and knowledge bias in New World snakes.

Extinction risk and body size have been found to be related in various vertebrate groups, with larger species being more at risk than smaller ones. We checked whether this was also the case for snakes by investigating extinction risk–body size relationships in the New Worlds Colubroidea species. We used the IUCN Red List risk categories to assign each species to one of two broad levels of threat (Threatened and Non-Threatened) or to identify it as either Data Deficient or Not-Evaluated by the IUCN. We also included the year of description of each species in our analysis as this could affect the level of threat assigned to it (earlier described species had more time to gather information about them, which might have facilitated their evaluation). Also, species detectability could be a function of body size, with larger species tending to be described earlier, which could have an impact in extinction risk–body size relationships. We found a negative relationship between body size and description year, with large-bodied species being described earlier. Description year also varied among risk categories, with Non-Threatened species being described earlier than Threatened species and both species groups earlier than Data Deficient species. On average, Data Deficient species also presented smaller body sizes, while no size differences were detected between Threatened and Non-Threatened species. So it seems that smaller body sizes are related with species detectability, thus potentially affecting both when a species is described (smaller species tend to be described more recently) as well as the amount of information gathered about it (Data Deficient species tend to be smaller). Our data also indicated that if Data Deficient species were to be categorized as Threatened in the future, snake body size and extinction risk would be negatively related, contrasting with the opposite pattern commonly observed in other vertebrate groups.

Wallace: A flexible platform for reproducible modeling of species niches and distributions built for community expansion

Abtract 1.Scientific research increasingly calls for open-source software that is flexible, interactive, and expandable, while providing methodological guidance and reproducibility. Currently, many analyses in ecology are implemented with “black box” graphical user interfaces that lack flexibility or command-line interfaces that are infrequently used by non-specialists. 2.To help remedy this situation in the context of species distribution modeling, we created Wallace, an open and modular application with a richly documented graphical user interface to underlying R scripts that is flexible and highly interactive. 3.Wallace guides users from acquiring and processing data to building models and examining predictions. Additionally, it is designed to grow via community contributions of new modules to expand functionality. All results are downloadable, along with code to reproduce the analysis. 4.Wallace provides an example of an innovative platform to increase access to cutting-edge methods and encourage plurality in science and collaboration in software development. This article is protected by copyright. All rights reserved.

Stacked species distribution and macroecological models provide incongruent predictions of species richness for Drosophilidae in the Brazilian savanna

We tested the adequacy of two richness‐modelling approaches within the ‘spatially explicit species assemblage modelling’ (SESAM) framework for drosophilid flies in a tropical biome. The pattern of drosophilid species richness throughout the Brazilian savanna was investigated by comparing richness estimates from macroecological models (MEM) and stacked species distribution models (S‐SDM). We used occurrence records for macroecological modelling and to generate geographic ranges by modelling species’ niches, which were stacked to generate SDM richness. Richness predictions were compared between models and with empirical data from well‐sampled areas. The spatial variation in drosophilid richness for both estimates revealed more species in the central and south‐eastern regions of the biome. Nonetheless, MEM generated a more fragmented pattern than S‐SDM, with scattered patches of high richness. S‐SDM produced richness estimates nearer to the empirical values than MEM, which in turn strongly underestimated richness. The correlation between S‐SDM and observed richness suggests that climate is the major (indirect) driver of drosophilid richness in the Brazilian savanna. Richness estimates based on macroecological modelling are, however, almost certainly affected by inventory incompleteness and sampling bias. We emphasise that S‐SDM can be a valuable approach to explore species richness patterns in poorly sampled regions.

Reproduction of Agalychnis granulosa Cruz, 1989 (Anura: Hylidae)

We provide a detailed description of the reproduction of the tree frog Agalychnis granulosa, including its advertisement call. Agalychnis granulosa breeds in ponds and the backwaters of streams within primary forests. The breeding season started at the beginning of the wet season and ended two months before the beginning of the dry season. Males called at night in the vegetation around the ponds at a maximum distance of 5 m from the water. The call was composed of a single note with three to seven pulses and a dominant frequency ranging from 1490 to 2101 Hz. Oviposition sites included tree trunks, attached leaves, fallen leaves and bromeliad roots, and ranged in height from 0 to 300 cm above the water. Egg clutches were composed of approximately 45 eggs encapsulated by a transparent gelatinous matrix. Empty egg capsules (4–7 per clutch) were recorded in 36% of the clutches. Great plasticity was observed in the reproductive strategies of A. granulosa, probably reflecting the varying competition and predation at the different life stages of the species.

Hindcasting global population densities reveals forces enabling the origin of agriculture

The development and spread of agriculture changed fundamental characteristics of human societies1–3. However, the degree to which environmental and social conditions enabled the origins of agriculture remains contested4–6. We test three hypothesized links between the environment, population density and the origins of plant and animal domestication, a prerequisite for agriculture: (1) domestication arose as environmental conditions improved and population densities increased7 (surplus hypothesis); (2) populations needed domestication to overcome deteriorating environmental conditions (necessity hypothesis)8,9; (3) factors promoting domestication were distinct in each location10 (regional uniqueness hypothesis). We overcome previous data limitations with a statistical model, in which environmental, geographic and cultural variables capture 77% of the variation in population density among 220 foraging societies worldwide. We use this model to hindcast potential population densities across the globe from 21,000 to 4,000 years before present. Despite the timing of domestication varying by thousands of years, we show that improving environmental conditions favoured higher local population densities during periods when domestication arose in every known agricultural origin centre. Our results uncover a common, global factor that facilitated one of humanity’s most significant innovations and demonstrate that modelling ancestral demographic changes can illuminate major events deep in human history.Kavanagh and colleagues model global human population densities between 21,000 and 4,000 years ago and find that improved environmental conditions and increased potential for population growth facilitated the emergence of agricultural domestication.

No deaths in the desert: predicted responses of an arid-adapted bee and its two nesting trees suggest resilience in the face of warming climates

Species distribution modelling (SDM) has been applied to multiple bee species to examine how they may respond to future climate change. Those studies indicate a variety of likely responses to a warming climate. No SDM approaches, however, have been undertaken for arid‐adapted bees, despite their enormous diversity in xeric habitats. We applied SDM to an arid‐zone allodapine bee, Exoneurella tridentata Houston, 1976 (Apidae: Allodapini), and the two tree species it depends on for nesting substrate, Alectryon oleifolius (Desf.) S.T. Reynolds (Sapindaceae) and Acacia papyrocarpa Benth. (Fabaceae). Because of the complete dependency of this bee on these trees, there is the possibility that its vulnerability to climate change may be greater than for bee species that have broader nesting niches, such as ground or non‐specific cavity nesting. Using a variety of future climate scenarios, both optimistic and pessimistic, and also the bees nest plant species as predictor variables of its distribution in some modelling runs, we find that both tree species and E. tridentata are likely to be resilient to future climates. Our findings suggest that for Australian arid‐zone bees, at least vulnerability to future climate change may be very different than that for tropical or temperate taxa.

Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species.