Quantifying responses of dung beetles to fire disturbance in tropical forests:the importance of trapping method and seasonality

Understanding how biodiversity responds to environmental changes is essential to provide the evidence-base that underpins conservation initiatives. The present study provides a standardized comparison between unbaited flight intercept traps (FIT) and baited pitfall traps (BPT) for sampling dung beetles. We examine the effectiveness of the two to assess fire disturbance effects and how trap performance is affected by seasonality. The study was carried out in a transitional forest between Cerrado (Brazilian Savanna) and Amazon Forest. Dung beetles were collected during one wet and one dry sampling season. The two methods sampled different portions of the local beetle assemblage. Both FIT and BPT were sensitive to fire disturbance during the wet season, but only BPT detected community differences during the dry season. Both traps showed similar correlation with environmental factors. Our results indicate that seasonality had a stronger effect than trap type, with BPT more effective and robust under low population numbers, and FIT more sensitive to fine scale heterogeneity patterns. This study shows the strengths and weaknesses of two commonly used methodologies for sampling dung beetles in tropical forests, as well as highlighting the importance of seasonality in shaping the results obtained by both sampling strategies

Bait attractiveness changes community metrics in dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae)

Species relative abundance (SRA) is an essential attribute of biotic communities, which can provide an accurate description of community structure. However, the sampling method used may have a direct influence on SRA quantification, since the use of attractants (e.g., baits, light, and pheromones) can introduce additional sources of variation in trap performance. We tested how sampling aided by baits affect community data and therefore alter derived metrics. We tested our hypothesis on dung beetles using data from flight interception traps (FITs) as a baseline to evaluate baited pitfall trap performance. Our objective was to assess the effect of bait attractiveness on estimates of SRA and assemblage metrics when sampled by pitfall traps baited with human feces.Dung beetles were sampled at three terra firme primary forest sites in the Brazilian Amazon. To achieve our objective, we (i) identified species with variable levels of attraction to pitfall baited with human feces; (ii) assessed differences in SRA; and (iii) assessed the effect of bait on the most commonly used diversity metrics derived from relative abundance (Shannon and Simpson indices). We identified species less and highly attracted to the baits used, because most attracted species showed greater relative abundances within baited pitfall traps samples compared with our baseline. Assemblages sampled by baited pitfall traps tend to show lower diversity and higher dominance than those sampled by unbaited FITs. Our findings suggest that for ecological questions focused on species relative abundance, baited pitfall traps may lead to inaccurate conclusions regarding assemblage structure. Although tested on dung beetles, we suggest that the same effect could be observed for other insect taxa that are also sampled with baited traps. We highlight a need for further studies on other groups to elucidate any potential effects of using baits

Trends in studies of Brazilian stream fish assemblages

Studies about fish assemblages in Brazilian streams have grown in recent years, however, it remains unclear whether this increase is followed by increments in the diversity of addressed topics and theoretical frameworks adopted by researchers. We performed a systematic search for Brazilian studies on stream fish assemblages recording study region, publication year, objectives, and spatial and temporal scales adopted. The number of studies is unevenly distributed among regions. Most papers describe the general structure of local fish assemblages and their scientific objectives have not varied through time. Studies have been conducted mainly at small temporal and spatial scales, though the latter is increasing over time. We argue for the need of focusing on recently developed ecological theories and frameworks, and expanding the temporal and spatial scales of studies. These changes will improve regional and local conservation policies, and the visibility of aquatic Brazilian research in the global scientific community. © 2016 Associação Brasileira de Ciência Ecológica e Conservaçã

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Tide assessment for the continental shelf situated in the southwestern Atlantic between the latitudes 19.8ºS and 21.2ºS

Abstract The astronomical tide was numerically simulated by the MOHID model for the South-Central Region of Espírito Santo State (Brazil), between latitudes 19.8ºS and 21.2ºS. The grid nesting technique was used to transpose the boundary conditions from the larger domain to a more refined local domain (spatial resolution around 450 m), with tidal harmonics provided by the TPXO tide inverse model as boundary conditions for the larger domain. Results from the numerical model were compared with both the pre-existing tide harmonics and the harmonics calculated from measured data. From the maps of phase, amplitude, tidal ellipses and residual currents the main tidal kinematic characteristics in the study area were described. On the continental shelf, the results showed that the physiography and bathymetry of the region play an important role in the distribution of tidal co-phases, co-amplitudes, ellipses and residual currents. The MOHID model was able to reproduce satisfactorily the astronomical tide and thus can be used to study the behaviour of the tidal propagation in continental shelf areas

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.Keywords: Social–ecological systems, Tropical forests, Land use, Interdisciplinary research, Sustainability, Trade-off

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost