Landscape composition regulates the spillover of beneficial insects between forest remnants and adjacent coffee plantations

Published versionCross-habitat movements are crucial for persistence of beneficial insects in agricultural landscapes; however, much remains unknown on how landscape structure affects the spillover of beneficial insects between crop and non-crop habitats. To estimate the effects of landscape structure on the spillover of beneficial insects we sampled predatory wasps in pairs of forest remnants and adjacent coffee plantations along a gradient of landscape composition and configuration. We used dissimilarity indices to estimate wasp spillover and we assumed that high dissimilarity means less flow (and thus less spillover) between forest and coffee habitats. We collected a total of 9847 wasps classified into 75 species and 23 genera. Wasp dissimilarity between habitats decreased with increasing forest cover in the surrounding landscape and did not respond to landscape diversity, edge density or pesticide usage. Our findings suggest that wasps forage in coffee plantations but seem to rely on forest remnants to find unmanaged nesting sites and a constant supply of resources that are not available in the agricultural matrix, and are neither in landscapes with high compositional diversity or edge density. Therefore, forest conservation and restoration should be incorporated in agro-environmental schemes designed to improve the spillover of beneficial insects and provision of ecosystem services within coffee farmlands

Spatial heterogeneity and habitat configuration overcome habitat composition influences on alpha and beta mammal diversity

The effects of habitat fragmentation on different taxa and ecosystems are subject to intense debate, and disentangling them is of utmost importance to support conservation and management strategies. We evaluated the importance of landscape composition and configuration, and spatial heterogeneity to explain α‐ and β‐diversity of mammals across a gradient of percent woody cover and land use diversity. We expected species richness to be positively related to all predictive variables, with the strongest relationship with landscape composition and configuration, and spatial heterogeneity respectively. We also expected landscape to influence β‐diversity in the same order of importance expected for species richness, with a stronger influence on nestedness due to deterministic loss of species more sensitive to habitat disturbance. We analyzed landscape structure using: (a) landscape metrics based on thematic maps and (b) image texture of a vegetation index. We compared a set of univariate explanatory models of species richness using AIC, and evaluated how dissimilarities in landscape composition and configuration and spatial heterogeneity affect β‐diversity components using a Multiple Regression on distance Matrix. Contrary with our expectations, landscape configuration was the main driver of species richness, followed by spatial heterogeneity and last by landscape composition. Nestedness was explained, in order of importance, by spatial heterogeneity, landscape configuration, and landscape composition. Although conservation policies tend to focus mainly on habitat amount, we advocate that landscape management must include strategies to preserve and improve habitat quality and complexity in natural patches and the surrounding matrix, enabling landscapes to harbor high species diversity

ATLANTIC BIRDS: a data set of bird species from the Brazilian Atlantic Forest

South America holds 30% of the world's avifauna, with the Atlantic Forest representing one of the richest regions of the Neotropics. Here we have compiled a data set on Brazilian Atlantic Forest bird occurrence (150,423) and abundance samples (N = 832 bird species; 33,119 bird individuals) using multiple methods, including qualitative surveys, mist nets, point counts, and line transects). We used four main sources of data: museum collections, on-line databases, literature sources, and unpublished reports. The data set comprises 4,122 localities and data from 1815 to 2017. Most studies were conducted in the Florestas de Interior (1,510 localities) and Serra do Mar (1,280 localities) biogeographic sub-regions. Considering the three main quantitative methods (mist net, point count, and line transect), we compiled abundance data for 745 species in 576 communities. In the data set, the most frequent species were Basileuterus culicivorus, Cyclaris gujanensis, and Conophaga lineata. There were 71 singletons, such as Lipaugus conditus and Calyptura cristata. We suggest that this small number of records reinforces the critical situation of these taxa in the Atlantic Forest. The information provided in this data set can be used for macroecological studies and to foster conservation strategies in this biodiversity hotspot. No copyright restrictions are associated with the data set. Please cite this Data Paper if data are used in publications and teaching events. © 2017 by the Ecological Society of Americ

Bird occurrence, ecological traits and landscape predictors in southeast Brazil

This database provide data on bird species occurrence in forest edges, pastures and eucalyptus plantation across a wide region of fragmented Atlantic Forest, southeastern Brazil. Additonally, information on species ecological traits, sampling geographical coordinates, and landscape attributes are available. Detailed information on how these data were collated are found in the Methods section of the manuscript

Use of Active Sensors in Coffee Cultivation for Monitoring Crop Yield

Monitoring the spatial variability of agricultural variables is a main step in implementing precision agriculture practices. Active optical sensors (AOS), with their instrumentation directly on agricultural machines, are suitable and make it possible to obtain high-frequency data. This study aimed to evaluate the potential of AOS to map the spatial and temporal variability of coffee crop yields, as well as to establish guidelines for the acquisition of AOS data for sensing the sides of a coffee plant, allowing the evaluation of large commercial fields. The study was conducted in a commercial coffee area of 10.24 ha, cultivated with the Catuaí 144 variety. Data collection was performed with six Crop Circle ACS 430 sensors (Holland Scientific, Lincoln, NE, USA) and two N-Sensor NG sensors (Yara International, Dülmen, Germany). Seven field expeditions were made to collect data using the optical sensors during 2019 and 2021, obtaining data during the flowering, fruit-filling and fruit maturation phases (pre-harvest), and post-harvest. The results showed that the different faces of the same plant present a different Pearson’s correlation coefficient (r) to its yield, obtained with a yield monitor on the harvester. The face with the highest exposure to solar radiation presented a slightly higher correlation to yield (−0.34 ≤ r ≤ −0.17) when compared with the face with less exposure (−0.27 ≤ r ≤ −0.15). In addition, it was observed that the vegetation indices measured at the beginning of the coffee cycle (before the rainy season that starts in October) present a positive correlation to the coffee yield of that same year (0.73 ≤ r ≤ 0.91). On the other hand, this relationship is changed after the beginning of the rain season, at which time the vegetation index increases abruptly, inverting the correlation with the yield after that (−0.93 ≤ r ≤ −0.77). Furthermore, it was observed that, due to the biennial nature of coffee production, the vegetation index acquired at a specific time has an inverted relationship when compared with the yield of that year and to the yield of the following (or previous) year

Use of Active Sensors in Coffee Cultivation for Monitoring Crop Yield

Monitoring the spatial variability of agricultural variables is a main step in implementing precision agriculture practices. Active optical sensors (AOS), with their instrumentation directly on agricultural machines, are suitable and make it possible to obtain high-frequency data. This study aimed to evaluate the potential of AOS to map the spatial and temporal variability of coffee crop yields, as well as to establish guidelines for the acquisition of AOS data for sensing the sides of a coffee plant, allowing the evaluation of large commercial fields. The study was conducted in a commercial coffee area of 10.24 ha, cultivated with the Catuaí 144 variety. Data collection was performed with six Crop Circle ACS 430 sensors (Holland Scientific, Lincoln, NE, USA) and two N-Sensor NG sensors (Yara International, Dülmen, Germany). Seven field expeditions were made to collect data using the optical sensors during 2019 and 2021, obtaining data during the flowering, fruit-filling and fruit maturation phases (pre-harvest), and post-harvest. The results showed that the different faces of the same plant present a different Pearson’s correlation coefficient (r) to its yield, obtained with a yield monitor on the harvester. The face with the highest exposure to solar radiation presented a slightly higher correlation to yield (−0.34 ≤ r ≤ −0.17) when compared with the face with less exposure (−0.27 ≤ r ≤ −0.15). In addition, it was observed that the vegetation indices measured at the beginning of the coffee cycle (before the rainy season that starts in October) present a positive correlation to the coffee yield of that same year (0.73 ≤ r ≤ 0.91). On the other hand, this relationship is changed after the beginning of the rain season, at which time the vegetation index increases abruptly, inverting the correlation with the yield after that (−0.93 ≤ r ≤ −0.77). Furthermore, it was observed that, due to the biennial nature of coffee production, the vegetation index acquired at a specific time has an inverted relationship when compared with the yield of that year and to the yield of the following (or previous) year

Edge and land use effects on dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) in Brazilian cerrado vegetation

The Edge Influence is one of the most pervasive effects of habitat fragmentation, as many forest remnants in anthropogenic landscapes are within 100 m of edges. Forest remnants may also affect the surrounding anthropogenic matrix, possibly resulting in a matrix–edge–remnant diversity gradient for some species groups. We sampled dung beetles in 15 agricultural landscapes using pitfall traps placed along transects in matrix–edge–remnant gradients. The remnants were a native savanna-like vegetation, the cerrado, and the matrix was composed of three human-dominated environments (sugarcane, eucalyptus, pasture). More species were observed in cerrado remnants than in adjacent land uses. Dung beetles were also more abundant in the cerrado than in the landscape matrix of sugarcane and eucalypt, but not of pasture. Dung beetles were severely affected by anthropogenic land uses, and notwithstanding their high abundance in some land uses such as pasture, the species richness in these areas tended to be smaller than in the cerrado remnants. We also found that the influence of the edge was evident only for abundance, particularly in landscapes with a pasture matrix. However, this land use disrupts the species composition of communities, indicating that communities located in cerrado and pasture have a distinct species composition, and that both communities are affected by edge distance. Thus, anthropogenic land uses may severely affect dung beetles, and this impact can extend to communities located in cerrado remnants as well as to those in matrices, with possible consequences for ecological processes such as decomposition and nutrient cycling. © 2016, Springer International Publishing Switzerland

Data from: Landscape Corridors (LSCorridors): a new software package for modeling ecological corridors based on landscape patterns and species requirements

1.Maintaining connectivity is one of the main challenges for biodiversity conservation worldwide. Ecological corridors are important to maintain landscape connectivity, but their efficiency depends on landscape patterns and species responses at different spatial extents and landscape contexts. 2.We developed a new ecologically oriented free software package, LandScape Corridors (LSCorridors), to improve ecological corridor design by considering biodiversity responses to landscape attributes at a variety of spatial extents. LSCorridors considers stochastic variation, species perception and landscape influence on organisms in the design of ecological corridors. In addition to the least cost path algorithm, we propose four different methods for the simulation of multiple-path functional ecological corridors. One method uses the information for each pixel separately whereas the three other methods permit corridor simulation considering the landscape context at different spatial extents. 3.LSCorridors permits to simulate corridors for species with different requirements and considers that different species perceive and respond to the surrounding landscape in different ways, as many species may choose to move through areas that may not be the most permeable ones in the landscape. Two parameters in LSCorridors modulate the stochasticity in corridors simulations. The first parameter is the level of variability added to the input resistance map in each simulation, resulting in more variable and spatially spread-out corridors. The other parameter is the spatial extent that may influence each pixel; larger extents result in larger spatial zones affecting each pixel during corridors simulations. Additionally, when considering spatial influence, the simulations may be performed for species highly, medially or less sensitive to habitat quality. 4.Some currently available software are not free or depend on a paid GIS software to work. In addition, some software do not support large matrices in their simulations, limiting their use. LSCorridors is designed to deal with large rasters, is based on strictly freeware software, and is freely available online. This allows the users to implement new methods for modeling multi-scale and ecologically-based corridors. 5.LSCorridors is a potential tool for the identification of protected areas, as corridor simulation considers species movement and landscape connectivity, essential characteristics to aid in large-scale biodiversity conservation, especially in anthropogenic landscapes. LSCorridors provides what we may call a zone for conservation, showing a set of connected areas in the landscape which may be ordered according to their potential for ecological corridors or which may be used as an aid for conservation strategies or ecological restoration projects

Environmental heterogeneity and sampling relevance areas in an Atlantic forest endemism region

The knowledge of the diversity, richness, and distribution of tropical organisms are poorly understood, and a plethora of new species are still being described even among groups considered well-known. As a result, this inadequate knowledge of the biodiversity has hampered the species' conservation. Thus, sampling efforts must be urgently optimized to survey important and unique areas and to better allocated the scarce conservation resources, especially in the tropical and developing countries that harbor much of the world biodiversity. We assessed the most relevant regions in terms of environmental dissimilarity for sampling vertebrates (amphibians, birds, and mammals) in the Pernambuco Endemism Center (PEC), located in Atlantic forest and the most threatened region in South America, where only about 1% of remaining forests are protected. We found that 8-41% of the PEC areas showed high sampling relevance for all vertebrate groups, with the non-coastal areas of the PEC presenting the highest sampling relevance in terms of environmental dissimilarity. For all vertebrate groups, the sites with the highest sampling relevance are threatened by fragmentation, and sampling efforts must be allocated to these areas before they are totally converted into human-modified landscapes. (C) 2021 Associacao Brasileira de Ciencia Ecologica e Conservacao. Published by Elsevier Editora Ltda