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Brood census data
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In flowering plants, pollinators contribute to gene flow while they also respond to variation in plant traits together determined by genetic, epigenetic and environmental sources of variation. Consequently, a correlation between abundance and diversity of pollinators and the genetic and epigenetic characteristics of plant populations such as diversity or distinctiveness is expected. However, no study has explored these long-term dimensions of plant-pollinator interactions. Mediterranean narrow endemics often exhibit unexpectedly high levels of population genetic and epigenetic diversity. We hypothesize that pollinators may contribute to explain this pattern. Specifically, given the higher sensitivity of small, isolated population to gene flow, we expect a stronger association of pollinators with population genetic and epigenetic variability in narrow endemics than in widely distributed congeners. We studied five pairs of congeneric plant species, consisting of one narrow endemic with a restricted distribution and one widespread congener, found in the Sierra de Cazorla mountains (SE Spain). We characterized the pollinators in up to three populations per species to estimate their diversity and visitation rates. Additionally, we calculated the genetic and epigenetic diversity and distinctiveness of each population using AFLP markers and methylation-sensitive AFLP markers (MSAP), respectively. We assessed the relationship between pollinator diversity and visitation rates. The diversity of pollinators did not vary according to the plant´s distribution range, but visitation rate was higher in widespread species. As predicted, only narrow endemics showed a significant association between pollinators and their population genetic and epigenetic characteristics. Specifically, higher pollinator diversity and visitation rates entailed higher population genetic diversity and lower epigenetic distinctiveness. This work shows the importance of investigating the relationship between pollinator diversity and population genetics and epigenetics to better understand the evolution of plant rarity. Methods This raw data was obtained from field direct observations of pollinator visits on 14 plant species. It includes the following information:
Plant genus and species. Plant distribution range. Plant population. Census id (each census consists on 3 minutes observation). Pollinator id. Number of open flowers at the census time. Number of visited flowers per pollinator id and census time.
Clonality is a widespread life history trait in flowering plants that may be essential for population persistence, especially in environments where sexual reproduction is unpredictable. Frequent clonal reproduction, however, could hinder sexual reproduction by spatially aggregating ramets that compete with seedlings and reduce inter-genet pollination. Nevertheless, the role of clonality in relation to variable sexual reproduction in population dynamics is often overlooked. We combined population matrix models and pollination experiments to compare the demographic contributions of clonal and sexual reproduction in three Dicentra canadensis populations, one in a well-forested landscape and two in isolated forest remnants. We constructed stage-based transition matrices from 3 years of census data to evaluate annual population growth rates, λ. We used loop analysis to evaluate the relative contribution of different reproductive pathways to λ. Despite strong temporal and spatial variation in...
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Functional traits help understand biological diversity and the mechanism by which ecological communities are structured and how they respond to the environment. For example, the high tree species diversity within tropical forests can be grouped into a few functional attributes like wood density, size, and dependence on animal pollination or seed dispersal. However, little is known about how these traits influence animal taxonomic and functional diversity. We carried out a vegetation census on six plots (20 x 100 m) within the National Forest of Carajás (Amazon biome) to identify forest canopy species and their functional traits. Within the same plot, we also applied three bee sampling methods (entomological nets, honey traps, and scent traps). By characterizing the functional traits of trees and bees, we were able to predict bee functional diversity better than with taxonomic diversity alone via combinations of tree traits like size, wood density, dependence on pollinators, and extinction risk. We found that the basal area of trees with low wood density was negatively associated with small, eusocial tree cavity-nesting bees. The richness of medium-sized solitary bees was positively associated with the richness and abundance of trees with extinction risk. The community dominance (average diameter at the basal area) of pollinator—dependent trees was negatively associated with the richness of aboveground and cavity-nesting bees. Our findings suggest that tree community composition limits the availability of nesting resources for specific bee groups. Moreover, the presence of trees with high conservation value was associated with a greater variety of bee traits and was the only metric associated with overall bee richness. As expected, functional traits shed light on the mechanism that might drive high diversity within tropical forests. Moreover, there seems to be complementarity in terms of conservation value and carbon stock potential, as areas harboring tree species with extinction risk and higher wood density are also those with overall greater bee and functional diversity. Finally, our study can contribute to the restoration of plant—pollinator community by providing an understanding of the vegetation community that contributes to biodiversity maintenance.
Methods
1. Vegetation sampling
The Carajas National Forest protected area comprises a set of mountain ranges covered with pristine Amazon Forest. Within the National Forest, we implemented vegetation census on 6 plots. Each plot consisted of a 20 m x 100 m area in which all the plants whose diameter at breast height (DBH) was greater than 10 cm were identified to the species level, and their DBH was measured. The minimum distance between plots was more than 2.5 km. For all trees, palms, and vines, we measured height, and DBH and assessed wood density and dependency on bee pollination from the literature (Table S3). For species with no data available (20%) we estimate wood density using the average wood density among the genera of that same individual for which wood density was missing. As we focused on trees, palms and vines, one vegetation census was performed in each plot over two years (2021 and 2022) of sampling, and the vegetation census occurred independently of bee sampling (2022).
Additionally, we classified species according to their vulnerability to extinction status, based on the International Union for Conservation of Nature (IUCN) Red List. Species were considered threatened if they were classified as endangered, vulnerable, or near threatened. The species classification is based upon one or multiple criteria, including population size decline, geographic range, and very small populations. Species classification is based upon one or multiple criteria, including population size decline, geographic range, and very small populations. Although threatened to extinction is not a function associated with a process, it can be considered a function in terms of a species’ shared susceptibility to stressors (all traits are functional traits).
We considered five functional traits: i) Plant size (DBH), ii) wood density, iii) height, iv) melittophily and v) extinction risk (threatened or not). To characterize the community considering categorical traits, we considered the abundance of each level (e.g., the abundance of melittophilous plants) and the aggregated plant size (sum of the DBH of individuals with a specific trait level) to characterize the dominance of functional traits in the community. For wood density, for example, we first categorized trees using a wood density threshold of 0.68 g/cc (median), grouping species as either having low wood density or high wood density. Then, for each category, we calculated the average, maximum value and accumulated total plant size (sum) of low- and high—wood—density trees. The same was done for all bee pollination dependent species and for all tree species with some level of extinction threat.
2. Bee sampling
We applied three complementary protocols for sampling bees in each vegetation sampling plot: 1) We actively collected bees using entomological nets by sampling across flowering plants in the understory. We collected bees from flowers by walking in the sampling area (plot) for two non-consecutive hours, one-hour sampling, at 30-minute intervals, followed by a second hour of sampling. Sampling was performed by one researcher in each area between 7 and 10 am. Three independent researchers collected the samples at the same time; thus, all areas were sampled on two consecutive days. 2) We used a honey trap, which consisted of a mixture of honey and water (1:2, i.e. 250 ml of honey and 500 ml of water) that was sprayed on a square meter on a plant with broad leaves chosen at random at the same sampling point. We performed two 10-minute bee samples (using entomological nets) from the honey traps (first between 8 and 9 am, and second between 10 and 11 am), with one-hour intervals between each sample. Finally, 3) we used a scent trap (four different scents were used), which was most effective for attracting bees from the Euglossini group (orchid bees). We used two sets of traps (with four scents: eucalyptol, eugenol, methyl salicylate and vanillin), and each set was placed at 2- and 20 m in height and remained in place for 48 h. Each of the sampling protocols was applied three times in each sampling area. Honey and scent traps were placed in the center of the plot, and flower visitors were actively collected through the plot. In total, we applied three sampling protocols (flower visitors, honey and scent traps) three times (March, May and August of 2022) in each area. We identified all bees to the species level, and we deposited them in Museu Paraense Emilio Goeldi (Belém, Pará, Brazil).
Using literature information, specimens’ measurements, and the species taxonomy, we were able to classify the bees accordingly to their nesting traits (type and location), body size and sociality. Nesting types were either below- or aboveground. Nesting location refers to whether a bee nested in tree cavities or not (other types were not considered due to the low number of species, cleptoparasitic and exposed). Body size was classified into three size classes according to the intertegular distance: small (0.9–2.1 mm), medium (2.2–3.9 mm) and large (>3.9 mm), following the classification from Borges et al., 2020. Moreover, we grouped them accordingly to their social behavior (eusocial, solitary and semisocial).
3. Functional trait richness
For each functional trait categorized either for plants (DBH, wood density, height, melittophily, or extinction risk) or bees (nesting type, nesting location, body size, and sociality) we also calculated the taxonomic richness within each categorical functional trait presented. For instance, the richness of bee-pollinated plants in each plot or the richness of plants with extinction risk per plot. Additionally, we calculated the Shannon index for each plot based on plant species abundance. For continuous variables, we also calculate average and total plot values within each category. The total plot value of plant size is aggregated per functional trait; for example, the size (DBH) of plants pollinated by bees is considered a proxy of how much of the plot’s canopy is dominated by plants that depend on bees for pollination. In the case of bee traits, a similar approach was implemented: we calculated the richness of small bees, for example, or the richness of bee that nest aboveground, or that are classified as solitary. Additionally, we calculated functional diversity metrics using the categorical and continuous abovementioned functional traits, with the functional diversity function of the FD package in r (R core Team, 2023).
Changes in the pollinator assemblage visiting a plant can have consequences for reproductive success and floral evolution. We studied a recent plant trans-continental range expansion to test whether the acquisition of new pollinator functional groups can lead to rapid adaptive evolution of flowers.
In Digitalis purpurea, we compared flower visitors, floral traits and natural selection between native European populations and those in two Neotropical regions, naturalised after independent introductions. Bumblebees are the main pollinators in native populations, while both bumblebees and hummingbirds are important visitors in the new range. We confirmed that the birds are effective pollinators and deposit more pollen grains on stigmas than bumblebees.
We found convergent changes in the two new regions towards larger proximal corolla tubes, a floral trait that restricts access to nectar to visitors with long mouthparts. There was strong positive linear selection for this trait in...
Census of Agriculture, 2021. Honeybees and other pollinating bees.
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Indirect effects arise when one species influences how another species interacts with a third. Pollinator-mediated indirect effects are widespread in many plant communities and are often not restricted to plant species pairs. An analytical framework does not exist yet that allows for the evaluation of indirect effects through shared pollinators in a community context, as well as their consequences for plant fitness. We used network indices describing pollinator sharing to assess the extent to which plant species affect and are affected by others in a pollination network from a species-rich dune community. For 23 plant species, we explore how these indices relate to plant fecundity (seeds/flower) over two years. We further linked plant traits and indices to uncover functional aspects of pollinator-mediated indirect interactions. Species frequently visited by shared pollinators showed higher fecundity and exhibited traits that increase pollinator attraction and generalization. Conversely, species whose shared pollinators frequently visited other plants had lower fecundity and had more specialized traits. Thus, pollinator sharing benefited some species while others suffered reproductive disadvantages, consistent with competition. The framework developed here uses network tools to advance our understanding of how pollinator-mediated indirect interactions influence a species’ relative reproductive success at the community-level.
Methods Fieldwork was carried out in Son Bosc within the protected area inside the s’Albufera Natural Park (39º46’28.1” N, 3º07’45.34” E). The sampling area consisted of a dune ecosystem at sea level in the northern region of Mallorca. We used the same 23 focal species described in Lázaro et al. (2020) for which data on plant-pollinator interactions, plant fitness and population and flower traits were available. The previous study was designed to uncover the link between commonly used network metrics and plant reproductive success (Lázaro et al. 2020), while here we specifically investigate the role of indirect interactions on plant fecundity. Thus, the analyses carried out here are post hoc given the availability of adequate data from Lázaro et al. (2020).
We used observational data on flower visitors to plants recorded in 2016 (38 plant and 119 pollinator species) and 2017 (38 plant and 174 pollinator species), as carried out by Lázaro et al. (2020), during the bloom period of the plant species included in this study (April-July). Insect censuses on focal plants were conducted once per week (15 weeks in 2016, 16 weeks in 2017), during the period of highest pollinator activity (10:00 am-17:00 pm), with each census lasting 5 min. Surveys were conducted on haphazardly selected individuals of all species in bloom each sampling day. Thus, sampling effort was proportional to plant species abundance (Lázaro et al. 2020). We considered only visits in which the insect touched reproductive organs of the flower. We pooled all visits of an insect species to a plant species across all observation periods. Then, we built quantitative networks for each year based on two visitation variables: visitation frequency (number of visits) and visitation rate per flower of each pollinator to each plant species.
Plant fecundity was estimated in 20 and 30 individuals per species in 2016 and 2017 (each year using different individuals), respectively (Lázaro et al. 2020). For each species, we obtained: (1) fruit set, i.e. number of fruits/infructescences per individual divided by the number of flowers/inflorescences, and (2) seed set, estimated as number of seeds per fruit (from one fruit/infructescence per individual chosen randomly). We used seeds per flower as the final fecundity measure, expressed as fruit set (fruits per flower) x seeds per fruit.
We used the trait data measured for each plant species in the field first reported by Lázaro et al. (2020). Briefly, we recorded the following traits: (1) Flower abundance (flowers/m2); average number of open flowers (flower units: flowers or inflorescences depending on the species) of each species counted in five transects of 50 x2 m sampled once every two weeks each year; (2) Flowering length; number of days the focal species was observed in bloom across all temporal surveys each year. (3) Flower shape; zygomorphic vs. actinomorphic flower or inflorescences; (4) Flower size; average largest diameter (width of the flower/inflorescence of each species), measured with digital calliper in 30 randomly chosen individuals per species (one fully-open flower unit randomly chosen per individual); (5) Corolla tube length (30 individuals per species); (6) Nectar volume, measured as the nectar standing crop of 10 randomly chosen individuals per species (one flower unit randomly chosen per individual) by means of microcapillary tubes; (7) Dependence on pollinators (degree of selfing), calculated as 1 – B/C, where B are the seeds per flower produced by 10 branches/individuals prevented from insect visitation (i.e. bagged before flower anthesis) and C are the seeds per flower of 10 control branches/individuals, open to natural pollination.
To estimate indirect interactions via pollinator sharing, we calculated potential indirect effects in the networks (one per year) based on visitation frequency and based on visitation rates per flower between all plant species pairs using the index proposed by Müller et al. (1999), by means of the PAC function in the bipartite R-package (Dormann et al. 2009). We obtained two sets of indirect interaction indices: the first based on visitation frequency (number of visits) and the second based on visitation rates per flower. For the indices based on visitation frequency, we built two plant-plant matrices (one for each year), with column values representing how much a plant species influences the other species, and rows representing how much the plant species is affected by other species. To obtain a single value per species and year, we summed all column values per species (separately for each year), representing the total effect of the species on all other plant species in the network (Acting degree, the sum of the effects of plant j on all other plant species in the network). Similarly, we summed all row values per species, representing the total effect of all species in the network on a particular one (Target degree, the sum of the effects plant i received from all other plant species in the network). We excluded the diagonal, setting these values to zero, as they are estimates of the potential for intraspecific competition. Additionally, to obtain indices without the influence of abundance, we obtained plant-plant matrices based on pollinator visitation rates per flower. We then followed the same procedure to estimate indirect effect indices in the pollination networks with visitation rates per flower as link weight. In other words, how much a plant species affects others by receiving a large fraction of per flower visits of shared pollinators (‘Per flower acting degree’) and how a plant species is affected by others receiving a large fraction of per flower visits of shared pollinators (‘Per flower target degree’).
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A figure showing the observed distribution of female and male flowers surrounding a focal plant (with at least one receptive female flower) across 10 census dates at four scales.
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Pesticide exposure has been implicated as a contributor to insect pollinator declines. In social bees, which are crucial pollination service providers, the effect of low-level chronic exposure is typically non-lethal leading researchers to consider whether exposure induces sublethal effects on behaviour and whether such impairment can affect colony development. Studies under laboratory conditions can control levels of pesticide exposure and elucidate causative effects, but are often criticized for being unrealistic. In contrast, field studies can monitor bee responses under a more realistic pesticide exposure landscape; yet typically such findings are limited to correlative results and can lack true controls or sufficient replication. We attempt to bridge this gap by exposing bumblebees to known amounts of pesticides when colonies are placed in the field. Using 20 bumblebee colonies, we assess the consequences of exposure to the neonicotinoid clothianidin, provided in sucrose at a concentration of five parts per billion, over 5 weeks. We monitored foraging patterns and pollen collecting performance from 3282 bouts using either a non-invasive photographic assessment, or by extracting the pollen from returning foragers. We also conducted a full colony census at the beginning and end of the experiment. In contrast to studies on other neonicotinoids, showing clear impairment to foraging behaviours, we detected only subtle changes to patterns of foraging activity and pollen foraging during the course of the experiment. However, our colony census measures showed a more pronounced effect of exposure, with fewer adult workers and sexuals in treated colonies after 5 weeks. Synthesis and applications. Pesticide-induced impairments on colony development and foraging could impact on the pollination service that bees provide. Therefore, our findings, that bees show subtle changes in foraging behaviour and reductions in colony size after exposure to a common pesticide, have important implications and help to inform the debate over whether the benefits of systemic pesticide application to flowering crops outweigh the costs. We propose that our methodology is an important advance to previous semi-field methods and should be considered when considering improvements to current ecotoxicological guidelines for pesticide risk assessment.
Landscape changes can alter pollinator movement and foraging patterns which can in turn influence demographic processes of plant populations. In the Cascade Mountains of the Pacific Northwest, USA, forests are encroaching on alpine meadows that harbor diverse plant and pollinator communities. Whether encroachment and isolation of sub-meadows will influence pollinator foraging behaviors is unknown. To help assess those behaviors, subcutaneous Passive Integrated Transponders were implanted into 163 Rufous Hummingbirds (Selasphorus rufus), common avian pollinators in western North America and four arrays of five hummingbird feeders were established equipped with Radio Frequency Identification data loggers to passively relocate individuals at points throughout the landscape. The feeder arrays were established on four peaks along Frizzel Ridge in the H. J. Andrews Experimental Forest (Lookout Mountain, M1, M2, and Carpenter Mountain). A center feeder was established in a large, central alpine meadow and four satellite feeders c.a. 250m from the center. The satellite feeders were positioned such that at least one was in the open and connected to the center feeder by open habitat, one was in the open but separated from the center by coniferous forest canopy, and one was placed under coniferous forest canopy. Feeders were maintained for 1.5-12 weeks per year from 2014-2017.
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The vast variation in floral traits across angiosperms is often interpreted as the result of adaptation to pollinators. However, studies in wild populations often find no evidence of pollinator-mediated selection on flowers. Evolutionary theory predicts this could be the outcome of periods of stasis under stable conditions, followed by shorter periods of pollinator change that provide selection for innovative phenotypes. We asked if periods of stasis are caused by stabilizing selection, absence of other forms of selection, or by low trait ability to respond even if selection is present. We studied a plant predominantly pollinated by one bee species across its range. We measured heritability and evolvability of traits, using genome-wide relatedness in a large wild population, and combined this with estimates of selection on the same individuals. We found evidence for both stabilizing selection and low trait heritability as potential explanations for stasis in flowers. The area of the standard petal is under stabilizing selection, but the variability is not heritable. A separate trait, floral weight, presents high heritability, but is not currently under selection. We show how a simple pollination environment coincides with the absence of current prerequisites for adaptive evolutionary change, while heritable variation remains to respond to future selection pressures. Methods The methods to collect the datasets are described below. R code used for analysis is also included in a separate file. Pollinator censuses. To quantify the diversity of floral visitors and visitation rates, we ran multiple three-minute pollinator censuses at different times of the day, for up to five hours of observations per site, on two separate days during peak blooming in 2014 (plus extra censuses in two sites in 2013). Each census recorded the number and identity of visitors to patches of flowers on haphazardly chosen shrubs, including but not limited to 40 tagged individuals. We counted the number of flowers surveyed in each census and the number of flowers visited to estimate the per-flower visitation rate. Floral phenotypes. We collected five haphazardly selected flowers from each individual plant for phenotypic characterization of two floral traits that function as proxies for flower showiness and flower size. The area of the upwards-facing petal, or standard, plays a key role in flower showiness. We removed standards from all flowers when fresh, and pressed them flat individually in a plant press. We then used scanned images of the standards to measure their area. Flower mass reflects the size of the flower. We estimated size as the dry weight of flowers (calyx and corolla) after removing the standard petal and the pedicel, and brushing off all pollen grains. Flowers were pressed and oven-dried at 40ºC for 48 hours and weighed to the nearest 0.01 mg. Fruit set. We estimated fruit set in the 40 individual plants in each of the six sites as a proxy for female reproductive success. We labelled a representative flowering twig per plant during peak flowering and collected it a few weeks later when fruit capsules were beginning to brown. In the laboratory, we measured 10 cm of twig to count a) the number of fruits developing normally, and b) scars left by all flowers produced by the twig, clearly visible under a dissecting microscope. From this, we calculated fruit set as the proportion of flowers that develop into a fruit. Plant genotyping. Fresh twigs were collected from each tagged individual plant and dried in silica gel. After DNA extraction we used a Genotyping-by-Sequencing (GBS) protocol to identify single nucleotide polymorphisms (SNPs) across the genome (Elshire et al. 2011). Two libraries were built for each individual after separate digestions of genomic DNA with PstI and EcoT22I, followed by HiSeq 2000 Illumina sequencing. We implemented SNP calling using the UNEAK pipeline (Lu et al. 2012) in the TASSEL v.3 software package (Bradbury et al. 2007), designed for data sets without a reference genome. SNP-based relatedness. Pairwise relatedness between all pairs of the remaining 225 individuals (after quality filtering) was estimated from the similarity of their SNP genotypes. To estimate the genome-wide relatedness matrix among all pairs of individuals, we used the kin function of package synbreed in R (Wimmer et al. 2012). Relatedness values are a measure of excess allele sharing compared to unrelated individuals. As a consequence, negative values can be common and correspond to individuals sharing fewer alleles than expected given the sample. References
Bradbury, P. J., Z. Zhang, D. E. Kroon, T. M. Casstevens, Y. Ramdoss, and E. S. Buckler. 2007. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633-2635. Elshire, R. J., J. C. Glaubitz, Q. Sun, J. A. Poland, K. Kawamoto, E. S. Buckler, and S. E. Mitchell. 2011. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PloS one 6:e19379. Lu, F., J. Glaubitz, J. Harriman, T. Casstevens, and R. Elshire. 2012. TASSEL 3.0 Universal Network Enabled Analysis Kit (UNEAK) pipeline documentation. White Paper 2012:1-12.
Wimmer, V., T. Albrecht, H. Auinger, and C. Schoen. 2012. synbreed: a framework for the analysis of genomic prediction data using R. Bioinformatics 28:2086-2087.
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ABSTRACT A comprehensive census of a hectare of cerrado s.s. in southeastern Brazil, a small-tree and scrub woodland physiognomy, allowed the evaluation of whether pollination and dispersal modes are correlated with the stratification of the vegetation and if so, in what way. Generalist pollination, and pollination by small bees, as well as ornithophily and anemophily were more frequent in the lower layers (ground and scrub), while species pollinated by large bees and beetles are more or less equally distributed among the ground, scrub and tree layers. The three nocturnal pollination modes, phalenophily, sphingophily, and chiropterophily indicated a preference for the upper layers (tree and scrub). Zoochory predominated in the tree layer, but autochory increased towards the ground at the expense of anemochory and zoochory. We discuss possible reasons for the height distribution of pollination and seed dispersal modes and compare the situation in Cerrado with other Neotropical forests.
Mutualistic interactions structure ecological communities and they are strongly influenced by the combined effect of different drivers of global change. Land-use changes and global warming have elicited rapid shrub encroachment in alpine grasslands in recent decades, which may have detrimental outcomes for native alpine forbs. In spite of the importance of this process, we lack knowledge about how shrub encroachment modifies community-wide patterns of plant–pollinator mutualistic interactions.
Based on the functional biodiversity hypothesis (FBH), which predicts higher pollinator biodiversity in species-rich plant communities, we asked whether the increase in nutritional resources available for pollinators due to shrub expansion modifies pollinator niche breadth and species richness, and whether these changes affect plant–plant interactions.
For this purpose, we compared quantitative plant–flower visitor interaction network assemblages at replicated plots in two habitat types in dry c...
The data are gathered within the TERENO (Terrestrial Environmental Observatories) long-term research programme involving several Helmholtz Association Centers in Germany (www.tereno.net). TERENO aims to catalogue the longterm ecological, social and economic impact of global change at regional and landscape level. The biodiversity part of TERENO deals with monitoring and research on different organism groups: (1) Vascular plants (primary producers, overall biodiversity indicators), (2) Bees and Hoverflies (important pollinators; ecosystem service agents), (3) Butterflies (indicators for habitat quality, pollinators), (4) Birds (highly mobile, sensitive to landscape context, integrative at landscape scale).This dataset covers bird count data of 4x4 km landscapes in Saxony-Anhalt (Germany) dominated by agricultural use. All singing, calling and seen birds were registered according to the point counts method described by Bibby et al. (1992): Bird census techniques, Academic press, London.
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Census of flower visitors and selective exclusion experiments.
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Brood census data