40 resultados para ABUNDANCE GRADIENTS


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Earthworms are significant ecosystem engineers and are an important component of the diet of many vertebrates and invertebrates, so the ability to predict their distribution and abundance would have wide application in ecology, conservation and land management. Earthworm viability is known to be affected by the availability and quality of food resources, soil water conditions and temperature, but has not yet been modelled mechanistically to link effects on individuals to field population responses. Here we present a novel model capable of predicting the effects of land management and environmental conditions on the distribution and abundance of Aporrectodea caliginosa, the dominant earthworm species in agroecosystems. Our process-based approach uses individual based modelling (IBM), in which each individual has its own energy budget. Individual earthworm energy budgets follow established principles of physiological ecology and are parameterised for A. caliginosa from experimental measurements under optimal conditions. Under suboptimal conditions (e.g. food limitation, low soil temperatures and water contents) reproduction is prioritised over growth. Good model agreement to independent laboratory data on individual cocoon production and growth of body mass, under variable feeding and temperature conditions support our representation of A. caliginosa physiology through energy budgets. Our mechanistic model is able to accurately predict A. caliginosa distribution and abundance in spatially heterogeneous soil profiles representative of field study conditions. Essential here is the explicit modelling of earthworm behaviour in the soil profile. Local earthworm movement responds to a trade-off between food availability and soil water conditions, and this determines the spatiotemporal distribution of the population in the soil profile. Importantly, multiple environmental variables can be manipulated simultaneously in the model to explore earthworm population exposure and effects to combinations of stressors. Potential applications include prediction of the population-level effects of pesticides and changes in soil management e.g. conservation tillage and climate change.

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Pollination services are economically important component of agricultural biodiversity which enhance the yield and quality of many crops. An understanding of the suitability of extant habitats for pollinating species is crucial for planning management actions to protect and manage these service providers. In a highly modified agricultural ecosystem, we tested the effect of different pollination treatments (open, autonomous self- and wind-pollination) on pod set, seed set, and seed weight in field beans (Vicia faba). We also investigated the effect of semi-natural habitats and flower abundance on pollinators of field beans. Pollinator sampling was undertaken in ten field bean fields along a gradient of habitat complexity; CORINE land cover classification was used to analyse the land use patterns between 500–3000 m around the sites. Total yield from open-pollination increased by 185% compared to autonomous self-pollination. There was positive interactive effect of local flower abundance and cover of semi-natural habitats on overall abundance of pollinators at 1500 and 2000 m, and abundance of bumblebees (Bombus spp.) at 1000–2000 m. In contrast, species richness of pollinators was only correlated with flower abundance and not with semi-natural habitats. We did not find a link between pod set from open-pollination and pollinator abundance, possibly due to variations in the growing conditions and pollinator communities between sites. We conclude that insect pollination is essential for optimal bean yields and therefore the maintenance of semi-natural habitats in agriculture-dominated landscapes should ensure stable and more efficient pollination services in field beans.

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We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

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Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

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The responses of animals and plants to recent climate change vary greatly from species to species, but attempts to understand this variation have met with limited success. This has led to concerns that predictions of responses are inherently uncertain because of the complexity of interacting drivers and biotic interactions. However, we show for an exemplar group of 155 Lepidoptera species that about 60% of the variation among species in their abundance trends over the past four decades can be explained by species-specific exposure and sensitivity to climate change. Distribution changes were less well predicted, but nonetheless, up to 53% of the variation was explained. We found that species vary in their overall sensitivity to climate and respond to different components of the climate despite ostensibly experiencing the same climate changes. Hence, species have undergone different levels of population “forcing” (exposure), driving variation among species in their national-scale abundance and distribution trends. We conclude that variation in species’ responses to recent climate change may be more predictable than previously recognized.

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1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline. 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes. 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93�7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R2 = 24�9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline. 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and istributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

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1. The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. 2. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). 3. The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial. 4. Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.

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The variability of populations over time is positively associated with their risk of local extinction. Previous work has shown that populations at the high-latitude boundary of species’ ranges show higher inter-annual variability, consistent with increased sensitivity and exposure to adverse climatic conditions. However, patterns of population variability at both high- and low-latitude species range boundaries have not yet been concurrently examined. Here, we assess the inter-annual population variability of 28 butterfly species between 1994 and 2009 at 351 and 18 sites in the United Kingdom and Catalonia, Spain, respectively. Local population variability is examined with respect to the position of the species’ bioclimatic envelopes (i.e. whether the population falls within areas of the ‘core’ climatic suitability or is a climatically ‘marginal’ population), and in relation to local landscape heterogeneity, which may influence these range location – population dynamic relationships. We found that butterfly species consistently show latitudinal gradients in population variability, with increased variability in the more northerly UK. This pattern is even more marked for southerly distributed species with ‘marginal’ climatic suitability in the UK but ‘core’ climatic suitability in Catalonia. In addition, local landscape heterogeneity did influence these range location – population dynamic relationships. Habitat heterogeneity was associated with dampened population dynamics, especially for populations in the UK. Our results suggest that promoting habitat heterogeneity may promote the persistence of populations at high-latitude range boundaries, which may potentially aid northwards expansion under climate warming. We did not find evidence that population variability increases towards southern range boundaries. Sample sizes for this region were low, but there was tentative evidence, in line with previous ecological theory, that local landscape heterogeneity may promote persistence in these retracting low-latitude range boundary populations.

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Changes in land management practices may have significant implications for soil microbial communities important in organic P turnover. Soil bacteria can increase plant P availability by excreting phosphatase enzymes which catalyze the hydrolysis of ester-phosphate bonds. Examining the diversity and abundance of alkaline phosphatase gene harboring bacteria may provide valuable insight into alkaline phosphatase production in soils. This study examined the effect of 20 years of no input organic (ORG), organic with composted manure (ORG + M), conventional (CONV) and restored prairie (PRA) management on soil P bioavailability, alkaline phosphatase activity (ALP), and abundance and diversity of ALP gene (phoD) harboring bacteria in soils from the northern Great Plains of Canada. Management system influenced bioavailable P (P < 0.001), but not total P, with the lowest concentrations in the ORG systems and the highest in PRA. Higher rates of ALP were observed in the ORG and ORG + M treatments with a significant negative correlation between bioavailable P and ALP in 2011 (r2 = 0.71; P = 0.03) and 2012 (r2 = 0.51; P = 0.02), suggesting that ALP activity increased under P limiting conditions. The phoD gene abundance was also highest in ORG and ORG + M resulting in a significant positive relationship between bacterial phoD abundance and ALP activity (r2 = 0.71; P = 0.009). Analysis of phoD bacterial community fingerprints showed a higher number of species in CONV compared to ORG and ORG + M, contrary to what was expected considering greater ALP activity under ORG management. In 2012, banding profiles of ORG + M showed fewer phoD bacterial species following the second manure application, although ALP activity is higher than in 2011. This indicates that a few species may be producing more ALP and that quantitative gene analysis was a better indicator of activity than the number of species present.

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Bacterial transformation of phosphorus (P) compounds in soil is largely dependent on soil microbial community function, and is therefore sensitive to anthropogenic disturbances such as fertilization or cropping systems. However, the effect of soil management on the transcription of bacterial genes that encode phosphatases, such as phoD, is largely unknown. This greenhouse study examined the effect of long-term management and P amendment on potential alkaline phosphatase (ALP) activity and phoD gene (DNA) and transcript (RNA) abundance. Soil samples (0–15 cm) were collected from the Glenlea Long-term Rotation near Winnipeg, Manitoba, to compare organic, conventional and prairie management systems. In the greenhouse, pots of soil from each management system were amended with P as either soluble mineral fertilizer or cattle manure and then planted with Italian ryegrass (Lolium multiforum). Soils from each pot were sampled for analysis immediately and after 30 and 106 days. Significant differences among the soil/P treatments were detected for inorganic P, but not the organic P in NaHCO3-extracts. At day 0, ALP activity was similar among the soil/P treatments, but was higher after 30 days for all P amendments in soil from organically managed plots. In contrast, ALP activity in soils under conventional and prairie management responded to increasing rates of manure only, with significant effects from medium and high manure application rates at 30 and 106 days. Differences in ALP activity at 30 days corresponded to the abundance of bacterial phoD genes, which were also significantly higher in soils under organic management. However, this correlation was not significant for transcript abundance. Next-generation sequencing allowed the identification of 199 unique phoD operational taxonomic units (OTUs) from the metagenome (soil DNA) and 35 unique OTUs from the metatranscriptome (soil RNA), indicating that a subset of phoD genes was being transcribed in all soils.