UK Center for Ecology and Hydrology

Lancaster, United Kingdom

UK Center for Ecology and Hydrology

Lancaster, United Kingdom
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Chapman D.S.,UK Center for Ecology and Hydrology
Global Change Biology | Year: 2013

Mountain plants are considered among the species most vulnerable to climate change, especially at high latitudes where there is little potential for poleward or uphill dispersal. Satellite monitoring can reveal spatiotemporal variation in vegetation activity, offering a largely unexploited potential for studying responses of montane ecosystems to temperature and predicting phenological shifts driven by climate change. Here, a novel remote-sensing phenology approach is developed that advances existing techniques by considering variation in vegetation activity across the whole year, rather than just focusing on event dates (e.g. start and end of season). Time series of two vegetation indices (VI), normalized difference VI (NDVI) and enhanced VI (EVI) were obtained from the moderate resolution imaging spectroradiometer MODIS satellite for 2786 Scottish mountain summits (600-1344 m elevation) in the years 2000-2011. NDVI and EVI time series were temporally interpolated to derive values on the first day of each month, for comparison with gridded monthly temperatures from the preceding period. These were regressed against temperature in the previous months, elevation and their interaction, showing significant variation in temperature sensitivity between months. Warm years were associated with high NDVI and EVI in spring and summer, whereas there was little effect of temperature in autumn and a negative effect in winter. Elevation was shown to mediate phenological change via a magnification of temperature responses on the highest mountains. Together, these predict that climate change will drive substantial changes in mountain summit phenology, especially by advancing spring growth at high elevations. The phenological plasticity underlying these temperature responses may allow long-lived alpine plants to acclimate to warmer temperatures. Conversely, longer growing seasons may facilitate colonization and competitive exclusion by species currently restricted to lower elevations. In either case, these results show previously unreported seasonal and elevational variation in the temperature sensitivity of mountain vegetation activity. © 2013 John Wiley & Sons Ltd.

Johnson A.C.,UK Center for Ecology and Hydrology
Environmental Science and Technology | Year: 2010

Daily steroid estrogen concentrations as 17β-estradiol equivalents (E2 equiv.) were modeled from 1992 to 2008 for single locations on the well populated Thames and Soar rivers in England. The historic daily mean flow values which were the basis of this exercise came from a selected gauging site on each river. The natural variation in flow from winter to summer typically produced a 20- to 30-fold difference in predicted estrogen concentration over the course of a year. Based on all the predicted values from minimum to maximum over the 1992 to 2008 period there was a 98-fold difference in estrogen concentrations on the basis of flow alone for the Thames (0.1-12.7 ng/L E2 equiv.) and 67-fold for the Soar (0.2-13.3 ng/L E2 equiv.). This compares to a predicted 0.5-fold difference that could arise from differences in sewage treatment and 0.1-fold difference due to differences in in-stream biodegradation. The seasonal variation in flow generated a repeating "roller coaster" in predicted estrogen concentrations. Regularly measured phosphate data for the river Avon over the period 1993 to 1996, where point sources also dominate, was compared against flow and predicted estrogen concentrations. The pattern of predicted estrogen and measured total phosphate concentration were very closely related. This dramatic variation in contaminant concentration over the year due to flow poses questions over what we mean by environmental relevance and the representation of the real environment in aquatic ecotoxicity tests. © 2010 American Chemical Society.

Dawson A.,UK Center for Ecology and Hydrology
General and Comparative Endocrinology | Year: 2013

Photoperiod is the major cue used by birds to time breeding seasons and molt. However, the annual cycle in photoperiod changes with latitude. Within species, for temperate and high latitude species, gonadal maturation and breeding start earlier at lower latitudes but regression and molt both occur at similar times at different latitudes. Earlier gonadal maturation can be explained simply by the fact that considerable maturation occurs before the equinox when photoperiod is longer at lower latitudes - genetic differences between populations are not necessary to explain earlier breeding at lower latitudes. Gonadal regression is caused either by absolute photorefractoriness or, in some species with long breeding seasons, relative photorefractoriness. In either case, the timing of regression and molt cannot be explained by absolute prevailing photoperiod or rate of change in photoperiod - birds appear to be using more subtle cues from the pattern of change in photoperiod. However, there may be no difference between absolute and relative photorefractory species in how they utilise the annual cycle in photoperiod to time regression. © 2013 Elsevier Inc.

There is increasing evidence that recent changes in climate have had an effect on lake phytoplankton communities and it has been suggested that it is likely that Cyanobacteria will increase in relative abundance under the predicted future climate. However, testing such a qualitative prediction is challenging and usually requires some form of numerical computer model. Therefore, the lake modelling literature was reviewed for studies that examined the impact of climate change upon Cyanobacteria. These studies, taken collectively, generally show an increase in relative Cyanobacteria abundance with increasing water temperature, decreased flushing rate and increased nutrient loads. Furthermore, they suggest that whilst the direct effects of climate change on the lakes can change the timing of bloom events and Cyanobacteria abundance, the amount of phytoplankton biomass produced over a year is not enhanced directly by these changes. Also, warmer waters in the spring increased nutrient consumption by the phytoplankton community which in some lakes caused nitrogen limitation later in the year to the advantage of some nitrogen-fixing Cyanobacteria. Finally, it is also possible that an increase in Cyanobacteria dominance of the phytoplankton biomass will lead to poorer energy flow to higher trophic levels due to their relatively poor edibility for zooplankton. © 2011 Elsevier Ltd.

Dawson A.,UK Center for Ecology and Hydrology
Frontiers in Neuroendocrinology | Year: 2015

This paper reviews current knowledge of photoperiod control of GnRH-1 secretion and proposes a model in which two processes act together to regulate GnRH1 secretion. Photo-induction controls GnRH1 secretion and is directly related to prevailing photoperiod. Photo-inhibition, a longer term process, acts through GnRH1 synthesis. It progresses each day during daylight hours, but reverses during darkness. Thus, photo-inhibition gradually increases when photoperiods exceed 12. h, and reverses under shorter photoperiods. GnRH1 secretion on any particular day is the net result of these two processes acting in tandem. The only difference between species is their sensitivity to photo-inhibition. This can potentially explain differences in timing and duration of breeding seasons between species, why some species become absolutely photorefractory and others relatively photorefractory, why breeding seasons end at the same time at different latitudes within species, and why experimental protocols sometimes produce results that appear counter to what happens naturally. © 2014 The Author.

Elliott J.A.,UK Center for Ecology and Hydrology
Global Change Biology | Year: 2010

The phytoplankton lake community model PROTECH (Phytoplankton RespOnses To Environmental CHange) was applied to the eutrophic lake, Esthwaite Water (United Kingdom). It was validated against monitoring data from 2003 and simulated well the seasonal pattern of total chlorophyll, diatom chlorophyll and Cyanobacteria chlorophyll with respective R2-values calculated between observed and simulated of 0.68, 0.72 and 0.77 (all P<0.01). This simulation was then rerun through various combinations of factorized changes covering a range of half to double the flushing rate and from -1 to +4°C changes in water temperature. Their effect on the phytoplankton was measured as annual, spring, summer and autumn means of the total and species chlorophyll concentrations. In addition, Cyanobacteria mean percentage abundance (%Cb) and maximum percentage abundance (Max %Cb) was recorded, as were the number of days that Cyanobacteria chlorophyll concentration exceed two World Health Organization (WHO) derived risk thresholds (10 and 50mgm-3). The phytoplankton community was dominated in the year by three of the eight phytoplankton simulated. The vernal bloom of the diatom Asterionella showed little annual or seasonal response to the changing drivers but this was not the case for the two Cyanobacteria that also dominated, Anabaena and Aphanizomenon. These Cyanobacteria showed enhanced abundance, community dominance and increased duration above the highest WHO risk threshold with increasing water temperature and decreasing flushing rate: This effect was greatest in the summer period. However, the response was ultimately controlled by the availability of nutrients, particularly phosphorus and nitrogen, with occasional declines in the latter's concentration helping the dominance of these nitrogen-fixing phytoplankton. © 2009 Blackwell Publishing Ltd.

Chapman D.S.,UK Center for Ecology and Hydrology
Global Ecology and Biogeography | Year: 2010

Aim Species distribution models (SDMs) are used to infer niche responses and predict climate change-induced range shifts. However, their power to distinguish real and chance associations between spatially autocorrelated distribution and environmental data at continental scales has been questioned. Here this is investigated at a regional (10 km) scale by modelling the distributions of 100 plant species native to the UK.Location UK.Methods SDMs fitted using real climate data were compared with those utilizing simulated climate gradients. The simulated gradients preserve the exact values and spatial structure of the real ones, but have no causal relationships with any species and so represent an appropriate null model. SDMs were fitted as generalized linear models (GLMs) or by the Random Forest machine-learning algorithm and were either non-spatial or included spatially explicit trend surfaces or autocovariates as predictors.Results Species distributions were significantly but erroneously related to the simulated gradients in 86% of cases (P < 0.05 in likelihood-ratio tests of GLMs), with the highest error for strongly autocorrelated species and gradients and when species occupied 50% of sites. Even more false effects were found when curvilinear responses were modelled, and this was not adequately mitigated in the spatially explicit models. Non-spatial SDMs based on simulated climate data suggested that 70-80% of the apparent explanatory power of the real data could be attributable to its spatial structure. Furthermore, the niche component of spatially explicit SDMs did not significantly contribute to model fit in most species.Main conclusions Spatial structure in the climate, rather than functional relationships with species distributions, may account for much of the apparent fit and predictive power of SDMs. Failure to account for this means that the evidence for climatic limitation of species distributions may have been overstated. As such, predicted regional- and national-scale impacts of climate change based on the analysis of static distribution snapshots will require re-evaluation. © 2010 Crown Copyright.

Hill M.O.,UK Center for Ecology and Hydrology
Methods in Ecology and Evolution | Year: 2012

Data on the occurrence of species in grid cells are collected by biological recording schemes, typically with the intention of publishing an atlas. Interpretation of such data is often hampered by the lack of information on the effort that went into collecting them. This is the 'recorder effort problem'. One measure of recorder effort is the proportion of a suite of common species ('benchmark species') found at a given location and time. Benchmark species have in the past been taken as a uniform set across a territory. However, if records are available from a neighbourhood surrounding a given location, then a local set benchmark species can be defined by pooling records from the neighbourhood and selecting the commonest species in the pooled set. Neighbourhoods differ in species richness, so that the list of species that 'ought' to be found in one location may be longer than that for another. If the richness of a neighbourhood can be estimated, then a suite of benchmark species can be standardized to be the commonest of a fixed proportion of the total expected for the neighbourhood. Recording effort is then defined as the proportion of benchmark species that were found. A method of estimating species richness is proposed here, based on the local frequencies f j of species in neighbouring grid cells. Species discovery is modelled as a Poisson process. It is argued that when a neighbourhood is well sampled, the frequency-weighted mean frequency /∑f j of species in the neighbourhood will assume a standard value. The method was applied to a data set of 2000000 records detailing the occurrence of bryophytes in 3695 out of the total 3854hectads (10-km squares) in Great Britain, Ireland, the Isle of Man and the Channel Islands. 6.Three main applications are outlined: estimation of recording effort, scanning data for unexpected presences or absences and measurement of species trends over time. An explicit statistical model was used to estimate trends, modelling the probability of species j being found at location i and time t as the outcome of Poisson process with intensity Q ijtx jt, where x jt is a time factor for species j, and Q ijt depends on recording effort at location i and time t and on the time-independent probability of species j being found in hectad i. © 2011 The Author. Methods in Ecology and Evolution © 2011 British Ecological Society.

Vanbergen A.J.,UK Center for Ecology and Hydrology
Frontiers in Ecology and the Environment | Year: 2013

Insect pollinators of crops and wild plants are under threat globally and their decline or loss could have profound economic and environmental consequences. Here, we argue that multiple anthropogenic pressures - including land-use intensification, climate change, and the spread of alien species and diseases - are primarily responsible for insect-pollinator declines. We show that a complex interplay between pressures (eg lack of food sources, diseases, and pesticides) and biological processes (eg species dispersal and interactions) at a range of scales (from genes to ecosystems) underpins the general decline in insect-pollinator populations. Interdisciplinary research on the nature and impacts of these interactions will be needed if human food security and ecosystem function are to be preserved. We highlight key areas that require research focus and outline some practical steps to alleviate the pressures on pollinators and the pollination services they deliver to wild and crop plants. © The Ecological Society of America.

Alex Elliott J.,UK Center for Ecology and Hydrology
Freshwater Biology | Year: 2012

1.Climate change and eutrophication will be two of the largest threats to lake ecosystems this century. Therefore, the effect of changing water temperature (+0 to +4°C) and nutrient load (0.5-2.0 proportional change) on the phytoplankton of Windermere was assessed using the phytoplankton community model, PROTECH (Phytoplankton RespOnses To Environmental CHange). 2.The following metrics were used for the analysis: annual, spring, summer and autumn mean chlorophyll a concentrations for total phytoplankton, diatoms and Cyanobacteria. Also, the timing of the spring diatom bloom was assessed and the number of days when the World Health Organisation (WHO)-derived risk threshold of 10mgm -3 Cyanobacteria chlorophyll a was exceeded. 3.The diatoms in Windermere produced their largest amount of chlorophyll a in the spring. Whilst the quantity of diatom biomass produced was relatively unaffected by the simulated changes in temperature and nutrient load, the timing of the bloom peak was 2-3days earlier per 1°C. 4.The modelled Cyanobacteria dominated in the summer and autumn and generally responded positively to both increasing nutrients and temperature illustrating a synergistic relationship between these two drivers. However, in the autumn, this relationship was sometimes disrupted because of variations in the length of stratification. 5.Temperature as a factor alone seemed to act in two ways: it affected phenology (e.g. bloom peak timing) mainly in the early part of the growing season and enhanced the dominance of Cyanobacteria in the late growing season. Furthermore, these effects were greatly reduced under the lower nutrient scenarios, suggesting that local management of nutrient inputs to the lake potentially offers a solution to the effects caused by the increase in temperature. © 2011 Blackwell Publishing Ltd.

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