Climate change-related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea

During the 1980s, the North Sea plankton community underwent a well-documented ecosystem regime shift, including both spatial changes (northward species range shifts) and temporal changes (increases in the total abundances of warmer water species). This regime shift has been attributed to climate change. Plankton provide a link between climate and higher trophic-level organisms, which can forage on large spatial and temporal scales. It is therefore important to understand not only whether climate change affects purely spatial or temporal aspects of plankton dynamics, but also whether it affects spatiotemporal aspects such as metapopulation synchrony. If plankton synchrony is altered, higher trophic-level feeding patterns may be modified. A second motivation for investigating changes in synchrony is that the possibility of such alterations has been examined for few organisms, in spite of the fact that synchrony is ubiquitous and of major importance in ecology. This study uses correlation coefficients and spectral analysis to investigate whether synchrony changed between the periods 1959–1980 and 1989–2010. Twenty-three plankton taxa, sea surface temperature (SST), and wind speed were examined. Results revealed that synchrony in SST and plankton was altered. Changes were idiosyncratic, and were not explained by changes in abundance. Changes in the synchrony of Calanus helgolandicus and Para-pseudocalanus spp appeared to be driven by changes in SST synchrony. This study is one of few to document alterations of synchrony and climate-change impacts on synchrony. We discuss why climate-change impacts on synchrony may well be more common and consequential than previously recognized.

Climate change-related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea

During the 1980s, the North Sea plankton community underwent a well-documented ecosystem regime shift, including both spatial changes (northward species range shifts) and temporal changes (increases in the total abundances of warmer water species). This regime shift has been attributed to climate change. Plankton provide a link between climate and higher trophic-level organisms, which can forage on large spatial and temporal scales. It is therefore important to understand not only whether climate change affects purely spatial or temporal aspects of plankton dynamics, but also whether it affects spatiotemporal aspects such as metapopulation synchrony. If plankton synchrony is altered, higher trophic-level feeding patterns may be modified. A second motivation for investigating changes in synchrony is that the possibility of such alterations has been examined for few organisms, in spite of the fact that synchrony is ubiquitous and of major importance in ecology. This study uses correlation coefficients and spectral analysis to investigate whether synchrony changed between the periods 1959–1980 and 1989–2010. Twenty-three plankton taxa, sea surface temperature (SST), and wind speed were examined. Results revealed that synchrony in SST and plankton was altered. Changes were idiosyncratic, and were not explained by changes in abundance. Changes in the synchrony of Calanus helgolandicus and Para-pseudocalanus spp appeared to be driven by changes in SST synchrony. This study is one of few to document alterations of synchrony and climate-change impacts on synchrony. We discuss why climate-change impacts on synchrony may well be more common and consequential than previously recognized.

Scale and ecosystem services: how do observation, management, and analysis shift with scale—lessons from Québec

Ecosystem service assessment and management are shaped by the scale at which they are conducted; however, there has been little systematic investigation of the scales associated with ecosystem service processes, such as production, benefit distribution, and management. We examined how social-ecological spatial scale impacts ecosystem service assessment by comparing how ecosystem service distribution, trade-offs, and bundles shift across spatial scales. We used a case study in Québec, Canada, to analyze the scales of production, consumption, and management of 12 ecosystem services and to analyze how interactions among 7 of these ecosystem services change across 3 scales of observation (1, 9, and 75 km²). We found that ecosystem service patterns and interactions were relatively robust across scales of observation; however, we identified 4 different types of scale mismatches among ecosystem service production, consumption, and management. Based on this analysis, we have proposed 4 aspects of scale that ecosystem service assessments should consider.

Catch and effort from a recreational trolling fishery in a large lake

Over recent decades recreational fisheries have grown substantially throughout the world. Despite this increase, catches from recreational fisheries have often been ignored in fisheries management, although this is now being remedied. Monitoring recreational fisheries can be expensive, and the primary means used for monitoring is angler (creel) surveys, typically funded from sales of fishing licences. The studies presented in this thesis examine different approaches to monitoring recreational trolling fisheries’ catch and effort, where fishing licenses are not required and there are no reporting requirements. I present results from a complemented roving/mail-in survey undertaken during 2013-2014 to estimate recreational effort and catch of Atlantic salmon (Salmo salar) and brown trout (S. trutta) in the largest lake in the European Union, Lake Vänern, Sweden. I also evaluate different angler catch reporting methods (mail-in, tournament reports and face-to-face interviews) and compare catch rates within and among spring and fall fishing periods. In addition, mail-in survey data are examined for recall bias.   I estimate that 28.7 tonnes of salmon and trout combined were harvested by the recreational trolling fishery in 2014, more than the commercial and subsistence fisheries combined. Seasonal differences in both recreational effort and catch were observed. Effort, in boat hours, was significantly higher in spring than in fall. Catch rates of trout were higher in fall than in spring, but there were no seasonal differences in catches of salmon. Harvest per boat day did not differ significantly among catch reporting methods, indicating that all three methods could be useful for managers interested in harvest rates. In contrast, total and released catch per boat day differed among reporting methods, with tournament anglers catching more fish in total. Finally, there was little evidence for recall bias in mail-in surveys, indicating that mail-in surveys are useful for collecting unbiased catch data. My study is the most comprehensive angler survey to date for Lake Vänern, and my results should be of immediate use to local fisheries managers and should also be of interest to researchers and managers interested in estimating catch and effort for fisheries at large spatial scales.

Recruitment patterns and processes of coastal fish species in a temperate rocky reef

Tese de Doutoramento, Ciências do Mar, da Terra e do Ambiente, Ramo: Ciências do Mar, Especialização em Ecologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Fractal descriptors for quantifying brain complexity in MRI

Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot’s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.

Constraining FIR size, dust temperature and dust mass in ALPINE galaxies at redshift 4

The study of galaxies at high redshift plays a crucial role to understand the mechanism of galaxy formation and evolution. At redshifts just after the epoch of re-ionization (4spatial extent of the dust emission in high-redshift galaxies and to provide a lower limit on dust temperature, to constrain the dust mass. This is achieved by studying 23 FIR continuum detected main-sequence galaxies of the ALMA Large Program to INvestigate (ALPINE) survey, performed at high redshift (4spatial extent of the dust emission, i.e. the dust size, with the stellar and gas distribution, traced by the UV and [CII] emission, respectively. Finally, we put these results in a broader context, by studying the dust size evolution as a function of cosmic time. We derive dust size measurements via a Gaussian fit in the image and uv plane. Out of the 23 FIR-continuum-detected targets, 20 have been considered in this work since they are isolated systems. Of these 20, 7 are spatially resolved; for each of the remaining 13, we provide an upper limit to the dust size. We find that the gas emission is more extended than the dust spatial scale, by a factor of 1.40±0.29, while the latter appears to be larger than the stellar emission size. Moreover, we do not find any significant trend for dust size as a function of the stellar mass and the redshift. In addition, we provide a minimum dust temperature estimate for the 7 resolved sources, for which we find Tmin∼16−19K. We also derive dust masses for the resolved sources, logMdust∼7−8M⊙.

Metacommunity Versus Biogeography: A Case Study Of Two Groups Of Neotropical Vegetation-dwelling Arthropods.

Biogeography and metacommunity ecology provide two different perspectives on species diversity. Both are spatial in nature but their spatial scales do not necessarily match. With recent boom of metacommunity studies, we see an increasing need for clear discrimination of spatial scales relevant for both perspectives. This discrimination is a necessary prerequisite for improved understanding of ecological phenomena across scales. Here we provide a case study to illustrate some spatial scale-dependent concepts in recent metacommunity studies and identify potential pitfalls. We presented here the diversity patterns of Neotropical lepidopterans and spiders viewed both from metacommunity and biogeographical perspectives. Specifically, we investigated how the relative importance of niche- and dispersal-based processes for community assembly change at two spatial scales: metacommunity scale, i.e. within a locality, and biogeographical scale, i.e. among localities widely scattered along a macroclimatic gradient. As expected, niche-based processes dominated the community assembly at metacommunity scale, while dispersal-based processes played a major role at biogeographical scale for both taxonomical groups. However, we also observed small but significant spatial effects at metacommunity scale and environmental effects at biogeographical scale. We also observed differences in diversity patterns between the two taxonomical groups corresponding to differences in their dispersal modes. Our results thus support the idea of continuity of processes interactively shaping diversity patterns across scales and emphasize the necessity of integration of metacommunity and biogeographical perspectives.

Encephalization And Diversification Of The Cranial Base In Platyrrhine Primates.

The cranial base, composed of the midline and lateral basicranium, is a structurally important region of the skull associated with several key traits, which has been extensively studied in anthropology and primatology. In particular, most studies have focused on the association between midline cranial base flexion and relative brain size, or encephalization. However, variation in lateral basicranial morphology has been studied less thoroughly. Platyrrhines are a group of primates that experienced a major evolutionary radiation accompanied by extensive morphological diversification in Central and South America over a large temporal scale. Previous studies have also suggested that they underwent several evolutionarily independent processes of encephalization. Given these characteristics, platyrrhines present an excellent opportunity to study, on a large phylogenetic scale, the morphological correlates of primate diversification in brain size. In this study we explore the pattern of variation in basicranial morphology and its relationship with phylogenetic branching and with encephalization in platyrrhines. We quantify variation in the 3D shape of the midline and lateral basicranium and endocranial volumes in a large sample of platyrrhine species, employing high-resolution CT-scans and geometric morphometric techniques. We investigate the relationship between basicranial shape and encephalization using phylogenetic regression methods and calculate a measure of phylogenetic signal in the datasets. The results showed that phylogenetic structure is the most important dimension for understanding platyrrhine cranial base diversification; only Aotus species do not show concordance with our molecular phylogeny. Encephalization was only correlated with midline basicranial flexion, and species that exhibit convergence in their relative brain size do not display convergence in lateral basicranial shape. The evolution of basicranial variation in primates is probably more complex than previously believed, and understanding it will require further studies exploring the complex interactions between encephalization, brain shape, cranial base morphology, and ecological dimensions acting along the species divergence process.

Using Imaging Spectroscopy to study soil properties

Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the 15 data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users, inhibiting researchers from trying this technique for their needs. The paper ends with a general call to the soil science audience to extend the utilization of the IS technique, and it provides some ideas on how to propel this technology forward to enable its widespread adoption in order to achieve a breakthrough in the field of soil science and remote sensing. (C) 2009 Elsevier Inc. All rights reserved.

A framework to monitor sustainability in the grains industry

Community awareness of the sustainable use of land, water and vegetation resources is increasing. The sustainable use of these resources is pivotal to sustainable farming systems. However, techniques for monitoring the sustainable management of these resources are poorly understood and untested. We propose a framework to benchmark and monitor resources in the grains industry. Eight steps are listed below to achieve these objectives: (i) define industry issues; (ii) identify the issues through growers, stakeholder and community consultation; (iii) identify indicators (measurable attributes, properties or characteristics) of sustainability through consultation with growers, stakeholders, experts and community members, relating to: crop productivity; resource maintenance/enhancement; biodiversity; economic viability; community viability; and institutional structure; (iv) develop and use selection criteria to select indicators that consider: responsiveness to change; ease of capture; community acceptance and involvement; interpretation; measurement error; stability, frequency and cost of measurement; spatial scale issues; and mapping capability in space and through time. The appropriateness of indicators can be evaluated using a decision making system such as a multiobjective decision support system (MO-DSS, a method to assist in decision making from multiple and conflicting objectives); (v) involve stakeholders and the community in the definition of goals and setting benchmarking and monitoring targets for sustainable farming; (vi) take preventive and corrective/remedial action; (vii) evaluate effectiveness of actions taken; and (viii) revise indicators as part of a continual improvement principle designed to achieve best management practice for sustainable farming systems. The major recommendations are to: (i) implement the framework for resources (land, water and vegetation, economic, community and institution) benchmarking and monitoring, and integrate this process with current activities so that awareness, implementation and evolution of sustainable resource management practices become normal practice in the grains industry; (ii) empower the grains industry to take the lead by using relevant sustainability indicators to benchmark and monitor resources; (iii) adopt a collaborative approach by involving various industry, community, catchment management and government agency groups to minimise implementation time. Monitoring programs such as Waterwatch, Soilcheck, Grasscheck and Topcrop should be utilised; (iv) encourage the adoption of a decision making system by growers and industry representatives as a participatory decision and evaluation process. Widespread use of sustainability indicators would assist in validating and refining these indicators and evaluating sustainable farming systems. The indicators could also assist in evaluating best management practices for the grains industry.

Life tables of the processionary caterpillar Ochrogaster lunifer Herrich-Schaffer (Lepidoptera : Thaumetopoeidae) at local and regional scales

A major ongoing debate in population ecology has surrounded the causative factors underlying the abundance of phytophagous insects and whether or not these factors limit or regulate herbivore populations. However, it is often difficult to identify mortality agents in census data, and their distribution and relative importance across large spatial scales are rarely understood. Were, we present life tables for egg batches and larval cohorts of the processionary caterpillar Ochrogaster lunifer Herrich-Schaffer, using intensive local sampling combined with extensive regional monitoring to ascertain the relative importance of different mortality factors at different localities. Extinction of entire cohorts (representing the entire reproductive output of one female) at natural localities was high, with 82% of the initial 492 cohorts going extinct. Mortality was highest in the egg and early instar stages due to predation from dermestid beetles, and while different mortality factors (e.g. hatching failure, egg parasitism and failure to establish on the host) were present at many localities, dermestid predation, either directly observed or inferred from indirect evidence, was the dominant mortality factor at 89% of localities surveyed. Predation was significantly higher in plantations than in natural habitats. The second most important mortality factor was resource depletion, with 14 cohorts defoliating their hosts. Egg and larval parasitism were not major mortality agents. A combination of predation and resource depletion consistently accounted for the majority of mortality across localities, suggesting that both factors are important in limiting population abundance. This evidence shows that O. lunifer is not regulated by natural enemies alone, but that resource patches (Acacia trees) ultimately, and frequently, act together to limit population growth.

Modelling solute transport in structured soils: Performance evaluation of the ADR and TRM models

The movement of chemicals through the soil to the groundwater or discharged to surface waters represents a degradation of these resources. In many cases, serious human and stock health implications are associated with this form of pollution. The chemicals of interest include nutrients, pesticides, salts, and industrial wastes. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals, and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and nonequilibrium between soil constituents, water, and solutes. A multiple sample percolation system (MSPS), consisting of 25 individual collection wells, was constructed to study the effects of localized soil heterogeneities on the transport of nutrients (NO3-, Cl-, PO43-) in the vadose zone of an agricultural soil predominantly dominated by clay. Very significant variations in drainage patterns across a small spatial scale were observed tone-way ANOVA, p < 0.001) indicating considerable heterogeneity in water flow patterns and nutrient leaching. Using data collected from the multiple sample percolation experiments, this paper compares the performance of two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR), and a two-region preferential flow model (TRM) suitable for modelling nonequilibrium transport. These results have implications for modelling solute transport and predicting nutrient loading on a larger scale. (C) 2001 Elsevier Science Ltd. All rights reserved.

The effect of resource aggregation at different scales: Optimal foraging behavior of Cotesia rubecula

Resources can be aggregated both within and between patches. In this article, we examine how aggregation at these different scales influences the behavior and performance of foragers. We developed an optimal foraging model of the foraging behavior of the parasitoid wasp Cotesia rubecula parasitizing the larvae of the cabbage butterfly Pieris rapae. The optimal behavior was found using stochastic dynamic programming. The most interesting and novel result is that the effect of resource aggregation within and between patches depends on the degree of aggregation both within and between patches as well as on the local host density in the occupied patch, but lifetime reproductive success depends only on aggregation within patches. Our findings have profound implications for the way in which we measure heterogeneity at different scales and model the response of organisms to spatial heterogeneity.