A systematic-ecological approach to Baltic Sea ice studies of algae and protists

The seasonal occurrence of sea ice that annually covers almost half the Baltic Sea area provides a unique habitat for halo- and cold temperature-tolerant extremophiles. Baltic Sea ice biology has more than 100 years of tradition that began with the floristic observation of species by the early pioneers using light microscopic techniques that were the only thing available at the time. Since the discovery of life within sea ice, more technologies have become available for taxonomy. Electron microscopy and genetic evidence have been used to identify sea ice biota revealing increased numbers of taxa. Meanwhile ecologists have used light microscopic cell enumeration in addition to the chemical and physical properties of sea ice in attempts to explain the food web structure of sea ice and its functions. Thus, during the Baltic winter, the sea ice hosts more abundant and diverse microbial communities than the water column beneath it. These communities are typically dominated by autotrophic diatoms together with a diverse assortment of dinoflagellates, auto- and heterotrophic flagellates, ciliates, metazoan rotifers and bacteria, which are mostly responsible for the recycling of nutrients. This thesis comprises ecological and systematic studies. In addition to the results of the previous studies carried out on landfast ice, the data presented here provide new insight into the spatial distribution of pelagial sea ice, which has remained largely unexplored. The studies reveal spatial heterogeneity in the pelagial sea ice of the Gulf of Bothnia. There were mismatches in chlorophyll-a concentrations and in photosynthetic efficiencies of the communities studied. The temporal succession was followed and experimental studies performed investigating the community responses towards increased or decreased light in landfast ice in the Gulf of Finland. The systematic studies carried out with established dinoflagellate cultures revealed a new resting cyst belonging to common sea ice dinoflagellate, Scrippsiella hangoei (Schiller) Larsen 1995. The cyst can be used to explain the overwintering of this species during prolonged periods of darkness. The dissimilarities and similarities in the material isolated from the sea ice called for description of a new subspecies Heterocapsa arctica ssp. frigida. The cells obtained in the cultured material were unlike those of the previously described species, necessitating description of ssp. frigida. As a result of its own unique habitus, the subspecies had been noted by Finnish taxonomists during the past three decades and thus its annual occurrence and geographical distribution in the Baltic Sea. This illustrates how combining ecology and systematics increases our understanding of organisms.

Complexity of collaborative work in residential aged care facilities: An analysis of information exchange for medication management

Information exchange (IE) is a critical component of the complex collaborative medication process in residential aged care facilities (RACFs). Designing information and communication technology (ICT) to support complex processes requires a profound understanding of the IE that underpins their execution. There is little existing research that investigates the complexity of IE in RACFs and its impact on ICT design. The aim of this study was thus to undertake an in-depth exploration of the IE process involved in medication management to identify its implications for the design of ICT. The study was undertaken at a large metropolitan facility in NSW, Australia. A total of three focus groups, eleven interviews and two observation sessions were conducted between July to August 2010. Process modelling was undertaken by translating the qualitative data via in-depth iterative inductive analysis. The findings highlight the complexity and collaborative nature of IE in RACF medication management. These models emphasize the need to: a) deal with temporal complexity; b) rely on an interdependent set of coordinative artefacts; and c) use synchronous communication channels for coordination. Taken together these are crucial aspects of the IE process in RACF medication management that need to be catered for when designing ICT in this critical area. This study provides important new evidence of the advantages of viewing process as a part of a system rather than as segregated tasks as a means of identifying the latent requirements for ICT design and that is able to support complex collaborative processes like medication management in RACFs. © 2012 IEEE.

Mycorrhizal fungi and nitrogen dynamics in drained peatland

Fungi have a fundamental role in carbon and nutrient transformations in the acids soils of boreal regions, such as peatlands, where high amounts of carbon (C) and nutrients are stored in peat, the pH is relatively low and the nutrient uptake of trees is highly dependent on mycorrhizae. In this thesis, the aim was to examine nitrogen (N) transformations and the availability of dissolved N compounds in forestry-drained peatlands, to compare the fungal community biomass and structure at various peat N levels, to investigate the growth of ectomycorrhizal fungi with variable P and K availability and to assess how the ectomycorrhizal fungi (ECM) affect N transformations. Both field and laboratory experiments were carried out. The peat N concentration did not affect the soil fungal community structure within a site. Phosphorus (P) and potassium (K) deficiency of the trees as well as the degree of decomposition and dissolved organic nitrogen (DON) concentration of the peat were shown to affect the fungal community structure and biomass of ECMs, highlighting the complexity of the below ground system on drained peatlands. The biomass of extrametrical mycorrhizal mycelia (EMM) was enhanced by P and/or K deficiency of the trees, and ECM biomass in the roots was increased by P deficiency. Thus, PK deficiency in drained peatlands may increase the allocation of C by the tree to ECMs. It was also observed that fungi can alter N mineralization processes in the rhizosphere but variously depending on fungal species and fertility level of peat. Gross N mineralization did not vary but the net N mineralization rate significantly increased along the N gradient in both field and laboratory experiments. Gross N immobilization also significantly increased when the peat N concentration increased. Nitrification was hardly detectable in either field or laboratory experiments. During the growing season, dissolved inorganic N (DIN) fluctuated much more than the relatively stable DON. Special methodological challenges associated with sampling and analysis in microbial studies on peatlands are discussed.

The Emerging Phenotype: Ecological Genetics of Color, Form and Sex in the Common Frog

One of the main aims of evolutionary biology is to explain why organisms vary phenotypically as they do. Proximately, this variation arises from genetic differences and from environmental influences, the latter of which is referred to as phenotypic plasticity. Phenotypic plasticity is thus a central concept in evolutionary biology, and understanding its relative importance in causing the phenotypic variation and differentiation is important, for instance in anticipating the consequences of human induced environmental changes. The aim of this thesis was to study geographic variation and local adaptation, as well as sex ratios and environmental sex reversal, in the common frog (Rana temporaria). These themes cover three different aspects of phenotypic plasticity, which emerges as the central concept for the thesis. The first two chapters address geographic variation and local adaptation in two potentially thermally adaptive traits, namely the degree of melanism and the relative leg length. The results show that although there is an increasing latitudinal trend in the degree of melanism in wild populations across Scandinavian Peninsula, this cline has no direct genetic basis and is thus environmentally induced. The second chapter demonstrates that although there is no linear, latitudinally ordered phenotypic trend in relative leg length that would be expected under Allen s rule an ecogeographical rule linking extremity length to climatic conditions there seems to be such a trend at the genetic level, hidden under environmental effects. The first two chapters thus view phenotypic plasticity through its ecological role and evolution, and demonstrate that it can both give rise to phenotypic variation and hide evolutionary patterns in studies that focus solely on phenotypes. The last three chapters relate to phenotypic plasticity through its ecological and evolutionary role in sex determination, and consequent effects on population sex ratio, genetic recombination and the evolution of sex chromosomes. The results show that while sex ratios are strongly female biased and there is evidence of environmental sex reversals, these reversals are unlikely to have caused the sex ratio skew, at least directly. The results demonstrate that environmental sex reversal can have an effect on the evolution of sex chromosomes, as the recombination patterns between them seem to be controlled by phenotypic, rather than genetic, sex. This potentially allows Y chromosomes to recombine, lending support for the recent hypothesis suggesting that sex-reversal may play an important role on the rejuvenation of Y chromosomes.

Ecological consequences of genetic modifications - an invasion analysis approach

Biological invasions are considered as one of the greatest threats to biodiversity, as they may lead to disruption and homogenization of natural communities, and in the worst case, to native species extinctions. The introduction of gene modified organisms (GMOs) to agricultural, fisheries and forestry practices brings them into contact with natural populations. GMOs may appear as new invasive species if they are able to (1) invade into natural habitats or (2) hybridize with their wild relatives. The benefits of GMOs, such as increased yield or decreased use of insecticides or herbicides in cultivation, may thus be reduced due the potential risks they may cause. A careful ecological risk analysis therefore has to precede any responsible GMO introduction. In this thesis I study ecological invasion in relation to GMOs, and what kind of consequences invasion may have in natural populations. A set of theoretical models that combine life-history evolution, population dynamics, and population genetics were developed for the hazard identification part of ecological risks assessment of GMOs. In addition, the potential benefits of GMOs in management of an invasive pest were analyzed. In the first study I showed that a population that is fluctuating due to scramble-type density dependence (due to, e.g., nutrient competition in plants) may be invaded by a population that is relatively more limited by a resource (e.g., light in plants) that is a cause of contest-type density dependence. This result emphasises the higher risk of invasion in unstable environments. The next two studies focused on escape of a growth hormone (GH) transgenic fish into a natural population. The results showed that previous models may have given too pessimistic a view of the so called Trojan gene -effect, where the invading genotype is harmful for the population as a whole. The previously suggested population extinctions did not occur in my studies, since the changes in mating preferences caused by the GH-fish were be ameliorated by decreased level of competition. The GH-invaders may also have to exceed a threshold density before invasion can be successful. I also showed that the prevalence of mature parr (aka. sneaker) strategy among GH-fish may have clear effect on invasion outcome. The fourth study assessed the risks and developed methods against the invasion of the Colorado Potato Beetle (CPB, Leptinotarsa decemlineata). I showed that the eradication of CPB is most important for the prevention of their establishment, but the cultivation of transgenic Bt-potato could also be effective. In general, my results emphasise that invasion of transgenic species or genotypes to be possible under certain realistic conditions and resulting in competitive exclusion, population decline through outbreeding depression and genotypic displacement of native species. Ecological risk assessment should regard the decline and displacement of the wild genotype by an introduced one as a consequence that is as serious as the population extinction. It will also be crucial to take into account different kinds of behavioural differences among species when assessing the possible hazards that GMOs may cause if escaped. The benefits found of GMO crops effectiveness in pest management may also be too optimistic since CPB may evolve resistance to Bt-toxin. The models in this thesis could be further applied in case specific risk assessment of GMOs by supplementing them with detailed data of the species biology, the effect of the transgene introduced to the species, and also the characteristics of the populations or the environments in the risk of being invaded.

The assessment of ecological condition in south-east Queensland, Australia: An evaluation of reliability across variable environments and surrogate efficacy for biodiversity values

Multimetric ecological condition assessment has become an important biodiversity management tool. This study was the first to examine the reliability of these ecological surrogates across variable environments, and the implications for surrogate efficacy. It was demonstrated that through strategic application and design of the multimetric ecological condition index, the effects of environmental gradients and disturbance regimes can be mitigated, and that ecological condition assessment may serve as a scientifically rigorous approach for conservation planning.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Low ML-Decoding Complexity, Large Coding Gain, Full-Rate, Full-Diversity STBCs for 2 x 2 and 4 x 2 MIMO Systems

This paper deals with low maximum-likelihood (ML)-decoding complexity, full-rate and full-diversity space-time block codes (STBCs), which also offer large coding gain, for the 2 transmit antenna, 2 receive antenna (2 x 2) and the 4 transmit antenna, 2 receive antenna (4 x 2) MIMO systems. Presently, the best known STBC for the 2 2 system is the Golden code and that for the 4 x 2 system is the DjABBA code. Following the approach by Biglieri, Hong, and Viterbo, a new STBC is presented in this paper for the 2 x 2 system. This code matches the Golden code in performance and ML-decoding complexity for square QAM constellations while it has lower ML-decoding complexity with the same performance for non-rectangular QAM constellations. This code is also shown to be information-lossless and diversity-multiplexing gain (DMG) tradeoff optimal. This design procedure is then extended to the 4 x 2 system and a code, which outperforms the DjABBA code for QAM constellations with lower ML-decoding complexity, is presented. So far, the Golden code has been reported to have an ML-decoding complexity of the order of for square QAM of size. In this paper, a scheme that reduces its ML-decoding complexity to M-2 root M is presented.

High-Rate Space-Time Coded Large-MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16 X 16 and 32 X 32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.

A Low-Complexity Near-ML Performance Achieving Algorithm for Large MIMO Detection

In this paper, we present a low-complexity, near maximum-likelihood (ML) performance achieving detector for large MIMO systems having tens of transmit and receive antennas. Such large MIMO systems are of interest because of the high spectral efficiencies possible in such systems. The proposed detection algorithm, termed as multistage likelihood-ascent search (M-LAS) algorithm, is rooted in Hopfield neural networks, and is shown to possess excellent performance as well as complexity attributes. In terms of performance, in a 64 x 64 V-BLAST system with 4-QAM, the proposed algorithm achieves an uncoded BER of 10(-3) at an SNR of just about 1 dB away from AWGN-only SISO performance given by Q(root SNR). In terms of coded BER, with a rate-3/4 turbo code at a spectral efficiency of 96 bps/Hz the algorithm performs close to within about 4.5 dB from theoretical capacity, which is remarkable in terms of both high spectral efficiency as well as nearness to theoretical capacity. Our simulation results show that the above performance is achieved with a complexity of just O(NtNt) per symbol, where N-t and N-tau denote the number of transmit and receive antennas.

Algebraic distributed space-time codes with low ML decoding complexity

"Extended Clifford algebras" are introduced as a means to obtain low ML decoding complexity space-time block codes. Using left regular matrix representations of two specific classes of extended Clifford algebras, two systematic algebraic constructions of full diversity Distributed Space-Time Codes (DSTCs) are provided for any power of two number of relays. The left regular matrix representation has been shown to naturally result in space-time codes meeting the additional constraints required for DSTCs. The DSTCs so constructed have the salient feature of reduced Maximum Likelihood (ML) decoding complexity. In particular, the ML decoding of these codes can be performed by applying the lattice decoder algorithm on a lattice of four times lesser dimension than what is required in general. Moreover these codes have a uniform distribution of power among the relays and in time, thus leading to a low Peak to Average Power Ratio at the relays.

A non-orthogonal cooperative multiple access (NCMA) protocol and low ML decoding complexity codes

A half-duplex constrained non-orthogonal cooperative multiple access (NCMA) protocol suitable for transmission of information from N users to a single destination in a wireless fading channel is proposed. Transmission in this protocol comprises of a broadcast phase and a cooperation phase. In the broadcast phase, each user takes turn broadcasting its data to all other users and the destination in an orthogonal fashion in time. In the cooperation phase, each user transmits a linear function of what it received from all other users as well as its own data. In contrast to the orthogonal extension of cooperative relay protocols to the cooperative multiple access channels wherein at any point of time, only one user is considered as a source and all the other users behave as relays and do not transmit their own data, the NCMA protocol relaxes the orthogonality built into the protocols and hence allows for a more spectrally efficient usage of resources. Code design criteria for achieving full diversity of N in the NCMA protocol is derived using pair wise error probability (PEP) analysis and it is shown that this can be achieved with a minimum total time duration of 2N - 1 channel uses. Explicit construction of full diversity codes is then provided for arbitrary number of users. Since the Maximum Likelihood decoding complexity grows exponentially with the number of users, the notion of g-group decodable codes is introduced for our setup and a set of necesary and sufficient conditions is also obtained.

Complexity of scheduling for minimum power on a GMAC

Two decision versions of a combinatorial power minimization problem for scheduling in a time-slotted Gaussian multiple-access channel (GMAC) are studied in this paper. If the number of slots per second is a variable, the problem is shown to be NP-complete. If the number of time-slots per second is fixed, an algorithm that terminates in O (Length (I)N+1) steps is provided.