On the Sources of Uncertainty in Exchange Rate Predictability

We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.

Transaction Costs and Institutions: Investments in Exchange

This paper proposes a simple model for understanding transaction costs for their composition, size and policy implications. We distinguish between investments in institutions that facilitate exchange and the cost of conducting exchange itself. Institutional quality and market size are determined by the decisions of risk averse agents and conditions are discussed under which the efficient allocation may be decentralized. We highlight a number of differences with models where transaction costs are exogenous, including the implications for taxation and measurement issues.

PSMA-Specific CAR-Engineered T Cells Eradicate Disseminated Prostate Cancer in Preclinical Models.

Immunology-based interventions have been proposed as a promising curative chance to effectively attack postoperative minimal residual disease and distant metastatic localizations of prostate tumors. We developed a chimeric antigen receptor (CAR) construct targeting the human prostate-specific membrane antigen (hPSMA), based on a novel and high affinity specific mAb. As a transfer method, we employed last-generation lentiviral vectors (LV) carrying a synthetic bidirectional promoter capable of robust and coordinated expression of the CAR molecule, and a bioluminescent reporter gene to allow the tracking of transgenic T cells after in vivo adoptive transfer. Overall, we demonstrated that CAR-expressing LV efficiently transduced short-term activated PBMC, which in turn were readily stimulated to produce cytokines and to exert a relevant cytotoxic activity by engagement with PSMA+ prostate tumor cells. Upon in vivo transfer in tumor-bearing mice, CAR-transduced T cells were capable to completely eradicate a disseminated neoplasia in the majority of treated animals, thus supporting the translation of such approach in the clinical setting.

Energetics of RecA-mediated recombination reactions. Without ATP hydrolysis RecA can mediate polar strand exchange but is unable to recycle.

We demonstrate that the step of DNA strand exchange during RecA-mediated recombination reaction can occur equally efficiently in the presence or absence of ATP hydrolysis. The polarity of strand exchange is the same when instead of ATP its non-hydrolyzable analog adenosine-5'-O-(3-thiotriphosphate) is used. We show that the ATP dependence of recombination reaction is limited to the post-exchange stages of the reactions. The low DNA affinity state of RecA protomers, induced after ATP hydrolysis, is necessary for the dissociation of RecA-DNA complexes at the end of the reaction. This dissociation of RecA from DNA is necessary for the release of recombinant DNA molecules from the complexes formed with RecA and for the recycling of RecA protomers for another round of the recombination reaction.

Review of therapeutic drug monitoring of anticancer drugs part one - Cytotoxics.

Most anticancer drugs are characterised by a steep dose-response relationship and narrow therapeutic window. Inter-individual pharmacokinetic (PK) variability is often substantial. The most relevant PK parameter for cytotoxic drugs is the area under the plasma concentration versus time curve (AUC). Thus it is somewhat surprising that therapeutic drug monitoring (TDM) is still uncommon for the majority of agents. Goals of the review were to assess the rationale for more widely used TDM of cytotoxics in oncology. There are several reasons why TDM has never been fully implemented into daily oncology practice. These include difficulties in establishing appropriate concentration target ranges, common use of combination chemotherapies for many tumour types, analytical challenges with prodrugs, intracellular compounds, the paucity of published data from pharmacological trials and 'Day1=Day21' administration schedules. There are some specific situations for which these limitations are overcome, including high dose methotrexate, 5-fluorouracil infusion, mitotane and some high dose chemotherapy regimens. TDM in paediatric oncology represents an important challenge. Established TDM approaches includes the widely used anticancer agents carboplatin, busulfan and methotrexate, with 13-cis-retinoic acid also recently of interest. Considerable effort should be made to better define concentration-effect relationships and to utilise tools such as population PK/PD models and comparative randomised trials of classic dosing versus pharmacokinetically guided adaptive dosing. There is an important heterogeneity among clinical practices and a strong need to promote TDM guidelines among the oncological community.

Towards the validation of "in silico" models and physicochemical filters to identify and characterize new chemical entities

Summary: Lipophilicity plays an important role in the determination and the comprehension of the pharmacokinetic behavior of drugs. It is usually expressed by the partition coefficient (log P) in the n-octanol/water system. The use of an additional solvent system (1,2-dichlorethane/water) is necessary to obtain complementary information, as the log Poct values alone are not sufficient to explain ail biological properties. The aim of this thesis is to develop tools allowing to predict lipophilicity of new drugs and to analyze the information yielded by those log P values. Part I presents the development of theoretical models used to predict lipophilicity. Chapter 2 shows the necessity to extend the existing solvatochromic analyses in order to predict correctly the lipophilicity of new and complex neutral compounds. In Chapter 3, solvatochromic analyses are used to develop a model for the prediction of the lipophilicity of ions. A global model was obtained allowing to estimate the lipophilicity of neutral, anionic and cationic solutes. Part II presents the detailed study of two physicochemical filters. Chapter 4 shows that the Discovery RP Amide C16 stationary phase allows to estimate lipophilicity of the neutral form of basic and acidic solutes, except of lipophilic acidic solutes. Those solutes present additional interactions with this particular stationary phase. In Chapter 5, 4 different IANI stationary phases are investigated. For neutral solutes, linear data are obtained whatever the IANI column used. For the ionized solutes, their retention is due to a balance of electrostatic and hydrophobie interactions. Thus no discrimination is observed between different series of solutes bearing the same charge, from one column to an other. Part III presents two examples illustrating the information obtained thanks to Structure-Properties Relationships (SPR). Comparing graphically lipophilicity values obtained in two different solvent systems allows to reveal the presence of intramolecular effects .such as internai H-bond (Chapter 6). SPR is used to study the partitioning of ionizable groups encountered in Medicinal Chemistry (Chapter7). Résumé La lipophilie joue un .rôle important dans la détermination et la compréhension du comportement pharmacocinétique des médicaments. Elle est généralement exprimée par le coefficient de partage (log P) d'un composé dans le système de solvants n-octanol/eau. L'utilisation d'un deuxième système de solvants (1,2-dichloroéthane/eau) s'est avérée nécessaire afin d'obtenir des informations complémentaires, les valeurs de log Poct seules n'étant pas suffisantes pour expliquer toutes les propriétés biologiques. Le but de cette thèse est de développer des outils permettant de prédire la lipophilie de nouveaux candidats médicaments et d'analyser l'information fournie par les valeurs de log P. La Partie I présente le développement de modèles théoriques utilisés pour prédire la lipophilie. Le chapitre 2 montre la nécessité de mettre à jour les analyses solvatochromiques existantes mais inadaptées à la prédiction de la lipophilie de nouveaux composés neutres. Dans le chapitre 3, la même méthodologie des analyses solvatochromiques est utilisée pour développer un modèle permettant de prédire la lipophilie des ions. Le modèle global obtenu permet la prédiction de la lipophilie de composés neutres, anioniques et cationiques. La Partie II présente l'étude approfondie de deux filtres physicochimiques. Le Chapitre 4 montre que la phase stationnaire Discovery RP Amide C16 permet la détermination de la lipophilie de la forme neutre de composés basiques et acides, à l'exception des acides très lipophiles. Ces derniers présentent des interactions supplémentaires avec cette phase stationnaire. Dans le Chapitre 5, 4 phases stationnaires IAM sont étudiées. Pour les composés neutres étudiés, des valeurs de rétention linéaires sont obtenues, quelque que soit la colonne IAM utilisée. Pour les composés ionisables, leur rétention est due à une balance entre des interactions électrostatiques et hydrophobes. Donc aucune discrimination n'est observée entre les différentes séries de composés portant la même charge d'une colonne à l'autre. La Partie III présente deux exemples illustrant les informations obtenues par l'utilisation des relations structures-propriétés. Comparer graphiquement la lipophilie mesurée dans deux différents systèmes de solvants permet de mettre en évidence la présence d'effets intramoléculaires tels que les liaisons hydrogène intramoléculaires (Chapitre 6). Cette approche des relations structures-propriétés est aussi appliquée à l'étude du partage de fonctions ionisables rencontrées en Chimie Thérapeutique (Chapitre 7) Résumé large public Pour exercer son effet thérapeutique, un médicament doit atteindre son site d'action en quantité suffisante. La quantité effective de médicament atteignant le site d'action dépend du nombre d'interactions entre le médicament et de nombreux constituants de l'organisme comme, par exemple, les enzymes du métabolisme ou les membranes biologiques. Le passage du médicament à travers ces membranes, appelé perméation, est un paramètre important à optimiser pour développer des médicaments plus puissants. La lipophilie joue un rôle clé dans la compréhension de la perméation passive des médicaments. La lipophilie est généralement exprimée par le coefficient de partage (log P) dans le système de solvants (non miscibles) n-octanol/eau. Les valeurs de log Poct seules se sont avérées insuffisantes pour expliquer la perméation à travers toutes les différentes membranes biologiques du corps humain. L'utilisation d'un système de solvants additionnel (le système 1,2-dichloroéthane/eau) a permis d'obtenir les informations complémentaires indispensables à une bonne compréhension du processus de perméation. Un grand nombre d'outils expérimentaux et théoriques sont à disposition pour étudier la lipophilie. Ce travail de thèse se focalise principalement sur le développement ou l'amélioration de certains de ces outils pour permettre leur application à un champ plus large de composés. Voici une brève description de deux de ces outils: 1)La factorisation de la lipophilie en fonction de certaines propriétés structurelles (telle que le volume) propres aux composés permet de développer des modèles théoriques utilisables pour la prédiction de la lipophilie de nouveaux composés ou médicaments. Cette approche est appliquée à l'analyse de la lipophilie de composés neutres ainsi qu'à la lipophilie de composés chargés. 2)La chromatographie liquide à haute pression sur phase inverse (RP-HPLC) est une méthode couramment utilisée pour la détermination expérimentale des valeurs de log Poct.

Glioprotective impact of cell-permeable peptides in preclinical models of amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disorder characterized by progressive degeneration of upper and lower motor neurons. It is mostly sporadic, but about 2% of cases are associated with mutations in the gene encoding the enzyme superoxide dismutase 1 (SOD1). A major constraint to the comprehension of the pathogenesis of ALS has been long represented by the conviction that this disorder selectively affects motor neurons in a cell-autonomous manner. However, the failure to identify the events underlying the neurodegenerative process and the increased knowledge of the complex cellular interactions necessary for the correct functioning of the CNS has recently focused the attention on the contribution to neurodegeneration of glial cells, including astrocytes. Astrocytes can hurt motor neurons directly by secreting neurotoxic factors, but they can also play a deleterious role indirectly by losing functions that are supportive for neurons. Recently, we reported that a subpopulation of astrocytes degenerates in the spinal cord of hSOD1G93A transgenic mouse model of ALS. Mechanistic studies in cultured astrocytes revealed that such effect is mediated by the excitatory amino acid glutamate.On the bsis of these observations, we next used the established cell culture model as a tool to screen the glioprotective effect of innovative drugs, namely cell-permeable therapeutics. These consist of peptidic effector moieties coupled to the selective intracellular peptide transporter TAT protein. We initially validated the usefulness of these molecules demonstrating that a control fluorescent peptide enters astrocytes in culture and is retained within the cells up to 24-48 h, according to the timing of our cytotoxicity experiments. We then tested the impact of specific intracellular peptides with antiapoptotic properties on glutamate-treated hSOD1G93A- expressing astrocytes and we identified one molecule that protects the cells from death. Chronic treatment of ALS mice with this peptide had a positive impact on the outcome of the disease.

One-year survival and neurological outcome after pediatric cardiopulmonary resuscitation.

OBJECTIVE: Reported survival after cardiopulmonary resuscitation (CPR) in children varies considerably. We aimed to identify predictors of 1-year survival and to assess long-term neurological status after in- or outpatient CPR. DESIGN: Retrospective review of the medical records and prospective follow-up of CPR survivors. SETTING: Tertiary care pediatric university hospital. PATIENTS AND METHODS: During a 30-month period, 89 in- and outpatients received advanced CPR. Survivors of CPR were prospectively followed-up for 1 year. Neurological outcome was assessed by the Pediatric Cerebral Performance Category scale (PCPC). Variables predicting 1-year survival were identified by multivariable logistic regression analysis. INTERVENTIONS: None. RESULTS: Seventy-one of the 89 patients were successfully resuscitated. During subsequent hospitalization do-not-resuscitate orders were issued in 25 patients. At 1 year, 48 (54%) were alive, including two of the 25 patients with out-of-hospital CPR. All patients died, who required CPR after trauma or near drowning, when CPR began >10 min after arrest or with CPR duration >60 min. Prolonged CPR (21-60 min) was compatible with survival (five of 19). At 1 year, 77% of the survivors had the same PCPC score as prior to CPR. Predictors of survival were location of resuscitation, CPR during peri- or postoperative care, and duration of resuscitation. A clinical score (0-15 points) based on these three items yielded an area under the ROC of 0.93. CONCLUSIONS: Independent determinants of long-term survival of pediatric resuscitation are location of arrest, underlying cause, and duration of CPR. Long-term survivors have little or no change in neurological status.

Genomic rearrangements in trypanosomatids: an alternative to the "one gene" evolutionary hypotheses?

Most molecular trees of trypanosomatids are based on point mutations within DNA sequences. In contrast, there are very few evolutionary studies considering DNA (re) arrangement as genetic characters. Waiting for the completion of the various parasite genome projects, first information may already be obtained from chromosome size-polymorphism, using the appropriate algorithms for data processing. Three illustrative models are presented here. First, the case of Leishmania (Viannia) braziliensis/L. (V.) peruviana is described. Thanks to a fast evolution rate (due essentially to amplification/deletion of tandemly repeated genes), molecular karyotyping seems particularly appropriate for studying recent evolutionary divergence, including eco-geographical diversification. Secondly, karyotype evolution is considered at the level of whole genus Leishmania. Despite the fast chromosome evolution rate, there is qualitative congruence with MLEE- and RAPD-based evolutionary hypotheses. Significant differences may be observed between major lineages, likely corresponding to major and less frequent rearrangements (fusion/fission, translocation). Thirdly, comparison is made with Trypanosoma cruzi. Again congruence is observed with other hypotheses and major lineages are delineated by significant chromosome rearrangements. The level of karyotype polymorphism within that "species" is similar to the one observed in "genus" Leishmania. The relativity of the species concept among these two groups of parasites is discussed.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Avian erythrocytes have functional mitochondria, opening novel perspectives for birds as animal models in the study of ageing.

BACKGROUND: In contrast to mammalian erythrocytes, which have lost their nucleus and mitochondria during maturation, the erythrocytes of almost all other vertebrate species are nucleated throughout their lifespan. Little research has been done however to test for the presence and functionality of mitochondria in these cells, especially for birds. Here, we investigated those two points in erythrocytes of one common avian model: the zebra finch (Taeniopygia guttata). RESULTS: Transmission electron microscopy showed the presence of mitochondria in erythrocytes of this small passerine bird, especially after removal of haemoglobin interferences. High-resolution respirometry revealed increased or decreased rates of oxygen consumption by erythrocytes in response to the addition of respiratory chain substrates or inhibitors, respectively. Fluorometric assays confirmed the production of mitochondrial superoxide by avian erythrocytes. Interestingly, measurements of plasmatic oxidative markers indicated lower oxidative stress in blood of the zebra finch compared to a size-matched mammalian model, the mouse. CONCLUSIONS: Altogether, those findings demonstrate that avian erythrocytes possess functional mitochondria in terms of respiratory activities and reactive oxygen species (ROS) production. Interestingly, since blood oxidative stress was lower for our avian model compared to a size-matched mammalian, our results also challenge the idea that mitochondrial ROS production could have been one actor leading to this loss during the course of evolution. Opportunities to assess mitochondrial functioning in avian erythrocytes open new perspectives in the use of birds as models for longitudinal studies of ageing via lifelong blood sampling of the same subjects.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Genetic analysis of phenoxyalkanoic acid degradation in Sphingomonas herbicidovorans MH.

Phenoxyalkanoic acid degradation is well studied in Beta- and Gammaproteobacteria, but the genetic background has not been elucidated so far in Alphaproteobacteria. We report the isolation of several genes involved in dichlor- and mecoprop degradation from the alphaproteobacterium Sphingomonas herbicidovorans MH and propose that the degradation proceeds analogously to that previously reported for 2,4-dichlorophenoxyacetic acid (2,4-D). Two genes for alpha-ketoglutarate-dependent dioxygenases, sdpA(MH) and rdpA(MH), were found, both of which were adjacent to sequences with potential insertion elements. Furthermore, a gene for a dichlorophenol hydroxylase (tfdB), a putative regulatory gene (cadR), two genes for dichlorocatechol 1,2-dioxygenases (dccA(I/II)), two for dienelactone hydrolases (dccD(I/II)), part of a gene for maleylacetate reductase (dccE), and one gene for a potential phenoxyalkanoic acid permease were isolated. In contrast to other 2,4-D degraders, the sdp, rdp, and dcc genes were scattered over the genome and their expression was not tightly regulated. No coherent pattern was derived on the possible origin of the sdp, rdp, and dcc pathway genes. rdpA(MH) was 99% identical to rdpA(MC1), an (R)-dichlorprop/alpha-ketoglutarate dioxygenase from Delftia acidovorans MC1, which is evidence for a recent gene exchange between Alpha- and Betaproteobacteria. Conversely, DccA(I) and DccA(II) did not group within the known chlorocatechol 1,2-dioxygenases, but formed a separate branch in clustering analysis. This suggests a different reservoir and reduced transfer for the genes of the modified ortho-cleavage pathway in Alphaproteobacteria compared with the ones in Beta- and Gammaproteobacteria.

Three essays in international finance

Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.

Arctic warming will promote Atlantic-Pacific fish interchange

Throughout much of the Quaternary Period, inhospitable environmental conditions above the Arctic Circle have been a formidable barrier separating most marine organisms in the North Atlantic from those in the North Pacific(1,2). Rapid warming has begun to lift this barrier(3), potentially facilitating the interchange of marine biota between the two seas(4). Here, we forecast the potential northward progression of 515 fish species following climate change, and report the rate of potential species interchange between the Atlantic and the Pacific via the Northwest Passage and the Northeast Passage. For this, we projected niche-based models under climate change scenarios and simulated the spread of species through the passages when climatic conditions became suitable. Results reveal a complex range of responses during this century, and accelerated interchange after 2050. By 2100 up to 41 species could enter the Pacific and 44 species could enter the Atlantic, via one or both passages. Consistent with historical and recent biodiversity interchanges(5,6), this exchange of fish species may trigger changes for biodiversity and food webs in the North Atlantic and North Pacific, with ecological and economic consequences to ecosystems that at present contribute 39% to global marine fish landings.