Kohalike ja invasiivsete röövtoiduliste suurselgrootute elupaigakasutus ja toitumissuhted Läänemere põhjaosas

Väitekirja elektrooniline versioon ei sisalda publikatsiooneRöövtoidulised suurselgrootud, peamiselt vähilaadsed, on rannikumere toitumisvõrgustikes oluliseks lüliks põhjaelustiku ja kalade vahel ning ühtlasi nad reguleerivad väiksemate selgrootute arvukust. Läänemere põhjaosas elas selle rühma esindajaid seni ainult kaks liiki – läänemere krevett (Palaemon adspersus) ja põhjamere garneel (Crangon crangon). Hiljuti lisandusid neile kohalikele liikidele kaks võõrliiki – elegantne krevett (Palaemon elegans) ja rändkrabi (Rhithropanopeus harrisii). Kohalike ja võõrliikidest röövtoiduliste suurselgrootute leviku, elupaigaeelistuste ja toitumise uurimiseks kasutati olemasolevaid põhjaelustiku leviku andmeid, spetsiaalselt uuritavatele liikidele suunatud proovide kogumist loodusest ja laborikatseid, kus rakendati muuhulgas loomade raadiomärgistamist. Võõrliigist kreveti levik oli ulatuslikum kui kohalike krevettide levik. Võõrliik oli kohalike krevettidega võrreldes enam seotud elupaikadega, millele on iseloomulikud etrofeerumise tunnused (kõrge toitainete kontsentratsioon, lühiealiste niitjate vetikate suur hulk). Krevettide toitumisuuringud näitasid, et uuritud Palaemon liikide toitumisintensiivsus ja toidu kooseis ei erinenud. Seega on kohaliku ja võõrkreveti roll rannikumere toiduvõrkudes sarnane, ent võõrliik võib troofilisi suhteid ümber kujundada piirkondades, kus kohalikud krevetid puuduvad. Kõige kitsama elupaigakasutusega oli põhjamere garneel ja Palaemon liikidest oli võõrliigi P. elegans spetsialiseerumise tase mõnevõrra kõrgem kui kohalikul liigil. R. harrisii eelistas põisadruga (Fucus vesiculosus) elupaika mis viitab sellele, et põisadruga elupaik pakub krabile aastaringset stabiilset elupaika ja et mitmekesine põhjakooslus võib saada seetõttu krabidest oluliselt mõjutatud. Doktoritöö tulemused näitasid, et elupaikade iseloom ja seisund mõjutab kohalike ja võõrliikide levikumustreid ning võõrliikidest selgrootute kiskjate saabumine ja kiire levila laienemine Läänemere põhjaosas toovad kaasa täiesti uue ökoloogilise funktsiooni (suuremõõtmeline kiskja) või juba varem regionaalselt esinenud funktsiooni leviku piirkondadesse, kus see varem puudus.Decapod crustaceans, such as crabs and shrimps play an important role in coastal ecosystems as they prey on small benthic invertebrates and at the same time they are an important food item for fishes. Until recently, this group of macroinvertebrates consisted of only a few species in the northern Baltic Sea, including only two species of native shrimps – Crangon crangon and Palaemon adspersus. However, very recently two non-native crustacean predators arrived – the shrimp Palaemon elegans and the crab Rhithropanopeus harrisii. Data from available databases were used together with field sampling and laboratory experiments (incl. radio frequency positioning technology) to describe the geographical distribution, habitat selection, and feeding of native and invasive predatory crustaceans in the coastal areas of the northern Baltic Sea. The distribution of the non-native P. elegans was wider than that of native species. P. elegans was associated with lower salinity, higher concentrations of nutrients and higher proportions of ephemeral filamentous algae, relative to P. adspersus. According to results of the experiment on feeding activity, P. elegans performs a similar role in the coastal food web as the native congener, although it may rearrange trophic interactions and introduce new ecological function in the most eutrophicated areas previously lacking any native shrimp. Among the studied shrimps, C. crangon had the highest habitat specialization. The non-native P. elegans showed slightly higher habitat specialization compared to the native P. adspersus. The invasive crab R. harrisii preferred habitats with bladder wrack where the diverse native community may become heavily impacted by this novel large-bodied predator. This thesis showed that the successful establishment of non-native predatory invertebrates can introduce new ecological functions (large-bodied predators) or considerably strengthen already existed ones, while the heterogeneity of habitats has varying effects on the distribution patterns of native and invasive species

(Non)Parallel Evolution

Parallel evolution across replicate populations has provided evolutionary biologists with iconic examples of adaptation. When multiple populations colonize seemingly similar habitats, they may evolve similar genes, traits, or functions. Yet, replicated evolution in nature or in the laboratory often yields inconsistent outcomes: Some replicate populations evolve along highly similar trajectories, whereas other replicate populations evolve to different extents or in distinct directions. To understand these heterogeneous outcomes, biologists are increasingly treating parallel evolution not as a binary phenomenon but rather as a quantitative continuum ranging from parallel to nonparallel. By measuring replicate populations’ positions along this (non)parallel continuum, we can test hypotheses about evolutionary and ecological factors that influence the extent of repeatable evolution. We review evidence regarding the manifestation of (non)parallel evolution in the laboratory, in natural populations, and in applied contexts such as cancer. We enumerate the many genetic, ecological, and evolutionary processes that contribute to variation in the extent of parallel evolution

Combining Exploration and Exploitation in Active Learning

This thesis investigates the active learning in the presence of model bias. State of the art approaches advocate combining exploration and exploitation in active learning. However, they suffer from premature exploitation or unnecessary exploration in the later stages of learning. We propose to combine exploration and exploitation in active learning by discarding instances outside a sampling window that is centered around the estimated decision boundary and uniformly draw sample from this window. Initially the window spans the entire feature space and is gradually constricted, where the rate of constriction models the exploration-exploitation tradeoff. The desired effect of this approach (CExp) is that we get an increasing sampling density in informative regions as active learning progresses, resulting in a continuous and natural transition from exploration to exploitation, limiting both premature exploitation and unnecessary exploration. We show that our approach outperforms state of the art on real world multiclass datasets. We also extend our approach to spatial mapping problems where the standard active learning assumption of uniform costs is violated. We show that we can take advantage of \emph{spatial continuity} in the data by geographically partitioning the instances in the sampling window and choosing a single partition (region) for sampling, as opposed to taking a random sample from the entire window, resulting in a novel spatial active learning algorithm that combines exploration and exploitation. We demonstrate that our approach (CExp-Spatial) can generate cost-effective sampling trajectories over baseline sampling methods. Finally, we present the real world problem of mapping benthic habitats where bathymetry derived features are typically not strong enough to discriminate the fine details between classes identified from high-resolution imagery, increasing the possiblity of model bias in active learning. We demonstrate, under such conditions, that CExp outperforms state of the art and that CExp-Spatial can generate more cost-effective sampling trajectories for an Autonomous Underwater Vehicle in contrast to baseline sampling strategies

Combining Exploration and Exploitation in Active Learning

This thesis investigates the active learning in the presence of model bias. State of the art approaches advocate combining exploration and exploitation in active learning. However, they suffer from premature exploitation or unnecessary exploration in the later stages of learning. We propose to combine exploration and exploitation in active learning by discarding instances outside a sampling window that is centered around the estimated decision boundary and uniformly draw sample from this window. Initially the window spans the entire feature space and is gradually constricted, where the rate of constriction models the exploration-exploitation tradeoff. The desired effect of this approach (CExp) is that we get an increasing sampling density in informative regions as active learning progresses, resulting in a continuous and natural transition from exploration to exploitation, limiting both premature exploitation and unnecessary exploration. We show that our approach outperforms state of the art on real world multiclass datasets. We also extend our approach to spatial mapping problems where the standard active learning assumption of uniform costs is violated. We show that we can take advantage of \emph{spatial continuity} in the data by geographically partitioning the instances in the sampling window and choosing a single partition (region) for sampling, as opposed to taking a random sample from the entire window, resulting in a novel spatial active learning algorithm that combines exploration and exploitation. We demonstrate that our approach (CExp-Spatial) can generate cost-effective sampling trajectories over baseline sampling methods. Finally, we present the real world problem of mapping benthic habitats where bathymetry derived features are typically not strong enough to discriminate the fine details between classes identified from high-resolution imagery, increasing the possiblity of model bias in active learning. We demonstrate, under such conditions, that CExp outperforms state of the art and that CExp-Spatial can generate more cost-effective sampling trajectories for an Autonomous Underwater Vehicle in contrast to baseline sampling strategies

Growth and Migration of Benthic Habitats: A Spatial Microsimulation Approach

Spatiotemporal visualization of the impact of geomorphological changes in coastlines benthic habitats can generate insight needful in understanding the spatial ecology of seafloors and in anticipating the location, growth and migration of marine sanctuary and marine protected areas (MPAs). Such understanding has implication for effective development and conservation of these MPAs. To date, there are limited studies that have applied complex adaptive systems (CAS) to investigate the impact of geomorphological changes on the location, growth and migration of benthic habitats. Also, there is a gap in our knowledge of the marine geographical information system (marine GIS). To fill these gaps in the literature, we propose the use of the CAS theory as a lens to study the growth and migration of underwater (benthic) habitats in the Hawaii coastline using bathymetric SoNAR Multibeam data. We investigate the research question that concerns whether spatial approach helps in understanding the impact of projected geomorphological changes on patterns of growth and migration of benthic habitats of Hawaii coastlines. We develop a spatiotemporal IT antifact that engages a prediction machine to project individual data units (micro-data) to future states based on geomorphological changes using dynamic spatial microsimulation based method. The results of our study provide evidence of the contributions of spatial approach to understanding benthic habitat. The results also present research and practical implications for marine exploration and resource managers, and governments