Spatial and temporal variability in midge (Nematocera) assemblages in shallow Finnish lakes (60−70 °N) : community-based modelling of past environmental change

Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

Environmental factors affecting the occurrence of periglacial landforms in Finnish Lapland: a numerical approach

Determination of the environmental factors controlling earth surface processes and landform patterns is one of the central themes in physical geography. However, the identification of the main drivers of the geomorphological phenomena is often challenging. Novel spatial analysis and modelling methods could provide new insights into the process-environment relationships. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, field observations and the results of HP analyses. A total of 40 different landform types and subtypes were identified. Topographical, soil property and vegetation variables were the primary correlates for the occurrence and cover of active periglacial landforms on the landscape scale. In the model evaluation, most of the GLMs were shown to be robust although the explanation power, prediction ability as well as the selected explanatory variables varied between the models. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and significances of the environmental variables and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical approach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Environmental change and anthropogenic impact on lake sediments during the Holocene in the Finnish - Karelian inland area

This thesis discusses the prehistoric human disturbance during the Holocene by means of case studies using detailed high-resolution pollen analysis from lake sediment. The four lakes studied are situated between 61o 40' and 61o 50' latitudes in the Finnish Karelian inland area and vary between 2.4 and 28.8 ha in size. The existence of Early Metal Age population was one important question. Another study question concerned the development of grazing, and the relationship between slash-and-burn cultivation and permanent field cultivation. The results were presented as pollen percentages and pollen concentrations (grains cm 3). Accumulation values (grains cm 2 yr 1) were calculated for Lake Nautajärvi and Lake Orijärvi sediment, where the sediment accumulation rate was precisely determined. Sediment properties were determined using loss-on-ignition (LOI) and magnetic susceptibility (k). Dating methods used include both conventional and AMS 14C determinations, paleomagnetic dating and varve choronology. The isolation of Lake Kirjavalampi on the northern shore of Lake Ladoga took place ca. 1460 1300 BC. The long sediment cores from Finland, Lake Kirkkolampi and Lake Orijärvi in southeastern Finland and Lake Nautajärvi in south central Finland all extended back to the Early Holocene and were isolated from the Baltic basin ca. 9600 BC, 8600 BC and 7675 BC, respectively. In the long sediment cores, the expansion of Alnus was visible between 7200 - 6840 BC. The spread of Tilia was dated in Lake Kirkkolampi to 6600 BC, in Lake Orijärvi to 5000 BC and at Lake Nautajärvi to 4600 BC. Picea is present locally in Lake Kirkkolampi from 4340 BC, in Lake Orijärvi from 6520 BC and in Lake Nautajärvi from 3500 BC onwards. The first modifications in the pollen data, apparently connected to anthropogenic impacts, were dated to the beginning of the Early Metal Period, 1880 1600 BC. Anthropogenic activity became clear in all the study sites by the end of the Early Metal Period, between 500 BC AD 300. According to Secale pollen, slash-and-burn cultivation was practised around the eastern study lakes from AD 300 600 onwards, and at the study site in central Finland from AD 880 onwards. The overall human impact, however, remained low in the studied sites until the Late Iron Age. Increasing human activity, including an increase in fire frequency was detected from AD 800 900 onwards in the study sites in eastern Finland. In Lake Kirkkolampi, this included cultivation on permanent fields, but in Lake Orijärvi, permanent field cultivation became visible as late as AD 1220, even when the macrofossil data demonstrated the onset of cultivation on permanent fields as early as the 7th century AD. On the northern shore of Lake Ladoga, local activity became visible from ca. AD 1260 onwards and at Lake Nautajärvi, sediment the local occupation was traceable from 1420 AD onwards. The highest values of Secale pollen were recorded both in Lake Orijärvi and Lake Kirjavalampi between ca. AD 1700 1900, and could be associated with the most intensive period of slash-and-burn from AD 1750 to 1850 in eastern Finland.

Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

The Taita Hills in southeastern Kenya form the northernmost part of Africa’s Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor. Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable reflectance throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular reflectance field measurements were taken and where horizontal visibility meteorological data concurrent with image acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive surface reflectance factor within an RMSE of < 0.02 ps in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium- and high-resolution optical satellite imagery, as well the utilized SPOT data.

Effects of environmental variation on ecological and evolutionary dynamics

Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

Environmental effects of thermal and radioactive discharges from nuclear power plants in the boreal brackish-water conditions of the northern Baltic Sea

During recent decades, thermal and radioactive discharges from nuclear power plants into the aquatic environment have become the subject of lively debate as an ecological concern. The target of this thesis was to summarize the large quantity of results obtained in extensive monitoring programmes and studies carried out in recipient sea areas off the Finnish nuclear power plants at Loviisa and Olkiluoto during more than four decades. The Loviisa NPP is located on the coast of the Gulf of Finland and Olkiluoto NPP on that of the Bothnian Sea. The state of the Gulf of Finland is clearly more eutrophic; the nutrient concentrations in the surface water are about 1½ 2 times higher at Loviisa than at Olkiluoto, and the total phosphorus concentrations still increased in both areas (even doubled at Loviisa) between the early 1970s and 2000. Thus, it is a challenge to distinguish the local effects of thermal discharges from the general eutrophication process of the Gulf of Finland. The salinity is generally low in the brackish-water conditions of the northern Baltic Sea, being however about 1 higher at Olkiluoto than at Loviisa (the salinity of surface water varying at the latter from near to 0 in early spring to 4 6 in late autumn). Thus, many marine and fresh-water organisms live in the Loviisa area close to their limit of existence, which makes the biota sensitive to any additional stress. The characteristics of the discharge areas of the two sites differ from each other in many respects: the discharge area at Loviisa is a semi-enclosed bay in the inner archipelago, where the exchange of water is limited, while the discharge area at Olkiluoto is more open, and the exchange of water with the open Bothnian Sea is more effective. The effects of the cooling water discharged from the power plants on the temperatures in the sea were most obvious in winter. The formation of a permanent ice cover in the discharge areas has been delayed in early winter, and the break-up of the ice occurs earlier in spring. The prolonging of the growing season and the disturbance of the overwintering time, in conditions where the biota has adjusted to a distinct rest period in winter, have been the most significant biological effects of the thermal pollution. The soft-bottom macrofauna at Loviisa has deteriorated to the point of almost total extinction at many sampling stations during the past 40 years. A similar decline has been reported for the whole eastern Gulf of Finland. However, the local eutrophication process seems to have contributed into the decline of the zoobenthos in the discharge area at Loviisa. Thermal discharges have increased the production of organic matter, which again has led to more organic bottom deposits. These have in turn increased the tendency of the isolated deeps to a depletion of oxygen, and this has further caused strong remobilization of phosphorus from the bottom sediments. Phytoplankton primary production and primary production capacity doubled in the whole area between the late 1960s and the late 1990s, but started to decrease a little at the beginning of this century. The focus of the production shifted from spring to mid- and late summer. The general rise in the level of primary production was mainly due to the increase in nutrient concentrations over the whole Gulf of Finland, but the thermal discharge contributed to a stronger increase of production in the discharge area compared to that in the intake area. The eutrophication of littoral vegetation in the discharge area has been the most obvious, unambiguous and significant biological effect of the heated water. Myriophyllum spicatum, Potamogeton perfoliatus and Potamogeton pectinatus, and vigorous growths of numerous filamentous algae as their epiphytes have strongly increased in the vicinity of the cooling water outlet, where they have formed dense populations in the littoral zone in late summer. However, the strongest increase of phytobenthos has extended only to a distance of about 1 km from the outlet, i.e., the changes in vegetation have been largest in those areas that remain ice-free in winter. Similar trends were also discernible at Olkiluoto, but to a clearly smaller extent, which was due to the definitely weaker level of background eutrophy and nutrient concentrations in the Bothnian Sea, and the differing local hydrographical and biological factors prevailing in the Olkiluoto area. The level of primary production has also increased at Olkiluoto, but has remained at a clearly lower level than at Loviisa. In spite of the analogous changes observed in the macrozoobenthos, the benthic fauna has remained strong and diversified in the Olkiluoto area. Small amounts of local discharge nuclides were regularly detected in environmental samples taken from the discharge areas: tritium in seawater samples, and activation products, such as 60Co, 58Co, 54Mn, 110mAg, 51Cr, in suspended particulate matter, bottom sediments and in several indicator organisms (e.g., periphyton and Fucus vesiculosus) that effectively accumulate radioactive substances from the medium. The tritium discharges and the consequent detection frequency and concentrations of tritium in seawater were higher at Loviisa, but the concentrations of the activation products were higher at Olkiluoto, where traces of local discharge nuclides were also observed over a clearly wider area, due to the better exchange of water than at Loviisa, where local discharge nuclides were only detected outside Hästholmsfjärden Bay quite rarely and in smaller amounts. At the farthest, an insignificant trace amount (0.2 Bq kg-1 d.w.) of 60Co originating from Olkiluoto was detected in Fucus at a distance of 137 km from the power plant. Discharge nuclides from the local nuclear power plants were almost exclusively detected at the lower trophic levels of the ecosystems. Traces of local discharge nuclides were very seldom detected in fish, and even then only in very low quantities. As a consequence of the reduced discharges, the concentrations of local discharge nuclides in the environment have decreased noticeably in recent years at both Loviisa and Olkiluoto. Although the concentrations in environmental samples, and above all, the discharge data, are presented as seemingly large numbers, the radiation doses caused by them to the population and to the biota are very low, practically insignificant. The effects of the thermal discharges have been more significant, at least to the wildlife in the discharge areas of the cooling water, although the area of impact has been relatively small. The results show that the nutrient level and the exchange of water in the discharge area of a nuclear power plant are of crucial importance.

Archaea, Bacteria, and methane production along environmental gradients in fens and bogs

Metanogeenit ovat hapettomissa oloissa eläviä arkkien pääryhmään kuuluvia mikrobeja, joiden ainutlaatuisen aineenvaihdunnan seurauksena syntyy metaania. Ilmakehässä metaani on voimakas kasvihuonekaasu. Yksi suurimmista luonnon metaanilähteistä ovat kosteikot. Pohjoisten soiden metaanipäästöt vaihtelevat voimakkaasti eri soiden välillä ja yhden suon sisälläkin, riippuen muun muassa vuodenajasta, suotyypistä ja kasvillisuudesta. Väitöskirjatyössä tutkittiin metaanipäästöjen vaihtelun mikrobiologista taustaa. Tutkimuksessa selvitettiin suotyypin, vuodenajan, tuhkalannoituksen ja turvesyvyyden vaikutusta metanogeeniyhteisöihin sekä metaanintuottoon kolmella suomalaisella suolla. Lisäksi tutkittiin ei-metanogeenisia arkkeja ja bakteereita, koska ne muodostavat metaanin tuoton lähtöaineet osana hapetonta hajotusta. Mikrobiyhteisöt analysoitiin DNA- ja RNA-lähtöisillä, polymeraasiketjureaktioon (PCR) perustuvilla menetelmillä. Merkkigeeneinä käytettiin metaanin tuottoon liittyvää mcrA-geeniä sekä arkkien ja bakteerien ribosomaalista 16S RNA-geeniä. Metanogeeniyhteisöt ja metaanintuotto erosivat huomattavasti happaman ja vähäravinteisen rahkasuon sekä ravinteikkaampien sarasoiden välillä. Rahkasuolta löytyi lähes yksinomaan Methanomicrobiales-lahkon metanogeeneja, jotka tuottavat metaania vedystä ja hiilidioksidista. Sarasoiden metanogeeniyhteisöt olivat monimuotoisempia, ja niillä esiintyi myös asetaattia käyttäviä metanogeeneja. Vuodenaika vaikutti merkittävästi metaanintuottoon. Talvella havaittiin odottamattoman suuri metaanintuottopotentiaali sekä viitteitä aktiivisista metanogeeneista. Arkkiyhteisön koostumus sen sijaan vaihteli vain vähän. Tuhkalannoitus, jonka tarkoituksena on edistää puiden kasvua ojitetuilla soilla, ei merkittävästi vaikuttanut metaanintuottoon tai -tuottajiin. Ojitetun suon yhteisöt kuitenkin muuttuivat turvesyvyyden mukaan. Vertailtaessa erilaisia PCR-menetelmiä todettiin, että kolmella mcrA-geeniin kohdistuvalla alukeparilla havaittiin pääosin samat ojitetun suon metanogeenit, mutta lajien runsaussuhteet riippuvat käytetyistä alukkeista. Soilla havaitut bakteerit kuuluivat pääjaksoihin Deltaproteobacteria, Acidobacteria ja Verrucomicrobia. Lisäksi löydettiin Crenarchaeota-pääjakson ryhmiin 1.1c ja 1.3 kuuluvia ei-metanogeenisia arkkeja. Tulokset ryhmien esiintymisestä hapettomassa turpeessa antavat lähtökohdan selvittää niiden mahdollisia vuorovaikutuksia metanogeenien kanssa. Tutkimuksen tulokset osoittivat, että metanogeeniyhteisön koostumus heijastaa metaanintuottoon vaikuttavia kemiallisia tai kasvillisuuden vaihteluita kuten suotyyppiä. Soiden metanogeenien ja niiden fysiologian parempi tuntemus voi auttaa ennustamaan ympäristömuutosten vaikutusta soiden metaanipäästöihin.

Conceptual and statistical modelling of environmental effects in population dynamics

Population dynamics are generally viewed as the result of intrinsic (purely density dependent) and extrinsic (environmental) processes. Both components, and potential interactions between those two, have to be modelled in order to understand and predict dynamics of natural populations; a topic that is of great importance in population management and conservation. This thesis focuses on modelling environmental effects in population dynamics and how effects of potentially relevant environmental variables can be statistically identified and quantified from time series data. Chapter I presents some useful models of multiplicative environmental effects for unstructured density dependent populations. The presented models can be written as standard multiple regression models that are easy to fit to data. Chapters II IV constitute empirical studies that statistically model environmental effects on population dynamics of several migratory bird species with different life history characteristics and migration strategies. In Chapter II, spruce cone crops are found to have a strong positive effect on the population growth of the great spotted woodpecker (Dendrocopos major), while cone crops of pine another important food resource for the species do not effectively explain population growth. The study compares rate- and ratio-dependent effects of cone availability, using state-space models that distinguish between process and observation error in the time series data. Chapter III shows how drought, in combination with settling behaviour during migration, produces asymmetric spatially synchronous patterns of population dynamics in North American ducks (genus Anas). Chapter IV investigates the dynamics of a Finnish population of skylark (Alauda arvensis), and point out effects of rainfall and habitat quality on population growth. Because the skylark time series and some of the environmental variables included show strong positive autocorrelation, the statistical significances are calculated using a Monte Carlo method, where random autocorrelated time series are generated. Chapter V is a simulation-based study, showing that ignoring observation error in analyses of population time series data can bias the estimated effects and measures of uncertainty, if the environmental variables are autocorrelated. It is concluded that the use of state-space models is an effective way to reach more accurate results. In summary, there are several biological assumptions and methodological issues that can affect the inferential outcome when estimating environmental effects from time series data, and that therefore need special attention. The functional form of the environmental effects and potential interactions between environment and population density are important to deal with. Other issues that should be considered are assumptions about density dependent regulation, modelling potential observation error, and when needed, accounting for spatial and/or temporal autocorrelation.