Changes in spring arrival of Nearctic-Neotropical migrants attributed to multiscalar climate

Climate-related changes associated with the California marine ecosystem have been documented; however, there are no studies assessing changes in terrestrial vertebrate phenology on the Pacific coast of western North America. We analyze the spring phenology of 21 Nearctic-Neotropical migratory songbird species in central and northern CA. Using observational and banding data at multiple sites, we evaluate evidence for a change in arrival timing being linked to either nonclimatic or multiscalar climatic explanations. Using correlation analysis, of the 13 species with a significant ( P <0.10) change in arrival, the arrival timing of 10 species (77%) is associated with both temperature and a large-scale climate oscillation index (El Niño Southern Oscillation, ENSO; North Atlantic Oscillation, NAO; and/or Pacific Decadal Oscillation, PDO) at least at one location. Eight of the 13 species (62%) are advancing their migratory timing. All species for which spring arrival is associated with climate at multiple locations are exhibiting changes ( n =5) and all species lacking evidence for association between migration phenology and climate ( n =3) exhibit no change. Migrants tend to arrive earlier in association with warmer temperatures, positive NAO indices, and stronger ENSO indices. Twelve species negatively correlate ( P ≤0.05) with local or regional temperature at least at one location; five species negatively correlate with ENSO. Eleven species' arrival is correlated ( P ≤0.05) with NAO; 10 are negatively associated. After an exhaustive literature search, this is apparently the first documentation of an association between NAO and migratory phenology in western North America.     

Influence of seasonal weather and climate variability on crop yields in Scotland

The climatic sensitivity of four important agriculture crops (wheat, barley, oats, potatoes) in a northern temperate bioclimatic region is investigated using national-level yield data for 1963–2005. The climate variables include monthly and annual meteorological data, derived bioclimatic metrics, and the North Atlantic Oscillation index. Statistical analysis shows that significant relationships between yield and climate vary depending on the crop type and month but highlight the influence of precipitation (negative correlation) and sunshine duration (positive correlation) rather than temperature. Soil moisture deficit is shown to be a particular useful indicator of yield with drier summers providing the best yields for Scotland as a whole. It is also tentatively inferred that the sensitivity of these crops, particularly wheat and barley, to soil moisture deficits has increased in recent years. This suggests that improved crop yields are optimised for dry sunny years despite the continued prevalence of considerable inter-annual variability in seasonal weather.     

Estimating climate change,CO2 and technology development effects on wheat yield in northeast Iran

Wheat is the main food for the majority of Iran’s population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO₂ concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO₂ concentration (1 ppm^?1) was considered 0.05 % and was used to implement the effect of elevated CO₂. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from ?28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.     

Response of Spring Wheat (Triticum aestivum L.) Quality Traits and Yield to Sowing Date

The unpredictability and large fluctuation of the climatic conditions in rainfed regions do affect spring wheat yield and grain quality. These variations offer the opportunity for the production of better quality wheat. The effect of variable years, locations and sowing managements on wheat grain yield and quality was studied through field experiments using three genotypes, three locations for two years under rainfed conditions. The two studied years as contrasting years at three locations and sowing dates depicted variability in temperature and water stress during grain filling which resulted considerable change in grain yield and quality. Delayed sowing, years (2009–10) and location (Talagang) with high temperature and water stress resulted increased proline, and grain quality traits i.e. grain protein (GP) and grain ash (GA) than optimum conditions (during 2008–09, at Islamabad and early sowing). However, opposite trend was observed for dry gluten (DG), sodium dodecyl sulphate (SDS), SPAD content and grain yield irrespective of genotypes. The influence of variable climatic conditions was dominant in determining the quality traits and inverse relationship was observed among some quality traits and grain yield. It may be concluded that by selecting suitable locations and different sowing managements for subjecting the crop to desirable environmental conditions (temperature and water) quality traits of wheat crop could be modified.     

Agroclimatic conditions in Europe under climate change

To date, projections of European crop yields under climate change have been based almost entirely on the outputs of crop‐growth models. While this strategy can provide good estimates of the effects of climatic factors, soil conditions and management on crop yield, these models usually do not capture all of the important aspects related to crop management, or the relevant environmental factors. Moreover, crop‐simulation studies often have severe limitations with respect to the number of crops covered or the spatial extent. The present study, based on agroclimatic indices, provides a general picture of agroclimatic conditions in western and central Europe (study area lays between 8.5°W–27°E and 37–63.5°N), which allows for a more general assessment of climate‐change impacts. The results obtained from the analysis of data from 86 different sites were clustered according to an environmental stratification of Europe. The analysis was carried for the baseline (1971–2000) and future climate conditions (time horizons of 2030, 2050 and with a global temperature increase of 5 °C) based on outputs of three global circulation models. For many environmental zones, there were clear signs of deteriorating agroclimatic condition in terms of increased drought stress and shortening of the active growing season, which in some regions become increasingly squeezed between a cold winter and a hot summer. For most zones the projections show a marked need for adaptive measures to either increase soil water availability or drought resistance of crops. This study concludes that rainfed agriculture is likely to face more climate‐related risks, although the analyzed agroclimatic indicators will probably remain at a level that should permit rainfed production. However, results suggests that there is a risk of increasing number of extremely unfavorable years in many climate zones, which might result in higher interannual yield variability and constitute a challenge for proper crop management.     

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10 degrees N-17 degrees N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel-Guillot-Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10-50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level.     

Assessment of climatic indices limiting rainfed wheat yield

In this study variation of six climatic indices including accumulated precipitation (P), accumulated potential evapotranspiration (PET), accumulated actual evapotranspiration (AET), accumulated crop evapotranspiration (ETC), accumulated water stress (S) and climatic water deficit (D), was investigated. Climatic indices and their variation were calculated during seven growth stages of wheat in five locations in the northeast of Iran from 1983 to 2008. Principal component analysis (PCA) technique was applied to explore major modes of variation in the regional climatic indices during different crop growth stages. The principle component obtained for each region was correlated to the regional winter wheat yield. Finally the regional amount of water and precipitation use efficiency (WUE and PUE) were analyzed in order to assess any possible association with wheat yield. The results showed that the highest precipitation occurred during the tillering stage and spatially decreased from north (Bojnord) to south (Birjand) and from east (Mashhad) to west (Sabzevar). The difference between the highest and the lowest precipitation across all locations was 2.5 of standard value. The variation pattern of AET, compared to other indices, showed more similarity to variation of precipitation at different growth stages and the highest AET (more than 2 of standard value in all locations) occurred during the tillering stage. The PCA indicated that effective components varied in different locations. The most positive and effective components were types of evapotranspiration that are associated with crop (ETC and AET) and precipitation. However none of these effective PCs showed a significant correlation with final yield. The PUE and WUE analysis indicated that PUE provides more information to interpret the relationship between total amounts of precipitation and the final yield.     

Distribution-wide effects of climate on population densities of a declining migratory landbird

1. Increases in global temperatures have created concern about effects of climatic variability on populations, and climate has been shown to affect population dynamics in an increasing number of species. Testing for effects of climate on population densities across a species' distribution allows for elucidation of effects of climate that would not be apparent at smaller spatial scales. 2. Using autoregressive population models, we tested for effects of the North Atlantic Oscillation (NAO) and the El Ni?o Southern Oscillation (ENSO) on annual population densities of a North American migratory landbird, the yellow-billed cuckoo Coccyzus americanus, across the species' breeding distribution over a 37-year period (1966-2002). 3. Our results indicate that both the NAO and ENSO have affected population densities of C. americanus across much of the species' breeding range, with the strongest effects of climate in regions in which these climate systems have the strongest effects on local temperatures. Analyses also indicate that the strength of the effect of local temperatures on C. americanus populations was predictive of long-term population decline, with populations that were more negatively affected by warm temperatures experiencing steeper declines. 4. Results of this study highlight the importance of distribution-wide analyses of climatic effects and demonstrate that increases in global temperatures have the potential to lead to additional population declines.     

Influences of the atmospheric patterns on unstable climate-growth associations of western Mediterranean forests

Quantifying climate-growth associations is needed to evaluate how forest productivity will respond to climate change. Year-to-year fluctuations in forest productivity and radial growth are partly explained by local climatic conditions driven by large-scale atmospheric patterns. This is illustrated by Iberian forests in the western Mediterranean Basin, which are subjected to complex climatic and atmospheric influences such as Atlantic and Mediterranean cyclogenesis. The North Atlantic Oscillation (NAO) is one of the major atmospheric circulation patterns affecting Iberian forests since positive winter NAO phases lead to dry and warm conditions. The Western Mediterranean Oscillation (WeMO) may also explain Iberian forest growth in some areas since this index captures Mediterranean cyclogenesis and WeMO negative phases are linked to warm and wet spring to summer conditions. Here, we analyze the associations between atmospheric patterns, climate and tree growth and we determine if they are changing through time. We use dendrochronology to relate radial growth of four tree species (Pyrenean oak, Sweet chestnut, Maritime pine and Scots pine) growing in western Spain to climate conditions and the NAO and WeMO indices. Winter and early spring temperatures increased since the 1950s in the area whereas the negative association between winter precipitation and the NAO strengthened since then. However, mean temperature rise was particularly evident since the 1970s. Growth was reduced by dry conditions during the growing season (spring and summer), but also by cold and dry conditions during the previous autumn and winter. This explains why the NAO January and the WeMo April indices were negative to growth of three species excluding Pyrenean oak. The early 1970s reflected an inflection point in the instability of climate-growth associations in the study area. We conclude that the winter NAO is a relevant driver of forest growth in the western Iberian Peninsula forests but additional atmospheric patterns (WeMO) also affect, albeit to a minor extent, these forests.     

Linkages between common wheat yields and climate in Morocco (1982–2008)

In Morocco, wheat production shows a high inter-annual variability due to uncertain rainfall. In view of the importance of this resource to the country’s economy, it is important to gain a better understanding of the natural large-scale climate oscillation governing this variability. In this study, we analyzed de-trended (1) time series of common wheat yields (1983–2008) from 11 agricultural provinces that account for 80 % of national wheat production; (2) monthly rainfall and 10-day temperature from ten meteorological stations; (3) 10-day normalized difference vegetation index (NDVI) from the AVHRR sensor; (4) monthly atmospheric climate indices [North Atlantic Oscillation (NAO) and Scandinavian Pattern (SCA)] and monthly 500 hPa geopotentials fields; and (5) monthly sea surface temperature (SST) fields and indices (NIÑO3, Tropical North Atlantic and Tropical South Atlantic). The relationship between rainfall and temperature during tillering in early winter and grain filling in early spring and wheat yields already observed at the plot scale was also found to be significant at the provincial scale. The linkages between wheat yields and large scale climate have been analyzed for the first time over Morocco. In agreement with previous studies, results show a complex and competing influence of different climate phenomena. The NAO is found to be significantly related to yields during the early stage of wheat growth in December, whereas the SCA correlates with yields later in the season, in January and February. Interesting lagged correlations with higher lead time are also highlighted, with the leading modes of SST variability in the equatorial Atlantic during October (the “Atlantic Niño” mode) and in the North Atlantic (the “Atlantic tripole” mode) in February. Our conclusion is that regional climate indices and variables represent valuable information with which to increase lead time and skill regarding wheat yield predictions in Morocco.     

Increasing temperature cuts back crop yields in Hungary over the last 90 years

The transformation of climatic regime has an undeniable impact on plant production, but we rarely have long enough date series to examine the unfolding of such effects. The clarification of the relationship between crop plants and climate has a near‐immediate importance due to the impending human‐made global change. This study investigated the relationship between temperature, precipitation, drought intensity and the yields of four major cereals in Hungary between 1921 and 2010. The analysis of 30‐year segments indicated a monotonously increasing negative impact of temperature on crop yields. A 1°C temperature increase reduced the yield of the four main cereals by 9.6%–14.8% in 1981–2010, which revealed the vulnerability of Eastern European crop farming to recent climate change. Climate accounted for 17%–39% of yield variability over the past 90 years, but this figure reached 33%–67% between 1981 and 2010. Our analysis supports the claim that the mid‐20th century green revolution improved yields “at the mercy of the weather”: during this period, the impact of increasing fertilization and mechanisation coincided with climatic conditions that were more favourable than today. Crop yields in Eastern Europe have been stagnating or decreasing since the mid‐1980s. Although usually attributed to the large socio‐economic changes sweeping the region, our analysis indicates that a warming climate is at least partially responsible for this trend. Such a robust impact of increasing temperatures on crop yields also constitutes an obvious warning for this core grain‐growing region of the world.     

Sub-saharan desertification and productivity are linked to hemispheric climate variability

Vegetation productivity and desertification in sub‐Saharan Africa may be influenced by global climate variability attributable to the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO). Combined and individual effects of the NAO and ENSO indices revealed that 75% of the interannual variation in the area of Sahara Desert was accounted for by the combined effects, with most variance attributable to the NAO. Effects were shown in the latitudinal variation on the 200 mm isocline, which was influenced mostly by the NAO. The combined indices explained much of the interannual variability in vegetation productivity in the Sahelian zone and southern Africa, implying that both the NAO and ENSO may be useful for monitoring effects of global climate change in sub‐Saharan Africa.     

Climate‐driven simulation of global crop sowing dates

Aim To simulate the sowing dates of 11 major annual crops at the global scale at high spatial resolution, based on climatic conditions and crop‐specific temperature requirements. Location Global. Methods Sowing dates under rainfed conditions are simulated deterministically based on a set of rules depending on crop‐ and climate‐specific characteristics. We assume that farmers base their timing of sowing on experiences with past precipitation and temperature conditions, with the intra‐annual variability being especially important. The start of the growing period is assumed to be dependent either on the onset of the wet season or on the exceeding of a crop‐specific temperature threshold for emergence. To validate our methodology, a global data set of observed monthly growing periods (MIRCA2000) is used. Results We show simulated sowing dates for 11 major field crops world‐wide and give rules for determining their sowing dates in a specific climatic region. For all simulated crops, except for rapeseed and cassava, in at least 50% of the grid cells and on at least 60% of the cultivated area, the difference between simulated and observed sowing dates is less than 1 month. Deviations of more than 5 months occur in regions characterized by multiple‐cropping systems, in tropical regions which, despite seasonality, have favourable conditions throughout the year, and in countries with large climatic gradients. Main conclusions Sowing dates under rainfed conditions for various annual crops can be satisfactorily estimated from climatic conditions for large parts of the earth. Our methodology is globally applicable, and therefore suitable for simulating sowing dates as input for crop growth models applied at the global scale and taking climate change into account.     

Temporal changes in climatic variables and their impact on crop yields in southwestern China

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985–2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P?<?0.05). Increased sunshine hours were observed during the oilseed rape growth period (P?<?0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P?<?0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P?<?0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P?<?0.01). Tobacco yield increased with mean temperature (P?<?0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.     

Complex structural effects of two hemispheric climatic oscillators on the regional spatio-temporal expansion of a threatened bird

Links between climatic conditions in the eastern equatorial Pacific and extratropical ecological processes remain unexplored. The analysis of a 20‐year time series of spatial and numeric dynamics of a threatened Mediterranean bird suggests, however, that such couplings can be remarkably complex. By providing a new ecological time‐series modelling approach, we were able to dissect the joint effects of the El Niño/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), regional weather, population density and stochastic variability on the expansion dynamics of the White‐headed duck (Oxyura leococephala) in Spain. Our results suggest that the spatial and numeric dynamics of ducks between peak brood emergence and wintering were simultaneously affected by different climatic phenomena during different phases of their global cycles, involving time lags in the numeric dynamics. Strikingly, our results point to both the NAO and the ENSO as potentially major factors simultaneously forcing ecological processes in the Northern Hemisphere, and suggest a new pathway for non‐additive effects of climate in ecology.     

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO₂ concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high‐resolution (12 km) dynamically downscaled climate projections for 1995–2004 and 2085–2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO₂ partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems.     

Contributions of climatic and crop varietal changes to crop production in the North China Plain,since 1980s

The North China Plain (NCP) is the most important agricultural production area in China. Crop production in the NCP is sensitive to changes in both climate and management practices. While previous studies showed a negative impact of climatic change on crop yield since 1980s, the confounding effects of climatic and agronomic factors have not been separately investigated. This paper used 25 years of crop data from three locations (Nanyang, Zhengzhou and Luancheng) across the NCP, together with daily weather data and crop modeling, to analyse the contribution of changes in climatic and agronomic factors to changes in grain yields of wheat and maize. The results showed that the changes in climate were not uniform across the NCP and during different crop growth stages. Warming mainly occurred during the vegetative (preflowering) growth stage of wheat and maize, while there was a cooling trend or no significant change in temperatures during the postflowering stage of wheat (spring) or maize (autumn). If varietal effects were excluded, warming during vegetative stages would lead to a reduction in the length of the growing period for both crops, generally leading to a negative impact on crop production. However, autonomous adoption of new crop varieties in the NCP was able to compensate the negative impact of climatic change. For both wheat and maize, the varietal changes helped stabilize the length of preflowering period against the shortening effect of warming and, together with the slightly reduced temperature in the postflowering period, extend the length of the grain‐filling period. The combined effect led to increased wheat yield at Zhengzhou and Luancheng; increased maize yield at Nanyang and Luancheng; stabilized wheat yield at Nanyang, and a slight reduction in maize yield at Zhengzhou, compared with the yield change caused entirely by climatic change.     

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near‐term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.     

North Atlantic Oscillation and fisheries management during global climate change

Reviews in Fish Biology and Fisheries - The North Atlantic Oscillation (NAO) is the most important large-scale climatic oscillation affecting the North Atlantic region. The variability introduced...     

A combination of hydrodynamical and statistical modelling reveals non-stationary climate effects on fish larvae distributions

Biological processes and physical oceanography are often integrated in numerical modelling of marine fish larvae, but rarely in statistical analyses of spatio-temporal observation data. Here, we examine the relative contribution of inter-annual variability in spawner distribution, advection by ocean currents, hydrography and climate in modifying observed distribution patterns of cod larvae in the Lofoten-Barents Sea. By integrating predictions from a particle-tracking model into a spatially explicit statistical analysis, the effects of advection and the timing and locations of spawning are accounted for. The analysis also includes other environmental factors: temperature, salinity, a convergence index and a climate threshold determined by the North Atlantic Oscillation (NAO). We found that the spatial pattern of larvae changed over the two climate periods, being more upstream in low NAO years. We also demonstrate that spawning distribution and ocean circulation are the main factors shaping this distribution, while temperature effects are different between climate periods, probably due to a different spatial overlap of the fish larvae and their prey, and the consequent effect on the spatial pattern of larval survival. Our new methodological approach combines numerical and statistical modelling to draw robust inferences from observed distributions and will be of general interest for studies of many marine fish species.