Detecting Spatial Patterns of Peatland Greenhouse Gas Sinks and Sources with Geospatial Environmental and Remote Sensing Data.

Peatlands play a key role in the circulation of the main greenhouse gases (GHG) - methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Therefore, detecting the spatial pattern of GHG sinks and sources in peatlands is pivotal for guiding effective climate change mitigation in the land use sector. While geospatial environmental data, which provide detailed spatial information on ecosystems and land use, offer valuable insights into GHG sinks and sources, the potential of directly using remote sensing data from satellites remains largely unexplored. We predicted the spatial distribution of three major GHGs (CH4, CO2, and N2O) sinks and sources across Finland. Utilizing 143 field measurements, we compared the predictive capacity of three different data sets with MaxEnt machine-learning modeling: (1) geospatial environmental data including climate, topography and habitat variables, (2) remote sensing data (Sentinel-1 and Sentinel-2), and (3) a combination of both. The combined dataset yielded the highest accuracy with an average test area under the receiver operating characteristic curve (AUC) of 0.845 and AUC stability of 0.928. A slightly lower accuracy was achieved using only geospatial environmental data (test AUC 0.810, stability AUC 0.924). In contrast, using only remote sensing data resulted in reduced predictive accuracy (test AUC 0.763, stability AUC 0.927). Our results suggest that (1) reliable estimates of GHG sinks and sources cannot be produced with remote sensing data only and (2) integrating multiple data sources is recommended to achieve accurate and realistic predictions of GHG spatial patterns.

A computationally efficient method for approximating reliabilities in large-scale single-step genomic prediction.

BACKGROUND: In this study, computationally efficient methods to approximate the reliabilities of genomic estimated breeding values (GEBV) in a single-step genomic prediction model including a residual polygenic (RPG) effect are described. In order to calculate the reliabilities of the genotyped animals, a single nucleotide polymorphism best linear unbiased prediction (SNPBLUP) or a genomic BLUP (GBLUP), was used, where two alternatives to account for the RPG effect were tested. In the direct approach, the genomic model included the RPG effect, while in the blended method, it did not but an index was used to weight the genomic and pedigree-based BLUP (PBLUP) reliabilities. In order to calculate the single-step GBLUP reliabilities for the breeding values for the non-genotyped animals, a simplified weighted-PBLUP model that included a general mean and additive genetic effects with weights accounting for the non-genomic and genomic information was used. We compared five schemes for the weights. Two datasets, i.e., a small (Data 1) one and a large (Data 2) one were used. RESULTS: For the genotyped animals in Data 1, correlations between approximate reliabilities using the blended method and exact reliabilities ranged from 0.993 to 0.996 across three lactations. The slopes observed by regressing the reliabilities of GEBV from the exact method on those from the blended method were 1.0 for all three lactations. For Data 2, the correlations and slopes ranged, respectively, from 0.980 to 0.986 and from 0.91 to 0.96, and for the non-genotyped animals in Data 1, they ranged, respectively, from 0.987 to 0.994 and from 0.987 to 1, which indicate that the approximations were in line with the exact results. The best approach achieved correlations of 0.992 to 0.994 across lactations. CONCLUSIONS: Our results demonstrate that the approximated reliabilities calculated using our proposed approach are in good agreement with the exact reliabilities. The blended method for the genotyped animals is computationally more feasible than the direct method when RPG effects are included, particularly for large-scale datasets. The approach can serve as an effective strategy to estimate the reliabilities of GEBV in large-scale single-step genomic predictions.

Breeding value reliabilities for multiple-trait single-step genomic best linear unbiased predictor.

Approximate multistep methods to calculate reliabilities for estimated breeding values in large genetic evaluations were developed for single-trait (ST-R2A) and multitrait (MT-R2A) single-step genomic BLUP (ssGBLUP) models. First, a traditional animal model was used to estimate the amount of nongenomic information for the genotyped animals. Second, this information was used with genomic data in a genomic BLUP model (genomic BLUP/SNP-BLUP) to approximate the total amount of information and ssGBLUP reliabilities for the genotyped animals. Finally, reliabilities for the nongenotyped animals were calculated using a traditional animal model where the increased information due to genomic data for the genotyped animals is accounted for by including pseudo-record counts for the genotyped animals. The approaches were tested using a multiple-trait ssGBLUP model on 2 data sets. The first data set (data 1) was small enough such that exact ssGBLUP model reliabilities could be computed by inversion and compared with the approximation method reliabilities. Data 1 had 46,535 first-, 35,290 second-, and 23,780 third-lactation 305-d milk yield records from 47,124 Finnish Red dairy cows. The pedigree comprised 64,808 animals, of which 19,757 were genotyped. We examined the efficiency of the MT-R2A approximation on a large data set (data 2) derived from the joint Nordic (Danish, Finnish, and Swedish) Holstein dairy cattle data. Data 2 had 17.8 million 305-d milk records from 8.3 million cows and first 3 lactations. The pedigree had 11 million animals of which 274,145 were genotyped on 46,342 SNP markers. For data 1, correlations between the exact ssGBLUP model and the ST-R2A for the genotyped (nongenotyped) animals were 0.995 (0.987), 0.965 (0.984), and 0.950 (0.983) for first, second, and third lactation, respectively. Correspondingly, correlations between exact ssGBLUP reliabilities and MT-R2A for the genotyped (nongenotyped) animals were 0.995 (0.993), 0.992 (0.991), and 0.990 (0.990) for first, second, and third lactation, respectively. The regression coefficients (b1) of ssGBLUP reliability on ST-R2A for the genotyped (nongenotyped) animals ranged from 0.87 (0.94) for first lactation to 0.68 (0.93) for third lactation, whereas for MT-R2A they were between 0.91 (0.99) for first lactation to 0.89 (0.99) for third lactation. Correspondingly, the intercepts varied from 0.11 (0.05) to 0.3 (0.06) for ST-R2A and from 0.06 (0.01) to 0.07 (0.02) for MT-R2A. The computing time for the approximation method was approximately 12% of that required by the direct exact approach. In conclusion, the developed approximate approach allows calculating estimated breeding value reliabilities in the ssGBLUP model even for large data sets.

Single-step genomic evaluation of Russian dairy cattle using internal and external information.

Genomic data are widely used in predicting the breeding values of dairy cattle. The accuracy of genomic prediction depends on the size of the reference population and how related the candidate animals are to it. For populations with limited numbers of progeny-tested bulls, the reference populations must include cows and data from external populations. The aim of this study was to implement state-of-the-art single-step genomic evaluations for milk and fat yield in Holstein and Russian Black & White cattle in the Leningrad region (LR, Russia), using only a limited number of genotyped animals. We complemented internal information with external pseudo-phenotypic and genotypic data of bulls from the neighbouring Danish, Finnish and Swedish Holstein (DFS) population. Three data scenarios were used to perform single-step GBLUP predictions in the LR dairy cattle population. The first scenario was based on the original LR reference population, which constituted 1,080 genotyped cows and 427 genotyped bulls. In the second scenario, the genotypes of 414 bulls related to the LR from the DFS population were added to the reference population. In the third scenario, LR data were further augmented with pseudo-phenotypic data from the DFS population. The inclusion of foreign information increased the validation reliability of the milk yield by up to 30%. Suboptimal data recording practices hindered the improvement of fat yield. We confirmed that the single-step model is suitable for populations with a low number of genotyped animals, especially when external information is integrated into the evaluations. Genomic prediction in populations with a low number of progeny-tested bulls can be based on data from genotyped cows and on the inclusion of genotypes and pseudo-phenotypes from the external population. This approach increased the validation reliability of the implemented single-step model in the milk yield, but shortcomings in the LR data recording scheme prevented improvements in fat yield.

A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models.

BACKGROUND AND AIMS: Branch biomass and other attributes are important for estimating the carbon budget of forest stands and characterizing crown structure. As destructive measuring is time-consuming and labour-intensive, terrestrial laser scanning (TLS) as a solution has been used to estimate branch biomass quickly and non-destructively. However, branch information extraction from TLS data alone is challenging due to occlusion and other defects, especially for estimating individual branch attributes in coniferous trees. METHODS: This study presents a method, entitled TSMtls, to estimate individual branch biomass non-destructively and accurately by combining tree structure models and TLS data. The TSMtls method constructs the stem-taper curve from TLS data, then uses tree structure models to determine the number, basal area and biomass of individual branches at whorl level. We estimated the tree structural model parameters from 122 destructively measured Scots pine (Pinus sylvestris) trees and tested the method on six Scots pine trees that were first TLS-scanned and later destructively measured. Additionally, we estimated the branch biomass using other TLS-based approaches for comparison. KEY RESULTS: Tree-level branch biomass estimates derived from TSMtls showed the best agreement with the destructive measurements [coefficient of variation of root mean square error (CV-RMSE) = 9.66 % and concordance correlation coefficient (CCC) = 0.99], outperforming the other TLS-based approaches (CV-RMSE 12.97-57.45 % and CCC 0.43-0.98 ). Whorl-level individual branch attributes estimates produced from TSMtls showed more accurate results than those produced from TLS data directly. CONCLUSIONS: The results showed that the TSMtls method proposed in this study holds promise for extension to more species and larger areas.

Landscape history improves detection of marginal habitats on semi-natural grasslands.

Semi-natural grassland habitats have markedly declined from their historical coverage, thus causing substantial losses for agricultural biodiversity and establishing a consequent need to spot the remaining habitat patches. These patches are generally remnants of once larger habitat areas, formed by uninterrupted and low-intensity management for centuries, but then later being isolated and fragmented into smaller pieces. In the light of this development, past landscape phases have a crucial role for the present existence of semi-natural grasslands. The importance of historical factors has been indicated in many studies but evaluation of their added value, or actual site-specific effects compared to observations of only the present landscape characteristics, is not generally provided. As data related to the past is often difficult to obtain, tedious to process and challenging to interpret, assessment of its advantages and related effects - or consequences of potential exclusion - would be needed. In this study, we used maximum entropy approach to model the distribution of Fumewort (Corydalis solida) which in the study area is a good indicator of valuable semi-natural habitats. We constructed three different models - one based on only the contemporary environment with expected indicators of habitat stability, one solely on the historical landscape phases and long-term dynamics, and one combining variables from the past and the present. Predictions of the three models were validated and compared with each other, followed by an analysis indicating the similarity of model results with known Fumewort occurrences. Our results indicate that present landscapes may provide workable surrogates to delineate larger core habitats, but utilization of historical data markedly improves the detection of small outlying patches. These conclusions emphasize the importance of previous landscape phases particularly in detecting marginal semi-natural grassland habitats, existing in contemporarily suboptimal conditions and being prone to disappear if no further actions are taken.

Similar understorey structure in spite of edaphic and floristic dissimilarity in Amazonian forests / Similaridade na estrutura do subosque a despeito de dissimilaridades edáficas e florísticas em florestas da Amazônia

Forest structure determines light availability for understorey plants. The structure of lowland Amazonian forests is known to vary over long edaphic gradients, but whether more subtle edaphic variation also affects forest structure has not beenresolved. In western Amazonia, the majority of non-flooded forests grow on soils derived either from relatively fertile sediments of the Pebas Formation or from poorer sediments of the Nauta Formation. The objective of this study was to compare structure and light availability in the understorey of forests growing on these two geological formations. We measured canopy openness and tree stem densities in three size classes in northeastern Peru in a total of 275 study points in old-growth terra firme forests representing the two geological formations. We also documented variation in floristic composition (ferns, lycophytes and the palm Iriartea deltoidea) and used Landsat TM satellite image information to model the forest structural and floristic features over a larger area. The floristic compositions of forests on the two formations were clearly different, and this could also be modelled with the satellite imagery. In contrast, the field observations of forest structure gave only a weak indication that forests on the Nauta Formation might be denser than those on the Pebas Formation. The modelling of forest structural features with satellite imagery did not support this result. Our results indicate that the structure of forest understorey varies much less than floristic composition does over the studied edaphic difference.

A estrutura florestal determina a disponibilidade de luz para plantas do subosque. Nas planícies Amazônicas, a estrutura florestal varia com fortes gradientes edáficos. O possível efeito de variações edáficas mais sutis sob a estrutura das florestas não está resolvido. Na Amazônia ocidental, a maioria das florestas não-inundadas crescem em solos derivados de sedimentos relativamente férteis da Formação Pebas ou de sedimentos mais pobres da Formação Nauta. Nosso objetivo é comparar a disponilidade de luz e a estrutura do subosque de florestas crescendo sobre duas formações geológicas. Nós medimos a abertura do dossel e a densidade de troncos de árvores em três classes de diâmetro no nordeste Peruano, totalizando 275 pontos de estudo em florestas de terra-firme representando as duas formações geológicas. Além disso, documentamos as variações na composição florística (samambaias, licófitas e a palmeira Iriartea deltoidea) e utilizamos informações de imagens de satélite Landsat TM para modelar as características estruturais e florísticas das florestas em uma área mais ampla. A composição florística sobre as duas formações foram claramente distintas e isso também pôde ser modelado com as imagens de satélite. Já as observações de campo sobre a estrutura da floresta deram uma fraca indicação de que as florestas sobre a Formação Nauta poderiam ser mais densas do que as florestas sobre a Formação Pebas. A modelagem das caraterísticas da estrutura florestal com imagens de satélite não deram o mesmo resultado. Nossos resultados indicam que a estrutura do subosque varia muito menos do que composição florística no gradiente edáfico estudado.

Across-country test-day model evaluations for Holstein, Nordic Red Cattle, and Jersey.

Three random regression models were developed for routine genetic evaluation of Danish, Finnish, and Swedish dairy cattle. Data included over 169 million test-day records with milk, protein, and fat yield observations from over 8.7 million dairy cows of all breeds. Variance component analyses showed significant differences in estimates between Holstein, Nordic Red Cattle, and Jersey, but only small to moderate differences within a breed across countries. The obtained variance component estimates were used to build, for each breed, their own set of covariance functions. The covariance functions describe the animal effects on milk, protein, and fat yields of the first 3 lactations as 9 different traits, assuming the same heritabilities and a genetic correlation of unity across countries. Only 15, 27, and 7 eigenfunctions with the largest eigenvalues were used to describe additive genetic animal effects and nonhereditary animal effects across lactations and within later lactations, respectively. These reduced-rank covariance functions explained 99.0 to 99.9% of the original variances but reduced the number of animal equations to be solved by 44%. Moderate rank reduction for nonhereditary animal effects and use of one-third-smaller measurement error correlations than obtained from variance component estimation made the models more robust against extreme observations. Estimation of the genetic levels of the countries' subpopulations within a breed was found sensitive to the way the breed effects were modeled, especially for the genetically heterogeneous Nordic Red Cattle. Means to ensure that only additive genetic effects entered the estimated breeding values were to describe the crossbreeding effects by fixed and random cofactors and the calving age effect by an age × breed proportion interaction, and to model phantom parent groups as random effects. To ensure that genetic variances were the same across the 3 countries in breeding value estimation, as suggested by the variance component estimates, the applied multiplicative heterogeneous variance adjustment method had to be tailored using country-specific reference measurement error variances. Results showed the feasibility of across-country genetic evaluation of cows and sires based on original test-day phenotypes. Nevertheless, applying a thorough model validation procedure is essential throughout the model building process to obtain reliable breeding values.

Assessing restoration potential of semi-natural grasslands by landscape change trajectories.

Species-rich semi-natural grasslands have rapidly declined and become fragmented in Northern Europe due to ceased traditional agricultural practices and animal husbandry. Restoration actions have been introduced in many places to improve the habitat conditions and increase the area to prevent any further losses of their ecological values. However, given the limited resources and long time span needed for successful restoration, it is essential to target activities on sites having a suitable initial state and where the effects of restoration are most beneficial for the habitat network. In this paper we present a conceptual framework for evaluating the restoration potential of partially overgrown and selectively managed semi-natural grasslands in a moderately transformed agricultural environment in south-western Finland. On the basis of the spatio-temporal landscape trajectory analysis, we construct potential restoration scenarios based on expected semi-natural grassland characteristics that are derived from land productivity, detected grassland continuum, and date of overgrowth. These scenarios are evaluated using landscape metrics, their feasibility is discussed and the effects of potential restoration are compared to the present extent of open semi-natural grasslands. Our results show that landscape trajectory analysis and scenario construction can be valuable tools for the restoration planning of semi-natural grasslands with limited resources. The approach should therefore be considered as an essential tool to find the most optimal restoration sites and to pre-evaluate the effects.

In vitro maturation supplements affect developmental competence of bovine cumulus-oocyte complexes and embryo quality after vitrification.

Oocyte quality affects subsequent embryo development and quality. We examined the impact of bovine oocyte in vitro maturation (IVM) conditions on subsequent embryo yield, quality and cryosurvival. Cumulus-oocyte complexes (COCs) were sampled for cytological and gene expression analysis after IVM in TCM199 supplemented with 10% fetal bovine serum (FBS), 4 mg/ml of fatty-acid-free bovine serum albumin (FAFBSA), 4 mg/ml of polyvinylpyrrolidone (PVP), FAFBSA with epidermal growth factor (EGF, 100 ng/ml) and insulin-like growth factor 1 (IGF-I, 100 ng/ml) (FAFBSAGF), PVP with EGF and IGF-I (PVPGF) or PVP with single strength BME and MEM amino acids (PVPAA). The remaining COCs were fertilized. On day 7 (IVF=day 0) quality 1 blastocysts were vitrified or analyzed for glucose transporter 1 (Glut-1) expression levels. The remaining blastocysts (days 7-9) were evaluated for morphology and total cell counts. After warming, survival and hatching rates were evaluated followed by total cell counts and Glut-1 expression levels. Only PVPGF IVM resulted in embryo production rates comparable to those recorded with FBS IVM. Growth factors with FAFBSA and amino acids with PVP reduced embryo production rates whereas the effect of the growth factors with PVP was negligible. Insulin-like growth factor 2 binding protein 3 (IGF2BP3) and beta cell translocation gene 4 (BTG4) were revealed as potential candidates for oocyte developmental competence, and secreted protein, acidic and rich in cysteine (SPARC) for cumulus cell expansion. There were no differences among treatments in hatching rates of vitrified embryos after warming. However, total cell numbers and Glut-1 expression levels at 72 h were affected.

Slip, trip and fall injuries in potato, sugar beet and open field vegetable production in Finland.

STF injuries are common in agriculture. The purposes of this study were to assess the magnitude of STF injuries, to identify contributing factors and to propose preventive actions to reduce injuries in potato, sugar beet and open field vegetable production in Finland. The material consisted of 1648 injury claim records and 22 interviews. The analysis showed 45% (n = 740) of the non-fatal injuries were STFs or jumps. Phrase analysis of injury descriptions provided further insight into the characteristics of STF injuries. The current findings suggest interventions should focus on making access paths (e.g. stairs, ladders, platforms) safer, minimising the need for mounting and dismounting equipment, decreasing manual material handling, improving contamination control and housekeeping in working areas and improving the safety of traffic areas and farmyards.