The ability to accurately assess the impact of organic soil drainage on greenhouse gas emissions (GHG) is still limited. Methane (CH4) emissions are characterized by significant variations, and GHG emissions from nutrient-rich organic soil in the region have not been extensively studied. The aim of this study was to assess CH4 and nitrous oxide (N2O) emissions from nutrient-rich organic soil in hemiboreal forests to provide insights into their role in regional GHG balance. Over the course of one year, CH4 and N2O emissions, as well as their affecting factors, were monitored in 31 forest compartments in Latvia in both drained and undrained nutrient-rich organic soils. The sites were selected to include forests of different ages, dominated by silver birch (Betula pendula Roth), Norway spruce (Picea abies (L.) Karsten), and black alder (Alnus glutinosai (L.) Gärtner), as well as clearcuts. Soil GHG emissions were estimated by collecting gas samples using the closed manual chamber method and analyzing these samples with a gas chromatograph. In addition, soil temperature and groundwater level (GW) measurements were conducted during gas sample collection. The mean annual CH4 emissions from drained and undrained soil were −4.6 ± 1.3 and 134.1 ± 134.7 kg CH4 ha−1 year−1, respectively. N2O emissions from undrained soil (4.1 ± 1.4 kg N2O ha−1 year−1) were significantly higher compared to those from drained soil (1.7 ± 0.6 kg N2O ha−1 year−1). In most of the study sites, undrained soil acted as a CH4 sink, with the soil estimated as a mean source of CH4, which was determined by one site where an emission hotspot was evident. The undrained soil acted as a CH4 sink due to the characteristics of GW level fluctuations, during which the vegetation season GW level was below 20 cm.

The reduction of greenhouse gas (GHG) emissions and climate change mitigation are global issues. Peatlands in Europe are widely distributed in the Nordic–Baltic region, and Baltic countries are some of the largest peat suppliers for horticulture in Europe. However, there is no sustainable substitute for peat in the horticulture industry. Therefore, it is necessary to identify suitable re-cultivation types for former peat extraction fields, because knowledge about the effect of re-cultivation on annual carbon and GHG budgets is limited. Ecosystem GHG (CO2, CH4, N2O) exchange measurements, environmental parameter assessment and sampling in the study were conducted in a hemiboreal vegetation zone for 24 consecutive months in former peat extraction fields with different re-cultivation management strategies (land use types). The aim of the study was to assess the influence of diverse re-cultivation management strategies on the GHG emissions of former peat extraction fields. The most suitable re-cultivation management is afforestation with Scots pine (Pinus sylvestris) in order to obtain the lowest annual CO2eq values and ensure additional carbon sequestration in living tree biomass. The developed linear mixed-effect models showed a good model fit (R2CO2 = 0.80, R2CH4 = 0.74) for the analyzed land use types, and thus can be used for CO2 and CH4 emissions estimation.

According to general knowledge rewetting of drained organic soils is a measure that can reduce net greenhouse gas emissions from ecosystem, however there is lack of evidence that approves such an assumption in hemiboreal forests. The aim of the study was to quantify N2O and CH4 flux from nutrient-rich organic soils in naturally wet (NWS) and drained (DS) hemiboreal forest sites in Latvia.In central Latvia, 26 NWS (Dryopterioso-caricosa and Filipendulosa) and DS (Oxalidosa turf. mel.) were selected to evaluate annual N2O and CH4 soil flux by manual chamber method. Gas sampling was performed once a month in five replicates in every sampling plot for period of one year covering all seasons from October of 2019 till November of 2020. During gas sampling soil temperature and groundwater level were measured. In addition, soil and groundwater was sampled and tested. Study results show that soil CH4 flux has strong correlation with groundwater level and weak correlation with soil temperature in booth DS and NWS. Moderate correlation between soil temperature and N2O flux were found in DS, however in rest of the study sites significant impact of soil temperature and groundwater level on N2O flux was not found. Estimated annual average soil CH4 flux is average -3.5±1.0 kg C-CH4 ha -1 yr -1 in DS and average 100.6±101.0 kg C-CH4 ha -1 yr -1 in NWS. While estimated annual average soil N2O flux is average 1.1±0.4 kg N-N2O ha -1 yr -1 in DS and 2.6±0.9 kg N-N2O ha -1 yr -1 in NWS.

According to earlier studies, Logbear F4000 forwarder is suitable for extreme and bad forwarding conditions in pre-commercial and commercial thinning, but it can be also used in salvage loggings and, when necessary, in final felling; however, larger machines are recommended for the conventional final felling. The aim of the study is to test performance of the tracked forwarder Logbear F4000 in thinning in forest stands with moderate or bad forwarding conditions (on wet and drained mineral and organic soils), including productivity, fuel consumption, load capacity and forwarding costs. Trials were conducted in 2016 and 2017 by forwarding logs in thinning, where harvesting was done by Vimek 404 T5 (bad conditions) and John Deere 1070 harvester and chainsaws (moderate conditions). No significant difference was found in forwarding productivity, when logging was done with a chainsaw or a harvester. In moderate forwarding conditions the average load was 3.4 m 3 and the average driving speed was 77.5 m•min-1 , but in bad forwarding conditions the average load was 3.6 m 3 and the average driving speed was 45.0 m•min-1. According to the study, the productivity is significantly influenced by both, increase of the forwarding distance and the load size. The average fuel consumption of Logbear F4000 is 4.93 ± 0.26 (standard deviation) l per hour (1.14 ± 0.14 (standard deviation) l m-3). Prime cost of roundwood forwarding in bad forwarding conditions is 6.8 EUR•m-3 , in moderate conditions 7.9 EUR•m-3 , accordingly, and is significantly influenced by increase of the forwarding distance and reduction of payload.

Water tends to flow and accumulate in response to topographical characteristics of local area and gravitational potential energy. Remote sensing data like LiDAR (Light detecting and ranging) or satellite data can be used to identify local depressions where wet areas may occur. The aim of this study was to evaluate methods that can be used to identify wet areas, to determine correlation between topography of the area and forest regeneration and to prepare proposals for forest management that could be usable in Latvia. Study area includes fertile forest land on wet mineral soils and drained mineral soils with planted spruce (Picea abies) and available LiDAR data. Map examples have been made to demonstrate methodology which allows to identify depressions with potentially hindered run-off. Fill sinks algorithm has shown best results in identifying wet areas and correlation with wet areas that were detected in field studies is 62%. TWI index is not suitable for this study because of relatively flat area. Result of this study reveals that wet areas have significant effect on tree species. In depressions, despite the fact that there has been planted spruce, main species are birch (Betula pendula) and black alder (Alnus glutinosa). Wet areas have significant effect on tree height.