Fractional Vegetation Cover Derived from UAV and Sentinel-2 Imagery as a Proxy for In Situ FAPAR in a Dense Mixed-Coniferous Forest?

The fraction of absorbed photosynthetic active radiation (FAPAR) is an essential climate variable for assessing the productivity of ecosystems. Satellite remote sensing provides spatially distributed FAPAR products, but their accurate and efficient validation is challenging in forest environments. As the FAPAR is linked to the canopy structure, it may be approximated by the fractional vegetation cover (FCOVER) under the assumption that incoming radiation is either absorbed or passed through gaps in the canopy. With FCOVER being easier to retrieve, FAPAR validation activities could benefit from a priori information on FCOVER. Spatially distributed FCOVER is available from satellite remote sensing or can be retrieved from imagery of Unmanned Aerial Vehicles (UAVs) at a centimetric resolution. We investigated remote sensing-derived FCOVER as a proxy for in situ FAPAR in a dense mixed-coniferous forest, considering both absolute values and spatiotemporal variability. Therefore, direct FAPAR measurements, acquired with a Wireless Sensor Network, were related to FCOVER derived from UAV and Sentinel-2 (S2) imagery at different seasons. The results indicated that spatially aggregated UAV-derived FCOVER was close (RMSE = 0.02) to in situ FAPAR during the peak vegetation period when the canopy was almost closed. The S2 FCOVER product underestimated both the in situ FAPAR and UAV-derived FCOVER (RMSE > 0.3), which we attributed to the generic nature of the retrieval algorithm and the coarser resolution of the product. We concluded that UAV-derived FCOVER may be used as a proxy for direct FAPAR measurements in dense canopies. As another key finding, the spatial variability of the FCOVER consistently surpassed that of the in situ FAPAR, which was also well-reflected in the S2 FAPAR and FCOVER products. We recommend integrating this experimental finding as consistency criteria in the context of ECV quality assessments. To facilitate the FAPAR sampling activities, we further suggest assessing the spatial variability of UAV-derived FCOVER to benchmark sampling sizes for in situ FAPAR measurements. Finally, our study contributes to refining the FAPAR sampling protocols needed for the validation and improvement of FAPAR estimates in forest environments.

Landscape Changes in Protected Areas in Poland

Land-Use Cover Changes (LUCCs) are one of the main problems for the preservation of landscapes and natural biodiversity. Protected Areas (PAs) do not escape this threat. Poland is among the European leaders in terms of the variety of landscapes and the share of an area designated as a protected area. However, as many as 78% of the habitats have poor or bad conservation status based on EEA reports. This article analyzes the LUCCs between 2000 and 2018 in various types of the Polish legal forms of nature protection areas and the European Natura 2000 network within the country. The research material was: the data of Corine Land Cover (CLC), the Central Register of Nature Protection Forms, and high-resolution layers, such as HRL and orthophotos. The results were compiled according to the CLC class and forms of protection. The matrix of transformations showed that the most frequently transformed CLC class was 312 (coniferous forest). It was transformed into class 324 (transitional woodland shrubs). The changes in PAs were usually smaller than in the surrounding buffer zones, which may indicate their effectiveness. The exception was the areas of the European Natura 2000 network. The scale of land-cover flows (LCFs) changed within particular forms of protected areas, though afforestation and deforestation predominating in all area types. National reserves and parks were the most stable in terms of land cover structures. However, human settlements increased around the protected areas, potentially increasing threats to their ecological integrity.

Responses of Larix principis-rupprechtii Radial Growth to Climatic Factors at Different Elevations on Guancen Mountain, North-Central China

Larix principis-rupprechtii is an important afforestation tree species in the North China alpine coniferous forest belt. Studying the correlations and response relationships between Larix principis-rupprechtii radial growth and climatic factors at different elevations is helpful for understanding the growth trends of L. principis-rupprechtiind its long-term sensitivity and adaptability to climate change. Pearson correlation, redundancy (RDA), and sliding analysis were performed to study the correlations and dynamic relationships between radial growth and climatic factors. The main conclusions are as follows: (1) The three-elevation standard chronologies all exhibited high characteristic values, contained rich climate information and were suitable for tree-ring climatological analyses. (2) Both temperature and precipitation restricted low-elevation L. principis-rupprechtii radial growth, while monthly maximum temperatures mainly affected mid-high-elevation L. principis-rupprechtii radial growth. (3) Mid-elevation L. principis-rupprechtii radial growth responded to climate factors with a “lag effect” and was not restricted by spring and early summer drought. (4) Long-term sliding analysis showed that spring temperatures and winter precipitation were the main climatic factors restricting L. principis-rupprechtii growth under warming and drying climate trends at different elevations. The tree-ring width index and Palmer drought severity index (PDSI) were positively correlated, indicating that L. principis-rupprechtii growth is somewhat restricted by drought. These results provide a reference and guidance for L. principis-rupprechtii management and sustainable development in different regions under warming and drying background climate trends.

Effects of stand age and soil organic matter quality on soil bacterial and fungal community composition in Larix gmelinii plantations, Northeast China

It is of great interest to elucidate the biogeographic patterns of soil microorganisms and their driving forces, which is fundamental to predicting alterations in microbial-mediated functions arising from environment changes. Although the vertical movement of dissolved organic matter (DOM) drives the cycle of nutrients such as soil carbon but, in the restored ecosystem, the relationship between DOM and soil microbial nutrient utilization remains to be determined. Here, we investigated the changes of soil microbial community at 0-40 cm depth profile in three stages (10-, 30-, 50-years) of succession in Larix olgensis plantations and the fluorescence spectrum composition of DOM. With the increase of soil depth, the signal source of microorganisms increases. In a coniferous forest soil environment, the possible main source of DOM in deep soil is the production of microbial metabolism. Difficulty in the decomposition of organic matter determines the distribution and composition of microorganisms. Increasing forest age makes bacteria and fungi more specific and bacterial-fungal associations greater. Overall, our work contributes to the understanding of factors underlying microbial community distribution in plantation forests and the importance of DOM quality in building microbial communities.

Recent Megafires Provide a Tipping Point for Desertification of Conifer Ecosystems

Recent megafires and gigafires are contributing to the desertification of conifer forest ecosystems due to their size and severity. Megafires have been increasing in their frequency in the past two decades of the 21st century. They are classed as such because of being 40,469 to 404,694 ha in size, having high complexity, resisting suppression, and producing desertification due to erosion and vegetation type conversion. Increasingly, gigafires (>404,694 ha) are impacting coniferous forest ecosystems. These were once thought of as only pre-20th century phenomena when fire suppression was in its infancy. Climate change is an insidious inciting factor in large wildfire occurrences. Fire seasons are longer, drier, hotter, and windier due to changes in basic meteorology. Conifer forests have accumulated high fuel loads in the 20th and 21st centuries. Ignition sources in conifer forests have increased as well due to human activities, economic development, and population demographics. Natural ignitions from lightning are increasing as a result of greater severe thunderstorm activity. Drought has predisposed these forests to easy fire ignition and spread. Wildfires are more likely to produce vegetation shifts from conifers to scrublands or grasslands, especially when wildfires occur with higher frequency and severity. Severe erosion after megafires has the collateral damage of reducing conifer resilience and sustainability.

‘Back to the Future’—Oak wood-pasture for wildfire prevention in the Mediterranean

In the summer of 2021, enormous wildfires in the Mediterranean eliminated huge areas of mainly coniferous forest, destroyed adjacent settlements and claimed the lives of many people. The fires indicate effects of climate change and expose consequences of rural demographic changes, deficits in regional and touristic development planning and shortcomings in forest policy. This forum article highlights the dimensions of the problem, calls for a paradigm shift and shows solutions. Land abandonment, woody plant encroachment and non-reflective afforestation are leading to increasing amounts of combustible biomass. To prevent disastrous fires in future, fundamental changes in tree species composition, forest structure and management are essential. Plantations of reseeding pines are to be substituted by spacious or periodically open woodlands of long-lived trees with resprouting capacity such as Mediterranean oaks. Biomass-reducing practices including wood-pasture have to be revived in rural and peri-urban areas. Exemplary fire-resistant multifunctional oak woodlands occur throughout the Mediterranean. Urgent and medium-term measures in the burnt areas include promoting natural ecosystem regeneration, developing regionalized seed banks and nurseries to support native genetic resources, fostering vegetation mosaics of groves and multiple-use open and coppice woodland maintained by traditional practices, and in general forest management aiming at fuel biomass reduction and a policy counteracting land abandonment.

Comparison of GEOBIA classification algorithms based on Worldview-3 imagery in the extraction of coastal coniferous forest

Šume primorskih četinjača, sa svojom ekološkom, ekonomskom, estetskom i društvenom funkcijom, predstavljaju važan dio europskih šumskih zajednica. Osnovni cilj ovoga rada je usporediti najkorištenije GEOBIA (engl. Geographic Object-Based Image Analysis) klasifikacijske algoritme (engl. Random Trees – RT, Maximum Likelihood – ML, Support Vector Machine – SVM) s ciljem izdvajanja šuma primorskih četinjača na visoko-rezolucijskom WorldView-3 snimku unutar topografskog slijevnog područja naselja Split. Metodološki okvir istraživanja uključuje (1) izvođenje izoštrenog multispektralnog snimka (WV-3_MS-a); (2) testiranje segmentacijskih korisničko-definiranih parametara; (3) dodavanje testnih uzoraka; (4) klasifikaciju segmentiranog modela; (5) procjenu točnosti klasifikacijskih algoritama, te (6) procjenu točnosti završnog modela. RT se prema korištenim pokazateljima (correctness – COR, completeness – COM i overall quality – OQ) pokazao kao najbolji algoritam. Iterativno postavljanje segmentacijskih parametara omogućilo je detekciju najprikladnijih vrijednosti za generiranje segmentacijskog modela. Utvrđeno je da sjene mogu uzrokovati značajne probleme ako se klasificiranje vrši na visoko-rezolucijskim snimkama. Modificiranim Cohen’s kappa coefficient (K) pokazateljem izračunata je točnost konačnog modela od 87,38%. WV-3_MS se može smatrati kvalitetnim podatkom za detekciju šuma primorskih četinjača primjenom GEOBIA metode.

Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management

Individual Tree Detection (ITD) algorithms that use Airborne Laser Scanning (ALS) data can provide accurate tree locations and measurements of tree-level attributes that are required for stand-to-landscape scale forest inventory and supply chain management. While numerous ITD algorithms exist, few have been assessed for accuracy in stands with complex forest structure and composition, limiting their utility for operational application. In this study, we conduct a preliminary assessment of the ability of the ForestView® algorithm created by Northwest Management Incorporated to detect individual trees, classify tree species, live/dead status, canopy position, and estimate height and diameter at breast height (DBH) in a mixed coniferous forest with an average tree density of 543 (s.d. ±387) trees/hectare. ITD accuracy was high in stands with lower canopy cover (recall: 0.67, precision: 0.8) and lower in stands with higher canopy cover (recall: 0.36, precision: 0.67), mainly owing to omission of suppressed trees that were not detected under the dominant tree canopy. Tree species that were well-represented within the study area had high classification accuracies (producer’s/user’s accuracies > ~60%). The similarity between the ALS estimated and observed tree attributes was high, with no statistical difference in the ALS estimated height and DBH distributions and the field observed height and DBH distributions. RMSEs for tree-level height and DBH were 0.69 m and 7.2 cm, respectively. Overall, this algorithm appears comparable to other ITD and measurement algorithms, but quantitative analyses using benchmark datasets in other forest types and cross-comparisons with other ITD algorithms are needed.