Effects of Forestry Transformation on the Landscape Level of Biodiversity in Poland’s Forests

At all times, historical, political, economic, and social factors have affected the management of forests, with direct and indirect effects on the landscape. This study aimed to trace the impact of Poland’s forestry evolution over the last 75 years (1945–2020) on forest biodiversity at the landscape level. Five indicators were selected (forest area, forest fragmentation, protected forests, protective forests, harvesting intensity) to identify directions and dynamics of changes of the forest landscape and their determinants and repercussions. In addition, there were determined forest landscapes threats and recommendations for further action and intervention were formulated. The study period embraced two eras of widely divergent political-economic conditions in Poland (socialism and democracy). In the socialism era (1945–1989), there promptly increased total forest cover, wood resources (total growing stock) and the total area of protective forests (essential for safeguarding biodiversity, including the landscape level). In the era of democracy (1990–2020), average growing stock density increased intensely, and at the same time, a greater emphasis was put on reducing forest fragmentation and clear-cut logging. The results obtained showed equal average increase in the area of protected forests in both eras under the study (most intense at their crossing point). In view of the protection of biodiversity at the forest landscape level, the changes throughout the study period were considered positive, although not without problems and challenging consequences for foresters. The determined pressures to the forest landscapes, requiring legal, political, or financial solutions, include a risk of alteration of the ownership structure of Poland’s forests or possibility of operational changes in the State Forests National Forest Holding; outdated forest policies; organizational difficulties in the forest landscape protection; insufficient conservation funding; uneven distribution and further fragmentation of forests; and—last but not least—climate change impacts, including extreme weather events and droughts.

Does anthropogenic fragmentation selectively filter avian phylogenetic diversity in a critically endangered forest system?

Summary Documenting phylogenetic diversity for conservation practice allows elucidation of ecosystem functioning and processes by highlighting the commonality and divergence of species’ functional traits within their evolutionary context. Conserving distinct evolutionary histories has intrinsic value, and the conservation of phylogenetically diverse communities is more likely to preserve distinct or relic evolutionary lineages. We explored the potential for anthropogenic forest fragmentation to act as a selective filter of avian phylogenetic diversity within the community of forest-dependent birds of the critically endangered Indian Ocean Coastal Belt Forest (IOCBF), South Africa. We conducted avian point count surveys during the austral breeding season, and calculated fragmentation metrics of forest structural complexity, patch size and isolation. We constructed a maximum likelihood phylogeny using the combined analysis of two mitochondrial genes and three nuclear markers and measured the influence of the fragmentation metrics on six measures of phylogenetic diversity. Our results indicated that the avian community was variously affected by anthropogenic forest fragmentation, with the different metrics of phylogenetic diversity responding with no definitive overall pattern. However, forest structural complexity emerged as an important metric explaining phylogenetic structuring. While the avian community’s phylogenetic diversity displayed resilience to anthropogenic fragmentation, previous research showed a reduction in functional diversity along the fragmentation gradient. Therefore, we recommend studies that especially aim to guide conservation management, incorporate both phylogenetic and functional diversity measures to sufficiently interrogate communities’ resilience to the threats under investigation.

Genetic Structure and Geographical Differentiation of Larix sibirica Ledeb. in the Urals

The Ural Mountains and the West Eurasian Taiga forests are one of the most important centers of genetic diversity for Larix sibirica Ledeb. Forest fragmentation negatively impacts forest ecosystems, especially due to the impact of their intensive use on the effects of climate change. For the preservation and rational use of forest genetic resources, it is necessary to carefully investigate the genetic diversity of the main forest-forming plant species. The Larix genus species are among the most widespread woody plants in the world. The Siberian larch (Larix sibirica, Pinaceae) is found in the forest, forest-tundra, tundra (Southern part), and forest-steppe zones of the North, Northeast, and partly East of the European part of Russia and in Western and Eastern Siberia; in the Urals, the Siberian larch is distributed fragmentarily. In this study, eight pairs of simple sequence repeat (SSR) primers were used to analyse the genetic diversity and population structure of 15 Siberian larch populations in the Urals. Natural populations in the Urals exhibit indicators of genetic diversity comparable to those of Siberia populations (expected heterozygosity, He = 0.623; expected number of alleles, Ne = 4017; observed heterozygosity, Ho = 0.461). Genetic structure analysis revealed that the examined populations are relatively highly differentiated (Fst = 0.089). Using various algorithms for determining the spatial genetic structure, the examined populations formed three groups according to geographical location. The data obtained are required for the development of species conservation and restoration programs, which are especially important in the Middle Urals, which is the region with strong forest fragmentation.

There Is No ‘Rule of Thumb’: Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates

The application of high-density polymorphic single-nucleotide polymorphisms (SNP) markers derived from high-throughput sequencing methods has heralded plenty of biological questions about the linkages of processes operating at micro- and macroevolutionary scales. However, the effects of SNP filtering practices on population genetic inference have received much less attention. By performing sensitivity analyses, we empirically investigated how decisions about the percentage of missing data (MD) and the minor allele frequency (MAF) set in bioinformatic processing of genomic data affect direct (i.e., parentage analysis) and indirect (i.e., fine-scale spatial genetic structure – SGS) gene flow estimates. We focus specifically on these manifestations in small plant populations, and particularly, in the rare tropical plant species Dinizia jueirana-facao, where assumptions implicit to analytical procedures for accurate estimates of gene flow may not hold. Avoiding biases in dispersal estimates are essential given this species is facing extinction risks due to habitat loss, and so we also investigate the effects of forest fragmentation on the accuracy of dispersal estimates under different filtering criteria by testing for recent decrease in the scale of gene flow. Our sensitivity analyses demonstrate that gene flow estimates are robust to different setting of MAF (0.05–0.35) and MD (0–20%). Comparing the direct and indirect estimates of dispersal, we find that contemporary estimates of gene dispersal distance (σrt = 41.8 m) was ∼ fourfold smaller than the historical estimates, supporting the hypothesis of a temporal shift in the scale of gene flow in D. jueirana-facao, which is consistent with predictions based on recent, dramatic forest fragmentation process. While we identified settings for filtering genomic data to avoid biases in gene flow estimates, we stress that there is no ‘rule of thumb’ for bioinformatic filtering and that relying on default program settings is not advisable. Instead, we suggest that the approach implemented here be applied independently in each separate empirical study to confirm appropriate settings to obtain unbiased population genetics estimates.