Old growth forests and large old trees as critical organisms connecting ecosystems and human health. A review

Old forests containing ancient trees are essential ecosystems for life on earth. Mechanisms that happen both deep in the root systems and in the highest canopies ensure the viability of our planet. Old forests fix large quantities of atmospheric CO2, produce oxygen, create micro-climates and irreplaceable habitats, in sharp contrast to young forests and monoculture forests. The current intense logging activities induce rapid, adverse effects on our ecosystems and climate. Here we review large old trees with a focus on ecosystem preservation, climate issues, and therapeutic potential. We found that old forests continue to sequester carbon and fix nitrogen. Old trees control below-ground conditions that are essential for tree regeneration. Old forests create micro-climates that slow global warming and are irreplaceable habitats for many endangered species. Old trees produce phytochemicals with many biomedical properties. Old trees also host particular fungi with untapped medicinal potential, including the Agarikon, Fomitopsis officinalis, which is currently being tested against the coronavirus disease 2019 (COVID-19). Large old trees are an important part of our combined cultural heritage, providing people with aesthetic, symbolic, religious, and historical cues. Bringing their numerous environmental, oceanic, ecological, therapeutic, and socio-cultural benefits to the fore, and learning to appreciate old trees in a holistic manner could contribute to halting the worldwide decline of old-growth forests.

Ecological data in Darwin Core: the case of earthworm surveys

This sampling-event dataset provides primary data about species diversity, age structure, abundance (in terms of biomass and density) and seasonal activity of earthworms (Lumbricidae). The study was carried out in old-growth broad-leaved and young forests of two protected areas ("Kaluzhskiye Zaseki" Nature Reserve and Ugra National Park) of Kaluga Oblast (Russia). The published dataset provides new data about earthworm communities in European Russia. We propose a new schema according to Darwin Core for the standardisation of the soil invertebrates survey data.

Cutlink Cleaning Head with a Spreading Feature for Biological Sprout Control

The ability of deciduous trees to sprout efficiently after cutting is problematic in young forests where the target is to cultivate coniferous trees for industry. Since the use of chemicals has been restricted, new alternatives are needed. One potential and environmentally friendly option is biological sprout control that is based on the use of a white-rot fungus, Chondrostereum purpureum (Pers. Ex Fr.) Pouzar. This method has been efficient in earlier investigations when performed manually, but efficient, fully mechanized devices which are able to cut and treat stumps with a fungus are still unavailable. Therefore, the efficacy of biological sprout control conducted with a Cutlink cleaning head equipped with a spreading feature was studied in two young Norway spruce (Picea abies (L.) H. Karst.) forests in central Finland.Sample plots for the control (cutting deciduous saplings only) and fungal treatment (cutting and spreading fungal inoculum on fresh stump surfaces) were established, and the ability of the Cutlink cleaning head in preventing sprouting of silver and downy birch (Betula pendula Roth and B. pubescens Ehrh., respectively) in the sample plots was investigated for two years.In the near vicinity of cultivated Norway spruce, the proportion of cut deciduous saplings varied from 50–60% after the Cutlink operation. The average mortality of silver and downy birch stumps in the fungal treatment plots was ca. 40%, while stump mortality in the control, i.e., cutting only, was only ca. 13%, after two years. Stump mortality increased up to 73% if the stumps did not include old branches, i.e., the stump was cut to a low enough height.These results confirmed that the Cutlink cleaning head is a potential tool in young stand management operation but further development will be needed in working methods in order to achieve lower stump heights (no branches on the stump) and also to increase the proportion of cut saplings.

Failure Detection in Eucalyptus Plantation Based on UAV Images

The information of the locations and numbers of failures is crucial to precise management of new afforestation, especially during seedling replanting in young forests. In practice, foresters are more accustomed to determining the locations of failures according to their rows than based on their geographical coordinates. The relative locations of failures are more difficult to collect than the absolute geographic coordinates which are available from an orthoimage. This paper develops a novel methodology for obtaining the relative locations of failures in rows and counting the number of failures in each row. The methodology contains two parts: (1) the interpretation of the direction angle of seedlings rows on an unmanned aerial vehicle (UAV) orthoimage based on the probability statistical theory (called the grid-variance (GV) method); (2) the recognition of the centerline of each seedling rows using K-means and the approach to counting failures in each row based on the distribution of canopy pixels near the centerline of each seedling row (called the centerline (CL) method). The experimental results showed that the GV method can accurately interpret the direction angle of rows (45°) in an orthoimage and the CL method can quickly and accurately obtain the numbers and relative locations of failures in rows. The failure detection rates in the two experimental areas were 91.8% and 95%, respectively. These research findings can provide technical support for the precise cultivation of planted seedling forests.

Interacting Fire, Logging and Climate Change has Sprung a Landscape Trap in Victoria’s Montane Ash Forests

Ecosystems are influenced by multiple drivers which shape ecosystem state and biodiversity. In some ecosystems, interactions and feedbacks between drivers can produce traps that confine an ecosystem to a particular state or condition and influence processes like succession. A range of traps have been recognized, with one of these – “a landscape trap” first proposed a decade ago for the tall, wet Mountain Ash and Alpine Ash forests of Victoria, south-eastern Australia. Under such a trap, young flammable forest is at high risk of reburning at high-severity, thereby precluding stand maturation, and potentially leading to ecosystem collapse. These young forests are more common because recurrent wildfire and widespread clearcutting have transformed historical patterns of forest cover from widespread old-growth with small patches of regrowth embedded within it, to the reverse. Indeed, approximately 99% of the montane ash ecosystem is now relatively young forest. Based on new empirical insights, we argue that at least three key inter-related pre-conditions underpin the development of a landscape trap in montane ash forests. A landscape trap has been sprung in these forests because the pre-conditions for its development have been met: We show how inter-relationships between these pre-conditions, leading to frequent high-severity fire, interacts with life history attributes (e.g. time to viable seed production) to make montane ash forests (e.g. which have been highly disturbed through logging and frequent fire) vulnerable to ecosystem collapse. We conclude with the ecological and resource management implications of this landscape trap and discuss how the problems created might be rectified.

The forests of the midwestern United States at Euro-American settlement: Spatial and physical structure based on contemporaneous survey data

We present gridded 8 km-resolution data products of the estimated stem density, basal area, and biomass of tree taxa at Euro-American settlement of the midwestern United States during the middle to late 19th century for the states of Minnesota, Wisconsin, Michigan, Illinois, and Indiana. The data come from settlement-era Public Land Survey (PLS) data (ca. 0.8-km resolution) of trees recorded by land surveyors. The surveyor notes have been transcribed, cleaned, and processed to estimate stem density, basal area, and biomass at individual points. The point-level data are aggregated within 8 km grid cells and smoothed using a generalized additive statistical model that accounts for zero-inflated continuous data and provides approximate Bayesian uncertainty estimates. The statistical modeling smooths out sharp spatial features (likely arising from statistical noise) within areas smaller than about 200 km2. Based on this modeling, presettlement Midwestern landscapes supported multiple dominant species, vegetation types, forest types, and ecological formations. The prairies, oak savannas, and forests each had distinctive structures and spatial distributions across the domain. Forest structure varied from savanna (averaging 27 Mg/ha biomass) to northern hardwood (104 Mg/ha) and mesic southern forests (211 Mg/ha). The presettlement forests were neither unbroken and massively-statured nor dominated by young forests constantly structured by broad-scale disturbances such as fire, drought, insect outbreaks, or hurricanes. Most forests were structurally between modern second growth and old growth. We expect the data product to be useful as a baseline for investigating how forest ecosystems have changed in response to the last several centuries of climate change and intensive Euro-American land use and as a calibration dataset for paleoecological proxy-based reconstructions of forest composition and structure for earlier time periods. The data products (including raw and smoothed estimates at the 8-km scale) are available at the LTER Network Data Portal as version 1.0.

Modeling post-logging height growth of black spruce forests by combining airborne LiDAR and historical forestry maps in eastern Canadian boreal forest

Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which affects global carbon dynamics and forest management. In this study, we present a novel method that combines a single airborne LiDAR acquisition and historical harvesting maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model where forest height is a function of stand age, combined with environmental variables. Our results highlight the strong predictive power of this model: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.75; relative RMSE = 19%). Moreover, our findings indicated an ecological gradient responsible for differences in height growth at the landscape scale, with better growth rates on mesic slopes compared to badly drained soils on flat lands. With the increased availability of LiDAR data, this method is promising since it can be applied to forests across the globe that are affected by stand-replacing disturbances.