Lahopuun spatiaalinen jakautuminen Suomen talousmetsissä

Coarse woody debris (CWD) is an important indicator of biodiversity in forests, the source of organic material and carbon dioxide in the atmosphere and the habitat for a wide variety of organisms. In southern Finland, the amount of CWD per hectare in fresh mineral soils of old spruce-dominant forests can be as much as 90–120 m3 ha-1. In managed forests, however, it is only about 2–10 m3 ha-1, due to the management methods used in forests. The spatial pattern of CWD in managed forests is an essential research area, although it has rarely been studied. With knowledge of the spatial pattern of CWD in managed forests, it is possible to investigate inventory methods of rare phenomena, such as adaptive cluster sampling or line intersect sampling. The field measurements were performed in eastern Finland as part of one of the most extensive projects in Finland to inventory rare phenomena. Altogether 340 hectares of managed forest were inventoried by strip survey and over 11 600 dead trees were measured. The spatial pattern of CWD was examined with Ripley’s K –method. The method allows spatial assessment at different scales among and between species and enables one to determine how CWD is located in the study area used. The results of this study indicate that the CWD is located clustered in the area level in every spatial scale below 25 m. The spatial pattern of the CWD was complete random in approximately 63% of the forest management compartments in every studied spatial scale. The spatial pattern was clustered in 12% of the compartments. The spatial pattern was a mixture of random and clustered pattern in the rest (25%) of the compartments. In the future, the results of the study will be used as background information for examining inventory methods of rare phenomena and damages in managed forests.Lahopuu on tärkeä talousmetsien monimuotoisuusindikaattori. Kuollut tai kuoleva puu on myös tärkeä orgaanisen materiaalin lähde, hiilen sitoja, sekä elinympäristö suurelle määrälle erilaisia kasveja ja eläimiä. Eteläisen Suomen vanhoissa luonnontilaisissa kuusikoissa lahopuun määrä voi olla jopa 90–120 m3 ha-1. Talousmetsissä lahopuun määrä samalla alueella on keskimäärin ainoastaan 2–10 m3 ha-1, johtuen muun muassa käytetyistä metsänhoitotoimenpiteistä. Lahopuun spatiaalista jakautumista talousmetsiin on tutkittu tähän mennessä ainoastaan vähän. Tieto lahopuun jakautumisesta on tärkeää esimerkiksi harvinaisten ilmiöiden inventointimenetelmiä kehitettäessä, esimerkkinä adaptiivinen ryväsotanta (ACS). Inventointi suoritettiin Itä-Suomessa, Sonkajärven Rautavaaran kuntien alueilla. Inventointiprojekti oli yksi Suomen suurimmista harvinaisten ilmiöiden kartoitusprojekteista. Yhteensä 340 ha alueelta talousmetsää mitattiin yli 11 600 kuollutta puuta. Lahopuun spatiaalista jakautumista tutkittiin Ripleyn K-funktion avulla. Menetelmän avulla ilmiön tilajärjestystä voidaan tutkia alueella eri mittakaavoissa. Tulosten perusteella lahopuu on tutkimusalueella aluetasolla jakautunut ryhmittäin kaikilla tutkituilla mittakaavoilla (< 25 m). Kuviotason tulokset osoittavat, että noin 63 %:lla metsätalouskuvioista lahopuun tilajärjestys on täysin satunnainen kaikilla tutkituilla mittakaavoilla. Kuvioista 12 %:lla tilajärjestys oli kaikilla mittakaavoilla ryhmittäinen ja lopuilla noin 25 %:lla kuvioista tilajärjestys oli sekoitus satunnaisesta ja ryhmittäisestä. Tulevaisuudessa tutkimuksen tuloksia käytetään aputietona harvinaisten ilmiöiden sekä metsätuhojen inventointimenetelmien kehitystyössä

Hyönteistuhoriskien hallinta uusilla teknologioilla

Tieteen tori: Luonnonvarariskien hallint

Influence of soil and topography on defoliation intensity during an extended outbreak of the common pine sawfly (Diprion pini L.)

Insect herbivore disturbances are likely to intensify as a consequence of climate change. In Finland, outbreaks of the common pine sawfly (Diprion pini L.), which feeds on Scots pine (Pinus sylvestris L.) needles, and resulting damage to forests have already increased. Although drivers of sawfly outbreak dynamics have been investigated, the effects of topography and soil fertility have not been fully elucidated. We studied the effect of elevation, slope and soil properties (carbon and nitrogen contents, C/N ratio, pH, texture and horizon thicknesses) on the defoliation intensity of 28 plots (227-531 m(2)), located in a 34.5 km(2) forested area in eastern Finland suffering from an extended outbreak of D. pini. Plot elevation and slope (relative relief 35 m, maximum elevation 200 m a. s.l.) were derived from a digital elevation model and the soil properties from samples of the humus layer (Of + Oh), (Ah+) E and B horizons of podzol profiles. Defoliation was greater on the more fertile and flatter sites than on less fertile and steeper sites, but independent of elevation. The soil property most strongly correlated to plot mean defoliation was the C/N ratio of the humus layer (Spearman's rho = -0.68). However, logistic modelling showed that the thickness of the (Ah+) E-horizon had the highest classification accuracy in predicting the probability of a plot having moderate to severe (> 20%) defoliation. Our study showed that forest damage caused by D. pini was related to topography and soil fertility. Taking these factors into account could help in understanding the population dynamics of D. pini, in modeling of insect outbreaks and in forest management planning.Peer reviewe

Hemlokin villakirvan nissimallit invaasion kattamasta Pohjois-Amerikan levinneisyysalueesta ja projektiot alkuperäiseltä levinneisyysalueelta ja tulevaisuuden ilmastosta

The hemlock woolly adelgid (Adelges tsugae Annand - HWA) is invasive in eastern North America where it causes extensive mortality to hemlock communities. The future of these communities under projected climate change is an issue of landscape ecological interest and speculation. We employed the MaxEnt algorithm with the random subset feature selection algorithm (RSFSA) in creating HWA niche models. Final models were ensembles of 12 statistically best models with six predictors each. Out of 119 climatic, topographic, and soil variables, 42 were used in at least one final model. Soil features, followed by climate and topographic features, were most common in selected models. The three most important variables among all models were November potential evapotranspiration, slope, and percent Ochrepts soil. The potential distributions of HWA within eastern North America were projected under historical and four future climate scenarios for 2050 and 2070 under low and high CO2 emissions. The mean of the minimum values for the minimum temperature of the coldest month from the 12 MaxEnt model projections in eastern North America was -15.8°C. This value was close to -15°C, the extreme minimum temperature found for both HWA occurrence points and previously reported HWA cold temperature limits. These results indicate that HWA may be close to equilibrium distribution in eastern North America under current climate. We also reverse-casted the eastern North American MaxEnt model back onto the HWA native ranges in eastern Asia and western North America. The projections match best with native ranges in Asian islands, such as Japan, and the Cascade Mountains in western North America. Statistically significant HWA range shifts of 221-468 km northwards and 110-164 km eastwards were projected by the 12 models for 2050-2070. The 2070 high CO2 emission scenario models projects HWA suitability throughout most of the northern range of eastern hemlock.Peer reviewe

Classification of Defoliated Trees Using Tree-Level Airborne Laser Scanning Data Combined with Aerial Images

Climate change and rising temperatures have been observed to be related to the increase of forest insect damage in the boreal zone. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini can cause severe growth loss and tree mortality in Scots pine (Pinus sylvestris L.) (Pinaceae). In this study, logistic LASSO regression, Random Forest (RF) and Most Similar Neighbor method (MSN) were investigated for predicting the defoliation level of individual Scots pines using the features derived from airborne laser scanning (ALS) data and aerial images. Classification accuracies from 83.7% (kappa 0.67) to 88.1% (kappa 0.76) were obtained depending on the method. The most accurate result was produced using RF with a combination of data from the two sensors, while the accuracies when using ALS and image features separately were 80.7% and 87.4%, respectively. Evidently, the combination of ALS and aerial images in detecting needle losses is capable of providing satisfactory estimates for individual trees.Peer reviewe

Development of a method for monitoring of insect induced forest defoliation - limitation of MODIS data in Fennoscandian forest landscapes

We investigated if coarse-resolution satellite data from the MODIS sensor can be used for regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed. Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for optimisation. The method was developed in fragmented and heavily managed forests in eastern Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly (Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain birch (Betula pubescens ssp. Czerepanovii N. I. Orlova) forests in northern Sweden, infested by autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.). In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and a misclassification of healthy stands of 22%. In areas with long outbreak histories the method resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of the damage detected and a misclassification of healthy samples of 19%. Our results indicate that MODIS data may fail to detect damage in fragmented forests, particularly when the damage history is long. Therefore, regional studies based on these data may underestimate defoliation. However, the method yielded accurate results in homogeneous forest ecosystems and when long-enough periods without damage could be identified. Furthermore, the method is likely to be useful for insect disturbance detection using future medium-resolution data, e. g. from Sentinel-2.Peer reviewe

Impacts of natural enemies and stand characteristics on cocoon mortality of the pine sawfly Diprion pini in a Fennoscandian boreal forest.

Peer reviewe

Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

Climate-related extended outbreaks and range shifts of destructive bark beetle species pose a serious threat to urban boreal forests in North America and Fennoscandia. Recent developments in low-cost remote sensing technologies offer an attractive means for early detection and management of environmental change. They are of great interest to the actors responsible for monitoring and managing forest health. The objective of this investigation was to develop, assess, and compare automated remote sensing procedures based on novel, low-cost hyperspectral imaging technology for the identification of bark beetle infestations at the individual tree level in urban forests. A hyperspectral camera based on a tunable Fabry-Perot interferometer was operated from a small, unmanned airborne vehicle (UAV) platform and a small Cessna-type aircraft platform. This study compared aspects of using UAV datasets with a spatial extent of a few hectares (ha) and a ground sample distance (GSD) of 10-12 cm to the aircraft data covering areas of several km(2) and having a GSD of 50 cm. An empirical assessment of the automated identification of mature Norway spruce (Picea abies L. Karst.) trees suffering from infestation (representing different colonization phases) by the European spruce bark beetle (Ips typographus L.) was carried out in the urban forests of Lahti, a city in southern Finland. Individual spruces were classified as healthy, infested, or dead. For the entire test area, the best aircraft data results for overall accuracy were 79% (Cohen's kappa: 0.54) when using three crown color classes (green as healthy, yellow as infested, and gray as dead). For two color classes (healthy, dead) in the same area, the best overall accuracy was 93% (kappa: 0.77). The finer resolution UAV dataset provided better results, with an overall accuracy of 81% (kappa: 0.70), compared to the aircraft results of 73% (kappa: 0.56) in a smaller sub-area. The results showed that novel, low-cost remote sensing technologies based on individual tree analysis and calibrated remote sensing imagery offer great potential for affordable and timely assessments of the health condition of vulnerable urban forests.Peer reviewe

Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Forest disturbances caused by pest insects are threatening ecosystem stability, sustainable forest management and economic return in boreal forests. Climate change and increased extreme weather patterns can magnify the intensity of forest disturbances, particularly at higher latitudes. Due to rapid responses to elevating temperatures, forest insect pests can flexibly change their survival, dispersal and geographic distributions. The outbreak pattern of forest pests in Finland has evidently changed during the last decade. Projection of shifts in distributions of insect-caused forest damages has become a critical issue in the field of forest research. The Common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini has resulted in severe growth loss and mortality of Scots pine (Pinus sylvestris L.) (Pinaceae) in eastern Finland. In this study, tree-wise defoliation was estimated for five different needle loss category classification schemes and for 10 different simulated airborne laser scanning (ALS) pulse densities. The nearest neighbor (NN) approach, a nonparametric estimation method, was used for estimating needle loss of 701 Scots pines, using the means of individual tree features derived from ALS data. The Random Forest (RF) method was applied in NN-search. For the full dense data (~20 pulses/m2), the overall estimation accuracies for tree-wise defoliation level varied between 71.0% and 86.5% (kappa-values of 0.56 and 0.57, respectively), depending on the classification scheme. The overall classification accuracies for two class estimation with different ALS pulse densities varied between 82.8% and 83.7% (kappa-values of 0.62 and 0.67, respectively). We conclude that ALS-based estimation of needle losses may be of acceptable accuracy for individual trees. Our method did not appear sensitive to the applied pulse densities.Peer reviewe