Forest Monitoring - Assessment, Analysis and Warning System for Forest Ecosystem Status

被引:0
|
作者
Badea, Ovidiu [1 ,2 ]
Silaghi, Diana [1 ,2 ]
Neagu, Stefan [1 ]
Taut, Ioan [1 ,3 ]
Leca, Stefan [1 ,2 ]
机构
[1] Forest Res & Management Inst, Voluntari 77190, Ilfov, Romania
[2] Transilvania Univ Brasov, Fac Silviculture & Forest Engn, Brasov 500068, Romania
[3] Univ Agr Sci & Vet Med, Cluj Napoca 400372, Romania
关键词
air pollution; climate change; crown condition; forest monitoring; national and transnational network; TREE MORTALITY; AIR-POLLUTION; DROUGHT; OZONE; MOUNTAINS; HEAT;
D O I
暂无
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Forests provide essential benefits and services as an important component of terrestrial ecosystems. Their functionality and health result from multiple and cumulative interactions of biotic and abiotic stress factors such as air pollution, climate change, changes in land use, and poor management practices. A forest monitoring system was established to identify, analyze and assess the degradation of European forests. Two levels of forest monitoring were developed: I) large-scale forest condition surveys, based on an European grid system starting in 1986 and II) an intensive non-systematic survey network placed in representative forest ecosystems starting in 1994. Romania implemented both level I (1990-1991) and level II (1991-1992) forest monitoring surveys with the results showing the effects of increased air temperatures and a drastic decrease of precipitation since the decade of 1971-1980. Thus, the highest values of damaged trees (crown defoliation >25%) percent were recorded in 1993, 1994, 2000 and 2003 both in the national and European networks. Also, in southern and South-Eastern Romania the forests are more frequently damaged as a response to worsening of climatic factors in this region in recent decades, with temperatures rising 0.7-0.8 degrees C. In general, in Romania, ozone concentrations remained below the critical threshold (40-50 ppb) for affecting growth or health of trees. The levels of S-SO4 and N-NO3 declined in the atmosphere but the accumulation continued to increase in the soil, leading to soil acidification, mainly at depths of 10-40 cm). In general, during the last decade, Romanian forests were affected at low to medium intensities with damage rate up to 11% of the trees and the status of general forest health improved slightly.
引用
收藏
页码:613 / 625
页数:13
相关论文
共 50 条
  • [41] Sustainable smart forest monitoring system for burning forest and deforestation detection
    Darlis, Denny
    Sirait, Dion Saputra Parulian
    Maulana, Dimas Bayu
    3RD ANNUAL APPLIED SCIENCE AND ENGINEERING CONFERENCE (AASEC 2018), 2018, 197
  • [42] THE FOREST FIRE RISK MONITORING SYSTEM
    Kwiatkowski, Miroslaw
    Szczygiel, Ryszard
    Piwnicki, Jozef
    Kolakowski, Bartlomiej
    Klimczyk, Alina
    CHALLENGES AND OPPORTUNITIES FOR 21ST-CENTURY FORESTRY, 2015, : 107 - 108
  • [43] Intelligent forest fire monitoring system
    Maja Stula
    Damir Krstinic
    Ljiljana Seric
    Information Systems Frontiers, 2012, 14 : 725 - 739
  • [44] Multisensor UAV System for the Forest Monitoring
    Novak, Milan
    Prokysek, Milos
    Dolezal, Petr
    Hais, Martin
    Gril, Stanislav
    Davidkova, Marketa
    Geyer, Jakub
    Hofmann, Peter
    Paudyal, Rajan
    2020 10TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER INFORMATION TECHNOLOGIES (ACIT), 2020, : 293 - 296
  • [45] Intelligent forest fire monitoring system
    Stula, Maja
    Krstinic, Damir
    Seric, Ljiljana
    INFORMATION SYSTEMS FRONTIERS, 2012, 14 (03) : 725 - 739
  • [46] PRELIMINARY ASSESSMENT OF THE STATUS OF THE FOREST ELEPHANT IN ZAIRE
    ALERS, MPT
    BLOM, A
    KIYENGO, CS
    MASUNDA, T
    BARNES, RFW
    AFRICAN JOURNAL OF ECOLOGY, 1992, 30 (04) : 279 - 291
  • [47] Multi-stakeholder assessment of forest sustainability: Multi-criteria analysis and the case of the Ontario forest assessment system
    Mendoza, GA
    Dalton, WJ
    FORESTRY CHRONICLE, 2005, 81 (02): : 222 - 228
  • [48] Overflow warning and remote monitoring technology based on improved random forest
    Haibo Liang
    Haochen Han
    Pengbo Ni
    Yingjun Jiang
    Neural Computing and Applications, 2021, 33 : 4027 - 4040
  • [49] Overflow warning and remote monitoring technology based on improved random forest
    Liang, Haibo
    Han, Haochen
    Ni, Pengbo
    Jiang, Yingjun
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (09): : 4027 - 4040
  • [50] Towards ecosystem service assessment: Developing biophysical indicators for forest ecosystem services
    Tiemann, Andre
    Ring, Irene
    ECOLOGICAL INDICATORS, 2022, 137