The Faculty of Forestry Sciences, Landscape Architecture and Ecoengineering “Hans Em” of Ss. Cyril and Methodius University in Skopje, often searched as the Faculty of Forestry of the University of Skopje, is a key institution in North Macedonia for forestry, landscape architecture, ecoengineering, nature conservation and forest ecosystem management. Important Macedonian SEO terms are included in the text: шумарство, шумарски науки, пејзажна архитектура, екоинженеринг, заштита на природата, шумски екосистеми, дрвна технологија, ГИС.
Students and researchers work with data on tree diameter and height, growing stock, biomass, increment, forest health, biodiversity, erosion, soil and water resources, landscape elements, GIS layers and environmental risks. This article belongs to the F9 hub: statistical help for forestry faculties, SPSS, ecology, GIS and growth models.
Statistical data analysis for the Faculty of Forestry of the University of Skopje
The Faculty of Forestry Sciences, Landscape Architecture and Ecoengineering “Hans Em” of Ss. Cyril and Methodius University in Skopje, in the regional SEO context often searched as the Faculty of Forestry of the University of Skopje, is an important institution for education and research in forestry, nature conservation, landscape architecture, ecoengineering, soil and water resources and sustainable forest ecosystem management.
For better search visibility, Macedonian terms are included: шумарство, шумарски науки, пејзажна архитектура, екоинженеринг, заштита на природата, шумски екосистеми, дрвна технологија, ГИС. These terms cover key study and research areas and make the article relevant for users searching in Macedonian, English, German and South Slavic languages.
Research in Skopje often lies at the intersection of natural sciences, technical disciplines and environmental sciences. Data may come from field measurements, ecological studies, GIS analysis, erosion assessment, forest stand research, landscape architecture projects, laboratory testing and analysis of soil and water resources. Statistical analysis must therefore be connected with research design, measurement type and practical meaning.
At StatistischeBeratung.de, professional support is provided throughout the research process — from research design and dataset structuring to method selection, SPSS analysis, interpretation and table preparation. The author remains responsible for the final text and interpretation. This article belongs to the F9 hub: statistical help for forestry faculties, SPSS, ecology, GIS and growth models.
Specific characteristics of forestry research in Skopje
Forestry and ecoengineering research in North Macedonia often includes very different natural conditions: mountainous areas, different forest types, drought periods, erosion processes, degraded soils, water resources, land-use changes and climate change impacts. Data should therefore not be interpreted only through mean values, but within ecological and spatial context.
It is essential to separate real effects of location, treatment, tree species, slope, exposure, altitude or management from natural variability. If stands, areas, species or degradation levels are compared, statistics must show whether differences are significant and practically relevant.
Data types
Projects may include dendrometric data, ecological indicators, GIS layers, erosion data, soil and water resource data, laboratory values, landscape parameters and survey data.
Dendrometric data include diameter at breast height, tree height, basal area, volume, growing stock, increment, biomass and stand density. Ecological data include biodiversity, species occurrence, regeneration, habitat structure, degradation and forest health. GIS data include spatial layers, slope, exposure, land cover, erosion risk, road access and land-use change.
Research design
Field measurements and sample plots
A large part of research is based on sample plots. Number of plots, plot size, inclusion criteria, sampling method and repeated measurement structure must be clearly defined.
Comparison of locations, stands and species
Comparison of stands, locations, tree species, habitat types, degradation levels or management practices requires suitable statistical methods such as t-test, ANOVA, Kruskal-Wallis test, regression or multivariate procedures.
GIS and spatial analysis
GIS is especially important in erosion research, soil and water protection, landscape architecture and forest ecosystems. Spatial data should be linked with quantitative indicators.
Growth and increment models
Growth and increment models are important for evaluating forest stand development, volume, biomass and long-term management. Since growth is often nonlinear, nonlinear or predictive models may be useful.
Important statistical methods
Descriptive statistics present means, medians, standard deviations, minima, maxima, coefficients of variation and graphs.
ANOVA and post-hoc tests compare several groups, such as locations, tree species, treatments, stands or landscape categories. After significant results, post-hoc tests enable precise identification of differences.
Correlation analysis examines relationships between diameter and height, slope and erosion, climate and increment, or biodiversity and habitat structure.
Regression analysis models volume, biomass, increment, erosion risk, soil degradation, damage probability or environmental effects.
Multivariate methods such as PCA and cluster analysis are useful when many related variables are present, for example in habitat classification, location grouping or degradation profiles.
Nonparametric methods such as Mann-Whitney U test, Kruskal-Wallis test or Spearman correlation are appropriate when assumptions of normality or homogeneity of variance are not met.
SPSS, GIS and interpretation
SPSS is used for descriptive statistics, group comparisons, ANOVA, regression, correlation and basic multivariate analyses. GIS tools are necessary for spatial data, but spatial results often require additional quantitative interpretation.
In forestry, landscape architecture and ecoengineering, statistical results must be interpreted in subject-matter context: forest ecosystems, nature conservation, erosion risk, soil and water quality, spatial planning and sustainable resource management.
Sample size and reliability
The number of plots, trees, locations, GIS units, time points and sampling strategy directly affects reliability. Small samples may lead to low power, while poor design may make interpretation difficult even with many measurements.
Typical topics for Skopje
Typical topics include forestry sciences, landscape architecture, ecoengineering, nature conservation, erosion, soil and water resources, GIS analysis, growth models, increment, biomass, biodiversity, habitat degradation, forest restoration, spatial planning and sustainable management of forest ecosystems.
Workflow
The workflow includes topic and objective analysis, dataset review, method selection, SPSS analysis, table preparation and interpretation. I prepare statistical results and suggest how to present them in the academic paper. The author remains responsible for the final text and interpretation.
FAQ
Can field plot data be analyzed?
Yes. Data by plots, trees, stands, locations and time points can be analyzed.
Can GIS data be analyzed?
Yes. GIS data can be connected with quantitative statistics.
Are growth models important for forestry?
Yes. Growth and increment models often require regression, nonlinear models or predictive approaches.
Can ecoengineering data be analyzed?
Yes. Erosion, soil, water, degradation and environmental risk data can be statistically analyzed and linked with GIS results.
Keywords
statistics Faculty of Forestry Skopje, Faculty of Forestry Sciences Skopje statistics, шумарство statistics, шумарски науки statistics, пејзажна архитектура statistics, екоинженеринг statistics, заштита на природата statistics, GIS forestry, forest growth models, SPSS forestry
Metatext
Statistical data analysis for the Faculty of Forestry Sciences, Landscape Architecture and Ecoengineering “Hans Em” in Skopje: SPSS, GIS, ecology, growth models, landscape architecture and ecoengineering.
