Janusz Szmyt. (2014). Spatial statistics in ecological analysis: from indices to functions. Silva Fennica vol. 48 no. 1 article id 1008. https://doi.org/10.14214/sf.1008

Keywords: spatial analyses; spatial indices; spatial functions; spatial ecology

Highlights: Spatial statistics provides a quantitative description of natural variables distributed in space and time; The objectives of spatial analysis are to detect spatial patterns and to confirm if a pattern found is significant; Spatially explicit indices and functions may be applied depending on the information collected from the field; Development of the specific software supports spatial analyses.

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This paper presents a review of the most common methods in ecological studies aimed at spatial analysis of population structures (horizontal and vertical), based on point process statistics. Methods based on simple spatially explicit indices as well as more sophisticated methods relying on functions are described in a comprehensible manner. Simple indices revealing the information on spatial structure at the scale of the nearest neighbor can be easily implemented in practical forestry. On the other hand, spatial functions, based on much more detailed data, describe the spatial structure in terms of the spatial relationships between the natural processes and population structures and because of this complexity they are rarely used in forest practice. Including both methods in a single paper is also valuable from the potential reader’s point of view saving their time for searching and choosing the appropriate method to make their spatial analysis. This paper can also serve as an initial guide for young researchers or those who are going to start their studies on spatial aspects of bio-systems. Avoiding the statistical and mathematical details makes this paper understandable for readers who are not statisticians or mathematicians. Readers will find many references related to each method described here, allowing them to find solutions to different problems observed in practice. This paper ends with a list of the most common specific software packages available to support spatial analysis.

Szmyt, Department of Silviculture, Faculty of Forestry, Poznań University of Life Sciences, ul. Wojska Polskiego 69, 60-625 Poznań, Poland E-mail: jszmyt@up.poznan.pl

Category : Discussion article

article id 24053, category Discussion article

Francisco X. Aguilar, Marie Lautrup, Dohun Kim, Ane C. Tangen, Aapo Rautiainen, Huntley Brownell, Lucas N. López, Andrew D. H. Stratton, Sebastian Glasenapp, Silvia M. Korth, Hanne K. Sjølie, Jette Bredahl Jacobsen. (2024). Inherently spatial: data and analytical insights for the identification of forest socio-ecological hotspots. Silva Fennica vol. 58 no. 5 article id 24053. https://doi.org/10.14214/sf.24053

Keywords: forest sector; spatial analyses; adaptive interventions; ecological-social systems; robustness; spatial data

Abstract | Full text in HTML | Full text in PDF | Author Info

We draw insights regarding intricacies with spatially explicit data and analyses when studying the vulnerability of forest socio-ecological systems to disruptive abiotic and biotic factors. Common issues associated with data include location precision, spatial delimitation, methodological comparability, and measurement consistency. Spatial data analyses are challenged by issues of interpolation and extrapolation, inferences using data at different spatial scales, and assessment of disruption impacts at detectable spatial scales. The inextricable empirical nature of spatial data and analyses requires carefully conducting and disclosing the sensitivity of findings, and including robustness tests to openly inform decision-makers on issues of uncertainty associated with possible interventions. These considerations might be central to identifying forest socio-ecological hotspots as forest-dominated geographic areas encompassing social and ecological systems vulnerable to disruptions caused by abiotic and biotic factors, but where risks to human wellbeing may be considerably reduced through adaptive interventions.

Aguilar, Swedish University of Agricultural Sciences (SLU), Department of Forest Economics, SE-901 83 Umeå, Sweden https://orcid.org/0000-0003-0226-4467 E-mail: francisco.aguilar@slu.se
Lautrup, University of Copenhagen, Department of Food and Resource Economics, Rolighedsvej 23, 1958 Frederiksberg C, Denmark E-mail: ml@ifro.ku.dk
Kim, Swedish University of Agricultural Sciences (SLU), Department of Forest Economics, SE-901 83 Umeå, Sweden https://orcid.org/0000-0002-1919-3346 E-mail: dohun.kim@slu.se
Tangen, Inland Norway University of Applied Sciences, Department of Forestry and Wildlife Management, P.O. Box 2400, Koppang, Norway https://orcid.org/0009-0001-3145-8159 E-mail: ane.tange@inn.no
Rautiainen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: aapo.rautiainen@luke.fi
Brownell, University of Copenhagen, Department of Geosciences and Natural Resource Management, Forest and Bioresources, Rolighedsvej 23, 1958 Frederiksberg C, Denmark https://orcid.org/0000-0002-3798-8783 E-mail: hb@ign.ku.dk
López, Inland Norway University of Applied Sciences, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, P.O. Box 2400, Koppang, Norway https://orcid.org/0009-0006-6860-3408 E-mail: lucas.lopez@inn.no
Stratton, University of Copenhagen, Department of Food and Resource Economics, Rolighedsvej 23, 1958 Frederiksberg C, Denmark https://orcid.org/0000-0002-6566-2043 E-mail: adhs@ifro.ku.dk
Glasenapp, Johann Heinrich von Thünen Institute, Institute of Forestry, Leuschnerstraße 91, 21031 Hamburg-Bergedorf, Germany E-mail: sebastian.glasenapp@thuenen.de
Korth, Universidad Nacional de Misiones Facultad de Ciencias Forestales, Bertoni 124, Eldorado 3380, Argentina https://orcid.org/0009-0007-3261-8234 E-mail: silviakorth@hotmail.com
Sjølie, Inland Norway University of Applied Sciences, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, P.O. Box 2400, Koppang, Norway https://orcid.org/0000-0001-8099-3521 E-mail: hanne.sjolie@inn.no
Bredahl Jacobsen, University of Copenhagen, Department of Food and Resource Economics, Rolighedsvej 23, 1958 Frederiksberg C, Denmark https://orcid.org/0000-0002-1313-6228 E-mail: jbj@ifro.ku.dk

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