Quantile regression for estimating Douglas-fir natural regeneration potential using the R package quaxnat: Advanced ecological modeling for the management of nature conservation and silviculture

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling Pub Date : 2025-02-01 DOI:10.1016/j.ecolmodel.2024.110968

Maximilian Axer , Robert Schlicht , Lukas Blickensdörfer

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引用次数: 0

Abstract

Recent extreme weather conditions in Europe have led to widespread destruction of Norway spruce by storms and bark beetles, creating large clearings that need replanting. The shortage of planting material has shifted focus to natural regeneration processes, with Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) emerging as a potential substitute due to its growth performance and drought tolerance. This study introduces and applies methods for investigating the regeneration ecology of Douglas-fir, focusing on the potential density of established regeneration and its dependence on the distance to the nearest seed source.

This dependence is modelled with various classical spatial dispersal kernels, the parameters of which are estimated with a quantile regression approach implemented in a new R package quaxnat. Regeneration data from 44,257 sample plots in the state forest of Lower Saxony, Germany, are combined with remote sensing-based positions of potential seed trees to illustrate these methods. Among the standard dispersal kernels provided by quaxnat, the spatial t distribution proves to be the most suitable. Here, for the .999th quantile, the estimated potential regeneration density reaches almost 11,000 trees per hectare in the immediate vicinity of the seed trees and decreases sharply with increasing distance.

A simple simulation model that takes dispersal and establishment into account illustrates how these results can be linked to management scenarios. The study provides valuable information for nature conservation and silviculture, suggesting buffer zones around sensitive habitats and guiding forest management decisions regarding natural regeneration options.

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来源期刊

Ecological Modelling 环境科学-生态学

CiteScore

5.60

自引率

6.50%

发文量

259

审稿时长

69 days

期刊介绍： The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).