Assessing impacts of management strategies may allow designing more resistant forests to wildfires. Planning-oriented models to predict the effect of stand structure and forest composition on mortality for supporting fire-smart management decisions, and allowing its inclusion in forest management optimization systems were developed. Post-fire mortality was modeled as a function of measurable forest inventory data and projections over time in 165 pure and 76 mixed forest stands in Portugal, collected by the 5th National Forest Inventory plots (NFI) plus other sample plots from ForFireS project, intercepted within 2006–2008 wildfire perimeters’ data. Presence and tree survival were obtained by examining 2450 trees from 16 species one year after the wildfire occurrence. A set of logistic regression models were developed under a three-stage modeling system: firstly multiple fixed-effects at stand-level that comprises a sub-model to predict mortality from wildfire; and another for the proportion of dead trees on stands killed by fire. At tree-level due to the nested structure of the data analyzed (trees within stands), a mixed-effect model was developed to estimate mortality among trees in a fire event. The results imply that the variation of tree mortality decreases when tree diameter at breast height increases. Moreover, the relative mortality increases with stand density, higher altitude and steeper slopes. In the same conditions, conifers are more prone to die than eucalyptus and broadleaves. Pure stands of broadleaves exhibit noticeably higher fire resistance than mixed stands of broadleaves and others species composition.

Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction.

Stem taper functions predict diameter variation along the tree stem, enabling to estimate merchantable volume according to market requirements. In this study, a stem taper function for Pinus sylvestris in Turkey was developed using the mixed-effects modelling approach, which allows some parameters to include a fixed part (common to the whole population) and a random effect (individualspecific response). We analyzed different strategies to choose the best combination of fixed parameters to expand with random effects (mixed-effects parameters): (1) expanding fixed parameters that presented the highest variability and (2) all possible combinations of one and two mixed-effects parameters; the best performance was observed in the latter. Given that inclusion of random effects was not enough to account for the existing correlation between the residuals of the same individual, the variance-covariance matrix of the error term was modelled by a first-order autoregressive structure. In addition, we evaluated the response obtained by calibration (estimation of random effects for a new individual), i.e. using a diameter measured at different heights along the stem. The selected mixed-effects model presented the best results both in the fitting and calibration steps. Generally, the mixed-effects model is recommended if an additional stem diameter measurement at 40-90 % of the total tree height is available. Otherwise, and from a predictive point of view, the model fitted by non-linear ordinary least squares is recommended, which only considers fixed parameters.

Doğu ladini (Picea orientalis L.) ülkemizin önemli ağaç türlerinden birisidir. Bu nedenle, ladin ormanlarının bugün ve geleceğe dönük yönetim ve planlama stratejilerinin geliştirilmesinde, türün büyüme ve hasılatına ilişkin bilgilere ihtiyaç duyulmaktadır. Ormanların büyüme ve hasılatına ilişkin tahminlerde kullanılan en önemli yapı taşlarından birisi, ağaç hacim tahminleridir. Gövde çapı denklemleri, bir ağaca ilişkin toplam ve ticari hacim tahminlerinde en güvenilir ve doğru yaklaşımlardan biri olarak kabul edilmektedir. Bu çalışmada, Ardahan-Posof Yöresi doğu ladini meşcerelerinden elde edilen 170 ağaç kullanılarak doğrusal olmayan karışık etkili modelleme (NLME) yaklaşımı ile gövde çapı modeli geliştirilmiştir. Karışık etkili modelleme, bir ağacın kendi içinde ve ağaçlar arasında gövde formu açısından değişimin hesaplanmasına imkân sağlamaktadır. Çalışmanın birinci aşamasında, öncelikle hangi parametrelerin tesadüfi etkili parametrelerle genişletilmesi gerektiğinin ortaya konması için modelin bir ve iki parametresine tesadüfi parametreler eklenerek olası tüm kombinasyonlar test edilmiştir. Modele tesadüfi etkili parametrelerin eklenmesi aynı ağaç için elde edilen hatalar arasında var olan korelasyonun hesaplanması için yeterli olmamış, hata terimine ilişkin varyans-kovaryans matrisi birinci derece otoregresif hata yapısı AR(1) ile modellenmiştir. Karışık etkili modele AR(1)’in eklenmesi ile hatalar arasındaki otokorelasyonun tamamının uzaklaştırılması mümkün olmuştur. İkinci aşamada, gövde üzerinde farklı noktalarda ölçülen çap değerleri kullanılarak kalibrasyon sonuçları değerlendirilmiştir. Seçilen karışık etkili model, hem model geliştirme hem de kalibrasyon için en iyi sonuçları üretmiştir. Genel olarak, kalibrasyon için toplam boyun %40-80 arasında ölçülen ekstra çapların gövde çapı modelinin tahmin performansını arttırdığı gözlenmiştir. Sonuç olarak model kalibrasyonu, karışık etkili model seçiminde önemli bir kriter olarak göz önünde bulundurulmalıdır.