Elsevier BV

This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design-based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data..We review studies on large-area forest surveys based on model-assisted, model-based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.

Distance-dependent individual-tree models have commonly been found to add little predictive power to that of distance-independent ones. One possible reason is plasticity, the ability of trees to lean and to alter crown and root development to better occupy available growing space. Being able to redeploy foliage (and roots) into canopy gaps and less contested areas can diminish the importance of stem ground locations. Plasticity was simulated for 3 intensively measured forest stands, to see to what extent and under what conditions the allocation of resources (e.g., light) to the individual trees depended on their ground coordinates. The data came from 50 × 60 m stem-mapped plots in natural monospecific stands of jack pine, trembling aspen and black spruce from central Canada. Explicit perfect-plasticity equations were derived for tessellation-type models. Qualitatively similar simulation results were obtained under a variety of modelling assumptions. The effects of plasticity varied somewhat with stand uniformity and with assumed plasticity limits and other factors. Stand-level implications for canopy depth, distribution modelling and total productivity were examined. Generally, under what seem like conservative maximum plasticity constraints, spatial structure accounted for less than 10% of the variance in resource allocation. The perfect-plasticity equations approximated well the simulation results from tessellation models, but not those from models with less extreme competition asymmetry. Whole-stand perfect plasticity approximations seem an attractive alternative to individual-tree models.

Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape. In addition, the fluctuations of wood prices influence greatly forest revenues. Markov decision process models (MDPs) offer a rigorous and practical way of developing optimum management strategies, given these multiple sources of risk. Examples illustrate how such management guidelines are obtained with MDPs for combined ecological and economic objectives, including diversity of tree species and size, landscape diversity, old growth preservation, and carbon sequestration. The findings illustrate the power of the MDP approach to deal with risk in forest resource management. They recognize that the future is best viewed in terms of probabilities. Given these probabilities, MDPs tie optimum adaptive actions strictly to the state of the forest and timber prices at decision time. The methods are theoretically rigorous, numerically efficient, and practical for field implementation.

The first three censuses of the 50-ha plot at Barro Colorado Island spanned an unusually harsh dry season during the 1983 El Niño. By the early 1990s, we had documented increases in tree mortality, tree growth, and large population fluctuations of many species during the 1982–1985 census interval. At the time, we asserted that increasing drought frequency would greatly affect the forest. With the benefit of five more censuses at Barro Colorado from 1995–2015, we can now put the 1980 conditions in a longer perspective and test the hypothesis that increasing droughtiness has continued to change the forest. A 50-ha forest plot on Barro Colorado Island was censused eight times, in 1982 and every five years since 1985. All free-standing woody stems were measured, mapped, and identified in each census. 1) The period 1982–1992 included several extreme dry seasons, not just 1983, but since then there have been few such droughts. 2) Dbh growth declined from a peak in the early 1980s to its lowest in the early 1990s. From 1995–2015 it increased slightly, but not returning to the initial peak. Nearly every species and all dbh categories followed the same pattern. 3) The elevated stand-wide mortality rate of large trees during the 1982–1985 drought has not returned, and most individual species showed the same pattern of elevated mortality in the 1980s followed by low and fairly stable mortality after 1990. 4) Sapling mortality declined after 1985, but rose again in the late-90s, so the 1980s drought period no longer looks unusual. Mortality of individual species’ saplings fluctuated erratically, including cases where mortality during the drought was lower than after. 5) Population sizes of individual species fluctuated in all possible directions. Some species declined precipitously during the drought, then recovered, but others did not recover. Other species increased in abundance during the drought. Droughts of the 1980s elevated tree growth and mortality at Barro Colorado, but since 1990, demographic rates have remained lower, paralleling a moderate climate with few severe droughts after 1990. Moisture-demanding species suffered during the drought, but many have since recovered. We do not know how often such drought periods recur. Moreover, many species’ abundances fluctuated over 35 years with no known cause.

Forest management aims at obtaining a sustainable production of wood to be harvested to generate products or energy. However, the quantitative influence of forest management and of removals by harvest on biomass stocks has rarely been analysed on a large scale based on measurements. Two hypotheses prevail: management induces a reduction of wood stocks due to cuttings, versus no impact because of increased growth of the remaining trees. Using data collected for 2840 permanent plots across Romania from the National Forest Inventory representing ~ 2.5 Mha, we have tested to what extent different management types and treatments can influence the biomass stock and productivity of beech forests, and attempt to quantify these effects both on the short and long terms. Three main types of beech forest management are implemented in Romania with specific objectives: intensive wood production in production forests, protection of ecosystem services (e.g. watersheds, avalanche protection) in protection forests, and protection of the forest and its biodiversity in protected forests. Production forests encompass two treatments differing according to the stand regeneration method: the age class rotation management and the group shelterwood management. We show that forest management had little influence on the biomass stocks at a given stand age. The highest stocks at stand age 100 were observed in production forests (the most intensively managed forests). Consequences of early cuttings were very short-termed because the increase in tree growth rapidly compensated for tree cuttings. The cumulated biomass of production forests exceeded that of protected and protection forests. Regarding the treatment, the group shelterwood forests had a markedly higher production over a full rotation period. The total amount of deadwood was primarily driven by the amount of standing deadwood, and no management effect was detected. Given the relatively low-intensity management in Romania, forest management had no negative impact on wood stocks in beech forests biomass stocks at large scale. Stand productivity was very similar among management types or treatments. However cumulated biomass in production forests was higher than in protection or protected forests, and differed markedly according to treatments with a higher cumulated biomass in shelterwood forests.