Response diversity, functional redundancy, and post-logging productivity in northern temperate and boreal forests.

The development of efficient ecosystem resilience indicators was identified as one of the key research priorities in the improvement of existing sustainable forest management frameworks. Two indicators of tree diversity associated with ecosystem functioning have recently received particular attention in the literature: functional redundancy (FR) and response diversity (RD). We examined how these indicators could be used to predict post-logging productivity in forests of Québec, Canada. We analysed the relationships between pre-logging FR and RD, as measured with sample plots, and post-logging productivity, measured as seasonal variation in enhanced vegetation index obtained from MODIS satellite imagery. The effects of the deciduous and coniferous tree components in our pre-disturbance diversity assessments were isolated in order to examine the hypothesis that they have different impacts on post-disturbance productivity. We also examined the role of tree species richness and species identity effects. Our analysis revealed the complementary nature of traditional biodiversity indicators and trait-based approaches in the study of biodiversity-ecosystem-functioning relationships in dynamic ecosystems. We report a significant and positive relationship between pre-disturbance deciduous RD and post-disturbance productivity, as well as an unexpected significant negative effect of coniferous RD on productivity. This negative relationship with post-logging productivity likely results from slower coniferous regeneration speeds and from the relatively short temporal scale examined. Negative black-spruce-mediated identity effects were likely associated with increased stand vulnerability to paludification and invasion by ericaceous shrubs that slow down forest regeneration. Response diversity outperformed functional redundancy as a measure of post-disturbance productivity most likely due to the stand-replacing nature of the disturbance considered. To the best of our knowledge, this is among the first studies to report a negative significant relationship between a component of RD and ecosystem functioning, namely coniferous RD and forest ecosystem productivity after a stand-replacing disturbance.

Salvage logging following fires can minimize boreal caribou habitat loss while maintaining forest quotas: An example of compensatory cumulative effects.

Protected area networks are the dominant conservation approach that is used worldwide for protecting biodiversity. Conservation planning in managed forests, however, presents challenges when endangered species use old-growth forests targeted by the forest industry for timber supply. In many ecosystems, this challenge is further complicated by the occurrence of natural disturbance events that disrupt forest attributes at multiple scales. Using spatially explicit landscape simulation experiments, we gather insights into how these large scale, multifaceted processes (fire risk, timber harvesting and the amount of protected area) influenced both the persistence of the threatened boreal caribou and the level of timber supply in the boreal forest of eastern Canada. Our result showed that failure to account explicitly and a priori for fire risk in the calculation of timber supply led to an overestimation of timber harvest volume, which in turn led to rates of cumulative disturbances that threatened both the long-term persistence of boreal caribou and the sustainability of the timber supply itself. Salvage logging, however, allowed some compensatory cumulative effects. It minimised the reductions of timber supply within a range of ∼10% while reducing the negative impact of cumulative disturbances caused by fire and logging on caribou. With the global increase of the human footprint on forest ecosystems, our approach and results provide useful tools and insights for managers to resolve what often appear as lose-lose situation between the persistence of species at risk and timber harvest in other forest ecosystems. These tools contribute to bridge the gap between conservation and forest management, two disciplines that remain too often disconnected in practice.

Unusual forest growth decline in boreal North America covaries with the retreat of Arctic sea ice.

The 20th century was a pivotal period at high northern latitudes as it marked the onset of rapid climatic warming brought on by major anthropogenic changes in global atmospheric composition. In parallel, Arctic sea ice extent has been decreasing over the period of available satellite data records. Here, we document how these changes influenced vegetation productivity in adjacent eastern boreal North America. To do this, we used normalized difference vegetation index (NDVI) data, model simulations of net primary productivity (NPP) and tree-ring width measurements covering the last 300 years. Climatic and proxy-climatic data sets were used to explore the relationships between vegetation productivity and Arctic sea ice concentration and extent, and temperatures. Results indicate that an unusually large number of black spruce (Picea mariana) trees entered into a period of growth decline during the late-20th century (62% of sampled trees; n = 724 cross sections of age >70 years). This finding is coherent with evidence encoded in NDVI and simulated NPP data. Analyses of climatic and vegetation productivity relationships indicate that the influence of recent climatic changes in the studied forests has been via the enhanced moisture stress (i.e. greater water demands) and autotrophic respiration amplified by the declining sea ice concentration in Hudson Bay and Hudson Strait. The recent decline strongly contrasts with other growth reduction events that occurred during the 19th century, which were associated with cooling and high sea ice severity. The recent decline of vegetation productivity is the first one to occur under circumstances related to excess heat in a 300-year period, and further culminates with an intensifying wildfire regime in the region. Our results concur with observations from other forest ecosystems about intensifying temperature-driven drought stress and tree mortality with ongoing climatic changes.

Structural differences and functional similarities between two sugar maple (Acer saccharum) stands.

The spatially inexplicit or functional multilayer models used to predict canopy transpiration or photosynthesis are based on the assumption that closed stands show less functional variability than structural variability, because foliage tends to arrange itself in space to optimize the capture of light. To validate this assumption, we compared the structural and functional properties, and the measured and modeled transpiration fluxes of two sugar maple (Acer saccharum Marsh.) stands of comparable leaf mass but differing in height and diameter distributions. One stand was characterized by a well-developed single-layer canopy, whereas the other stand had a multilayered canopy and a stem diameter distribution of the classical inverse-J shape. Stand differences in height and diameter distribution, and canopy gap fraction, were highly significant. There were minor but significant differences in leaf mass and leaf mass per unit leaf area (LMA) distributions. We found no differences in tree-level relationships between basal area and either transpiration flux or sapwood area. We compared measurements of stand transpiration with transpiration estimates obtained from a multilayer gas exchange model, in which only the nonspatial inputs, leaf area index and LMA frequency distribution described stand structure. For both stands, modeled values of daily transpiration closely followed measured values (r(2) = 0.94). These results support use of the nonspatially explicit approach to estimating canopy gas exchange, especially if the intent is to scale-up to larger portions of the landscape.

Explaining geographic gradients in winter selection of landscapes by boreal caribou with implications under global changes in Eastern Canada.

Many animal species exhibit broad-scale latitudinal or longitudinal gradients in their response to biotic and abiotic components of their habitat. Although knowing the underlying mechanism of these patterns can be critical to the development of sound measures for the preservation or recovery of endangered species, few studies have yet identified which processes drive the existence of geographical gradients in habitat selection. Using extensive spatial data of broad latitudinal and longitudinal extent, we tested three hypotheses that could explain the presence of geographical gradients in landscape selection of the endangered boreal woodland caribou (Rangifer tarandus caribou) during winter in Eastern Canadian boreal forests: 1) climate-driven selection, which postulates that geographic gradients are surrogates for climatic gradients; 2) road-driven selection, which proposes that boreal caribou adjust their selection for certain habitat classes as a function of proximity to roads; and 3) an additive effect of both roads and climate. Our data strongly supported road-driven selection over climate influences. Thus, direct human alteration of landscapes drives boreal caribou distribution and should likely remain so until the climate changes sufficiently from present conditions. Boreal caribou avoided logged areas two-fold more strongly than burnt areas. Limiting the spread of road networks and accounting for the uneven impact of logging compared to wildfire should therefore be integral parts of any habitat management plan and conservation measures within the range of the endangered boreal caribou. The use of hierarchical spatial models allowed us to explore the distribution of spatially-structured errors in our models, which in turn provided valuable insights for generating alternative hypotheses about processes responsible for boreal caribou distribution.

Modeling the influence of temperature on monthly gross primary productivity of sugar maple stands.

A bottom-up and a top-down model were used to estimate the effect of temperature on monthly gross primary productivity (GPP) of sugar maple (Acer saccharum Marsh.). The bottom-up model computed canopy photosynthesis at an hourly time step from detailed physiological sub-models of leaf photosynthesis and stomatal conductance. Leaf mass per area was used as a covariable to integrate photosynthesis through the canopy. The top-down model used a radiation-use efficiency coefficient to relate canopy gross photosynthesis to absorbed photosynthetically active radiation at a monthly time step. The parameters of the top-down model were estimated from simulations with the bottom-up model. Forty single-year simulations were made using records of daily maximum and minimum temperatures from weather stations selected within the natural range of sugar maple in the province of Québec, Canada. Leaf area index was randomly varied between 4 and 10. Within a broad range of values, temperature had a minor effect on predicted monthly canopy-level GPP and its contribution to explaining the variability of GPP was low, both through its direct effect on photosynthetic processes (1.1%), and indirectly through the effect of relative humidity on stomatal conductance (4.0%). This result was unchanged when key parameters relating photosynthesis to temperature and stomatal conductance to atmospheric humidity were changed in the bottom-up model. An increase in time step from hourly to monthly resulted in a downward shift in the optimum temperature range for photosynthesis, from 30 degrees C for a leaf at saturating irradiance to 22 degrees C for the canopy at a monthly time scale.

Canopy photosynthesis of sugar maple (Acer saccharum): comparing big-leaf and multilayer extrapolations of leaf-level measurements.

A comparison is made between a big-leaf model (i.e., without details of the canopy profile) and two multilayer models (i.e., with details of the canopy profile) to estimate daily canopy photosynthesis of a sugar maple (Acer saccharum Marsh.) stand. The first multilayer model uses the distribution of leaf area by leaf mass per unit area (LMA) classes, the observed relationships between the parameters of a photosynthesis-irradiance curve and LMA, and the relationship between relative irradiance and LMA to estimate canopy photosynthesis. When compared with this model, the big-leaf model underestimates daily canopy photosynthesis by 26% because of an assumed proportionality between photosynthetic capacity and relative irradiance, a proportionality that is inconsistent with our data. The bias induced by this assumption is reduced when the big-leaf model is compared with the second multilayer model which, in addition to the assumptions made for the first multilayer model, accounts for the sunlit and shaded fractions of leaf area. The residual bias is almost eliminated when the big-leaf model is run using a weekly averaged irradiance. It is likely, however, that this is the result of a compensating bias that, in this particular case, compensates for the initial bias introduced by the proportionality assumption. It is also shown that canopy photosynthesis can be represented by spatially inexplicit multilayer models that use leaf mass per area as a covariable to describe leaf characteristics and environment. Such models represent an interesting alternative to the biased big-leaf approach.