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International audience; Key messageWe present a methodological framework that both scientists and supply chain actors can mobilise to organise information at different scales of observation, and further make informed decisions regarding the supply and extraction of bio-molecules from forest biomass. We demonstrate its usefulness for extracting bio-molecules contained in silver fir growing in France.ContextNumerous bio-active molecules can be extracted from trees at an industrial scale. Supply chain actors play a central role in this emerging bio-economy. However, they do not have enough information and tools to make informed decisions with respect to species, growing locations, or identities of potential suppliers of relevant wood biomass.AimsWe explore and demonstrate an information chain and methodological framework that can help make three critical decisions regarding the selection of (1) the species containing the desired bio-molecules, (2) the locations where the resource is collected, and (3) the supply chain partners and types of industrial wood by-products necessary to obtain sufficient biomass for industrial extraction.MethodsThe methodological framework provides detailed guidelines and references to select the right combination of sampling protocol, allometric models, chemical analyses, GIS tools, and forest growth and supply chain models in order to produce information for the three decision steps within various regional contexts.ResultsWe apply the framework within the context of supply chain actors who are interested in estimating the quantity and diversity of bio-molecules contained in silver fir (Abies alba Mill.) growing in the Grand Est region of France. We show how conflicting environmental, legal and economic constraints can affect the results. We discuss future challenges that need to be tackled to improve the methodological framework.ConclusionThis study represents a highly detailed overview of the potential bio-molecules contained in a tree species, from its natural habitat or plantation to the end of the regional supply chain. It also represents a step towards the development of a generic knowledge infrastructure and methodology that is necessary to solve various decision-making problems regarding the industrial supply and extraction of high-value bio-molecules.

International audience; Forest ecosystems are typical examples of socio-ecological systems. However, in terms of modelling, the social aspect has been given far less attention than the ecological aspect. In this study, we modelled the impact of eco- nomic and social factors on the occurrence of harvesting. This harvest model was then integrated into an individual- based model of forest growth designed for large-area forec asts. The resulting s ocio-ecological model was then used to produce volume predictions for two regions of France. Among the economic factors, the annual stumpage prices in interaction with the species proved to be a signi fi cant predictor of harvest occurrence. Simulating different stum- page price evolutions made it possible to predict supply curves for the two regions. Projections until 2060 showed that increases in stumpage prices will be detrimental to st anding volumes in both regions. Integrating the demand for wood products into such socio-ecological models in forestry would be a major improvement.

International audience; Various combinations of data and expert opinion have been used to select species for indices of bird trends. Commonly these indices break species into groups based on their habitat preference such as woodland specialist, farmland specialist and generalist birds. It is unclear what influence differences in how species are allocated to these groups might have on trends in these indices. There is uncertainty surrounding reported trends in these bird groups with studies variously showing declines or increases in prevalence. This is usually attributed to ecological factors but if studies classify bird groups differently this variation may be due to inconsistency in classification. Disagreement about whether these bird groups are stable, increasing or declining has the potential to obscure important changes in bird prevalence and impede appropriate, timely conservation. We examined how consistently European and Australian researchers classified woodland, farmland and generalist birds, and whether this affected the trends in indices of these groups. Researchers from both regions classified species differently, and the population trends seen in these groups were strongly affected by differences in classification. While all classifications we studied suggest that populations are consistently declining for Australian woodland and European farmland birds and increasing for European woodland birds. European generalist and Australian farmland and generalist birds may be seen as increasing or decreasing in prevalence depending on classification. Our results question the current practice of idiosyncratically classifying indicators in scientific research and conservation. Current practice is making it more difficult to infer whether, when and how to preserve bird groups in Europe and Australia, potentially leading to sub-optimal biodiversity outcomes. We offer suggestions for building consensus on how to classify these bird groups in order to provide more reliable evidence to support conservation decisions.

Determining the best management actions is challenging when critical information is missing. However, urgency and limited resources require that decisions must be made despite this uncertainty. The best practice method for managing uncertain systems is adaptive management, or learning by doing. Adaptive management problems can be solved optimally using decision-theoretic methods; the challenge for these methods is to represent current and future knowledge using easy-to-optimize representations. Significant methodological advances have been made since the seminal adaptive management work was published in the 1980s, but despite recent advances, guidance for implementing these approaches has been piecemeal and study-specific. There is a need to collate and summarize new work. Here, we classify methods and update the literature with the latest optimal or near-optimal approaches for solving adaptive management problems. We review three mathematical concepts required to solve adaptive management problems: Markov decision processes, sufficient statistics, and Bayes’ theorem. We provide a decision tree to determine whether adaptive management is appropriate and then group adaptive management approaches based on whether they learn only from the past (passive) or anticipate future learning (active). We discuss the assumptions made when using existing models and provide solution algorithms for each approach. Finally, we propose new areas of development that could inspire future research. For a long time, limited by the efficiency of the solution methods, recent techniques to efficiently solve partially observable decision problems now allow us to solve more realistic adaptive management problems such as imperfect detection and non-stationarity in systems.

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species.

Software applications for life cycle assessment of greenhouse gas (GHG) emissions have become popular over the last decade. Their objective is to provide insight into how GHG emissions could be reduced in the sectors defined by the UNFCCC. However, boundaries between these sectors are not closed and current tools are not designed to represent this complexity or to assess the numerous sources of uncertainties. In this paper, we present CAT v1.0, software developed for managed forests in the LULUCF sector, but whose emission life cycle is linked to that of other sectors. While the structure of the software follows IPCC Guidelines, it also contains additional features such as an embedded Monte-Carlo error propagation technique and a user-friendly flux manager that allows for complex cradle-to-grave representations of the wood transformation industry. The flexibility of the software is illustrated through two case studies in northeastern France.

Weather is a general stochastic influence on the life history of weeds. In contrast, anthropogenic disturbance (e.g. land use) is an important deterministic influence on weed demography. Our aim with this study was to investigate the relative contributions of land use and weather on the demography of Lantana camara (lantana), a weed of agricultural and natural habitats, based on the intensive monitoring of lantana populations under three land uses (viz. farm[pasture], and burnt and grazed forests) in subtropical Australia. Lantana populations were growing vigorously across all land uses (asymptotic population growth rate, λ > 3). Examination of historical demography using retrospective perturbation analyses showed that weather was a strong influence on lantana demography with the transition from an El Nino (2008–09) to a La Nina (2009–10) year having a strong positive effect on population growth rate. This effect was most marked at the grazed site, and to a lesser extent at the burnt site, with seedling-to-juvenile and juvenile-to-adult transitions contributing most to these effects. This is likely the result of burning and grazing having eliminated/reduced interspecific competition at these sites. Prospective perturbation analyses revealed that λ was most sensitive to proportionate changes in growth transitions, followed by fecundity and survival transitions. Examination of context-specific patterns in elasticity revealed that growth and fecundity transitions are likely to be the more critical vital rates to reduce λ in wet years at the burnt and grazed forest sites, compared to the farm/pasture site. Management of lantana may need to limit the transition of juveniles into the adult stages, especially in sites where lantana is free from competition (e.g. in the presence of fire or grazing), and this particularly needs to be achieved in wet years. Collectively, these results shed light on aspects of spatial and temporal variation in the demography of lantana, and offer insights on its context-specific management.

Threats to migratory animals can occur at multiple periods of the annual cycle that are separated by thousands of kilometres and span international borders. Populations of the iconic monarch butterfly (Danaus plexippus) of eastern North America have declined over the last 21 years. Three hypotheses have been posed to explain the decline: habitat loss on the overwintering grounds in Mexico, habitat loss on the breeding grounds in the United States and Canada, and extreme weather events. Our objectives were to assess population viability, determine which life stage, season and geographical region are contributing the most to population dynamics and test the three hypotheses that explain the observed population decline. We developed a spatially structured, stochastic and density-dependent periodic projection matrix model that integrates patterns of migratory connectivity and demographic vital rates across the annual cycle. We used perturbation analysis to determine the sensitivity of population abundance to changes in vital rate among life stages, seasons and geographical regions. Next, we compared the singular effects of each threat to the full model where all factors operate concurrently. Finally, we generated predictions to assess the risk of host plant loss as a result of genetically modified crops on current and future monarch butterfly population size and extinction probability. Our year-round population model predicted population declines of 14% and a quasi-extinction probability (1000 individuals)5% within a century. Monarch abundance was more than four times more sensitive to perturbations of vital rates on the breeding grounds than on the wintering grounds. Simulations that considered only forest loss or climate change in Mexico predicted higher population sizes compared to milkweed declines on the breeding grounds. Our model predictions also suggest that mitigating the negative effects of genetically modified crops results in higher population size and lower extinction risk. Recent population declines stem from reduction in milkweed host plants in the United States that arise from increasing adoption of genetically modified crops and land-use change, not from climate change or degradation of forest habitats in Mexico. Therefore, reducing the negative effects of host plant loss on the breeding grounds is the top conservation priority to slow or halt future population declines of monarch butterflies in North America.

Regrowing forests on cleared land is a key strategy to achieve both biodiversity conservation and climate change mitigation globally. Maximizing these co-benefits, however, remains theoretically and technically challenging because of the complex relationship between carbon sequestration and biodiversity in forests, the strong influence of climate variability and landscape position on forest development, the large number of restoration strategies possible, and long time-frames needed to declare success. Through the synthesis of three decades of knowledge on forest dynamics and plant functional traits combined with decision science, we demonstrate that we cannot always maximize carbon sequestration by simply increasing the functional trait diversity of trees planted. The relationships between plant functional diversity, carbon sequestration rates above-ground and in the soil are dependent on climate and landscape positions. We show how to manage ‘identities’ and ‘complementarities’ between plant functional traits in order to achieve systematically maximal co-benefits in various climate and landscape contexts. We provide examples of optimal planting and thinning rules that satisfy this ecological strategy and guide the restoration of forests that are rich in both carbon and plant functional diversity. Our framework provides the first mechanistic approach for generating decision-making rules that can be used to manage forests for multiple objectives, and supports joined carbon credit and biodiversity conservation initiatives, such as Reducing Emissions from Deforestation and forest Degradation REDD+. The decision framework can also be linked to species distribution models and socio-economic models in order to find restoration solutions that maximize simultaneously biodiversity, carbon stocks and other ecosystem services across landscapes. Our study provides the foundation for developing and testing cost-effective and adaptable forest management rules to achieve biodiversity, carbon sequestration and other socio-economic co-benefits under global change.

Summary 1. Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. 2. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. 3. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. 4. Synthesis and applications. In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Explaining variation in population growth rates is fundamental to predicting population dynamics and population responses to environmental change. In this study, we used matrix population models, which link birth, growth and survival to population growth rate, to examine how and why population growth rates vary within and among 50 terrestrial plant species. Population growth rates were more similar within species than among species; with phylogeny having a minimal influence on among-species variation. Most population growth rates decreased over the observation period and were negatively autocorrelated between years; that is, higher than average population growth rates tended to be followed by lower than average population growth rates. Population growth rates varied more through time than space; this temporal variation was due mostly to variation in post-seedling survival and for a subset of species was partly explained by response to environmental factors, such as fire and herbivory. Stochastic population growth rates departed from mean matrix population growth rate for temporally autocorrelated environments. Our findings indicate that demographic data and models of closely related plant species cannot necessarily be used to make recommendations for conservation or control, and that post-seedling survival and the sequence of environmental conditions are critical for determining plant population growth rate.

Summary 1. A primary goal of evolutionary ecology is to understand factors selecting for the diversity of life histories. Life-history components, such as time-to-reproduction, adult survivorship and fecundity, might differ among species because of variation in direct and indirect benefits of these life histories in different environments or might have lower-than-expected variability because of phylogenetic constraints. Here, we present a phylogenetic examination of demography and life histories using a data base of 204 terrestrial plant species. 2. Overall, statistical models without phylogeny were preferred to models with phylogeny for vital rates and elasticities, suggesting that they lacked phylogenetic signal and are evolutionarily labile. However, the effect of phylogeny was significant in models including sensitivities, suggesting that sensitivities exhibit greater phylogenetic signal than vital rates or elasticities. 3. Species with a greater age at first reproduction had lower fecundity, consistent with a cost of delayed reproduction, but only in some habitats (e.g. grassland). We found no evidence for an indirect benefit of delayed reproduction via a decrease in variation in fecundity with age to first reproduction. 4. The greater sensitivity and lower variation in survival than in fecundity was consistent with buffering of more important vital rates, as others have also found. This suggests that studies of life-history evolution should include survival, rather than only fecundity, for the majority of species. 5. Synthesis. Demographic matrix models can provide informative tests of life-history theory because of their shared construction and outputs and their widespread use among plant ecologists. Our comparative analysis suggested that there is a cost of delayed reproduction and that more important vital rates exhibit lower variability. The absolute importance of vital rates to population growth rates (sensitivities) exhibited phylogenetic signal, suggesting that a thorough understanding of life-history evolution might require an understanding of the importance of vital rates, not just their means, and the role of phylogenetic history.

International audience; Over the last decades, agricultural intensification has caused a dramatic reduction of grassy habitats. This habitat loss has had a strong negative effect on many meadow-living insect populations, including butterflies. As a part of the cross-compliance measures of the Common Agricultural Policy of the European Union, subsidies for creation and maintenance of grassy field margins (GFM) have been launched. Among other environmental issues, they may serve as corridors for movement of various meadow-living species between individual meadows. Their role as corridors has, however, not yet been demonstrated at the landscape scale and their characteristics that most significantly increase landscape connectivity are unknown. Empirical data for such studies are missing, as the GFM subsidies were launched only 3 years ago. One possibility to get some predictions of their outcomes is provided by simulation models. Here we present our simulation results, using an extension of the model developed by Kindlmann et al. (2004) for the Meadow Brown butterfly, Maniola jurtina. The extension includes the probability to cross a boundary (Conradt and Roper, 2006) that negatively influences dispersal rates but increases sensitivity to the corridor effect. Our simulations show that GFMs increase the dispersal rates between habitat patches and we predict the optimal combinations of width and number of GFMs in the landscape. This way we provide a decision-making tool for increasing landscape connectivity for M. jurtina and similar species. Although our simulations are based on a particular species, they may be generalized because this species shows dispersal rates that are typical of butterfly metapopulations (Conradt et al., 2000), and a potentially widespread dispersal kernel (i.e. “foray search”) that has been reported in a wide variety of species (see Conradt et al., 2003 for a review).

Changed fire regimes have led to declines of fire-regime-adapted species and loss of biodiversity globally. Fire affects population processes of growth, reproduction, and dispersal in different ways, but there is little guidance about the best fire regime(s) to maintain species population processes in fire-prone ecosystems. We use a process-based approach to determine the best range of fire intervals for keystone plant species in a highly modified Mediterranean ecosystem in southwestern Australia where current fire regimes vary. In highly fragmented areas, fires are few due to limited ignitions and active suppression of wildfire on private land, while in highly connected protected areas fires are frequent and extensive. Using matrix population models, we predict population growth of seven Banksia species under different environmental conditions and patch connectivity, and evaluate the sensitivity of species survival to different fire management strategies and burning intervals. We discover that contrasting, complementary patterns of species life-histories with time since fire result in no single best fire regime. All strategies result in the local patch extinction of at least one species. A small number of burning strategies secure complementary species sets depending on connectivity and post-fire growing conditions. A strategy of no fire always leads to fewer species persisting than prescribed fire or random wildfire, while too-frequent or too-rare burning regimes lead to the possible local extinction of all species. In low landscape connectivity, we find a smaller range of suitable fire intervals, and strategies of prescribed or random burning result in a lower number of species with positive growth rates after 100 years on average compared with burning high connectivity patches. Prescribed fire may reduce or increase extinction risk when applied in combination with wildfire depending on patch connectivity. Poor growing conditions result in a significantly reduced number of species exhibiting positive growth rates after 100 years of management. By exploring the consequences of managing fire, we are able to identify which species are likely to disappear under a given fire regime. Identifying the appropriate complementarity of fire intervals, and their species-specific as well as community-level consequences, is crucial to reduce local extinctions of species in fragmented fire-prone landscapes.

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one-sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost-effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost-effectiveness was relatively unaffected by including climate change into decision-making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.

To better understand the impact of habitat fragmentation on population dynamics at the landscape scale, we develop a model combining a spatially implicit landscape model, a multisite Leslie-type model and an implicit model of habitat fragmentation. The studied species (Abax parallelepipedus, Coleoptera: Carabidae) is a corridor forest insect sensitive to wood fragmentation. The population of A. parallelepipedus was divided into three stages and move in the landscape between four classes of elements: wood, lane bordered by two hedgerows, hedgerow and agricultural matrix. The landscape representation was supposed to be implicit and the four classes of elements were randomly distributed in space. The originality of this approach is that we fit the movement frequency between elements according to woodland forest fragmentation. When wood fragmentation increases, the movement process can be very frequent and the method of aggregation of variables allows us to simplify the analysis of the model. Outputs of the model include the asymptotic population growth rate, stable stage structure and asymptotic spatial distribution that allow comparison of the influence of different spatial scenarios of wood fragmentation on population dynamics. Our results indicate that a single large patch of wood is better than several small patches of wood for population viability, that hedgerows have negative effects on population viability but lanes border by two hedgerows have positive effects even if they are randomly distributed at the landscape scale. When wood fragmentation is important, hedgerows create a population drain in woods and individuals pass and die more frequently in agricultural matrix.

To better understand the role of habitat quality and boundaries on population dynamics at the landscape scale, we develop a model combining a spatially implicit approach, a spatial population Leslie-type model and an implicit model of habitat fragmentation. An original approach of elasticity permits to identify which types of element and boundary influence the most population viability according to the wood fragmentation degree. The studied species is a corridor forest insect sensitive to fragmentation ( Abax parallelepipedus, Coleoptera, Carabidae). We show that a single large patch of wood is better than several small patches for the population viability. To cite this article: J.-B. Pichancourt et al., C. R. Biologies 329 (2006).

Phenotypic plasticity has long been suspected to allow invasive species to expand their geographic range across large-scale environmental gradients. We tested this possibility in Australia using a continental scale survey of the invasive tree Parkinsonia aculeata (Fabaceae) in twenty-three sites distributed across four climate regions and three habitat types. Using tree-level responses, we detected a trade-off between seed mass and seed number across the moisture gradient. Individual trees plastically and reversibly produced many small seeds at dry sites or years, and few big seeds at wet sites and years. Bigger seeds were positively correlated with higher seed and seedling survival rates. The trade-off, the relation between seed mass, seed and seedling survival, and other fitness components of the plant life-cycle were integrated within a matrix population model. The model confirms that the plastic response resulted in average fitness benefits across the life-cycle. Plasticity resulted in average fitness being positively maintained at the wet and dry range margins where extinction risks would otherwise have been high (“Jack-of-all-Trades” strategy JT), and fitness being maximized at the species range centre where extinction risks were already low (“Master-of-Some” strategy MS). The resulting hybrid “Jack-and-Master” strategy (JM) broadened the geographic range and amplified average fitness in the range centre. Our study provides the first empirical evidence for a JM species. It also confirms mechanistically the importance of phenotypic plasticity in determining the size, the shape and the dynamic of a species distribution. The JM allows rapid and reversible phenotypic responses to new or changing moisture conditions at different scales, providing the species with definite advantages over genetic adaptation when invading diverse and variable environments. Furthermore, natural selection pressure acting on phenotypic plasticity is predicted to result in maintenance of the JT and strengthening of the MS, further enhancing the species invasiveness in its range centre.

Explaining variation in population growth rates is fundamental to predicting population dynamics and population responses to environmental change. In this study, we used matrix population models, which link birth, growth and survival to population growth rate, to examine how and why population growth rates vary within and among 50 terrestrial plant species. Population growth rates were more similar within species than among species; with phylogeny having a minimal influence on among-species variation. Most population growth rates decreased over the observation period and were negatively autocorrelated between years; that is, higher than average population growth rates tended to be followed by lower than average population growth rates. Population growth rates varied more through time than space; this temporal variation was due mostly to variation in post-seedling survival and for a subset of species was partly explained by response to environmental factors, such as fire and herbivory. Stochastic population growth rates departed from mean matrix population growth rate for temporally autocorrelated environments. Our findings indicate that demographic data and models of closely related plant species cannot necessarily be used to make recommendations for conservation or control, and that post-seedling survival and the sequence of environmental conditions are critical for determining plant population growth rate.