Short- and long-term efficacy of forest thinning to mitigate drought impacts in mountain forests in the European Alps.

In many regions of the world, drought is projected to increase under climate change, with potential negative consequences for forests and their ecosystem services (ES). Forest thinning has been proposed as a method for at least temporarily mitigating drought impacts, but its general applicability and longer-term impacts are unclear. We use a process-based forest model to upscale experimental data for evaluating the impacts of forest thinning in a drought-susceptible valley in the interior of the European Alps, with the specific aim of assessing (1) when and where thinning may be most effective and (2) the longer-term implications for forest dynamics. Simulations indicate that forests will be impacted by climate-induced increases in drought across a broad elevation range. At lower elevations, where drought is currently prevalent, thinning is projected to temporarily reduce tree mortality, but to have minor impacts on forest dynamics in the longer term. Thinning may be particularly useful at intermediate and higher elevations as a means of temporarily reducing mortality in drought-sensitive species such as Norway spruce and larch, which currently dominate these elevations. However, in the longer term, even intense thinning will likely not be sufficient to prevent a climate change induced dieback of these species, which is projected to occur under even moderate climate change. Thinning is also projected to have the largest impact on long-term forest dynamics at intermediate elevations, with the magnitude of the impact depending on the timing and intensity of thinning. More intense thinning that is done later is projected to more strongly promote a transition to more drought-tolerant species. We conclude that thinning is a viable option for temporarily reducing the negative drought impacts on forests, but that efficient implementation of thinning should be contingent on a site-specific evaluation of the near term risk of significant drought, and how thinning will impact the rate and direction of climate driven forest conversion.

Evaluating the relative impact of climate and economic changes on forest and agricultural ecosystem services in mountain regions.

Provisioning of ecosystem services (ES) in mountainous regions is predicted to be influenced by i) the direct biophysical impacts of climate change, ii) climate mediated land use change, and iii) socioeconomic driven changes in land use. The relative importance and the spatial distribution of these factors on forest and agricultural derived ES, however, is unclear, making the implementation of ES management schemes difficult. Using an integrated economic-ecological modeling framework, we evaluated the impact of these driving forces on the provision of forest and agricultural ES in a mountain region of southern Switzerland. Results imply that forest ES will be strongly influenced by the direct impact of climate change, but that changes in land use will have a comparatively small impact. The simulation of direct impacts of climate change affects forest ES at all elevations, while land use changes can only be found at high elevations. In contrast, changes to agricultural ES were found to be primarily due to shifts in economic conditions that alter land use and land management. The direct influence of climate change on agriculture is only predicted to be substantial at high elevations, while socioeconomic driven shifts in land use are projected to affect agricultural ES at all elevations. Our simulation results suggest that policy schemes designed to mitigate the negative impact of climate change on forests should focus on suitable adaptive management plans, accelerating adaptation processes for currently forested areas. To maintain provision of agricultural ES policy needs to focus on economic conditions rather than on supporting adaptation to new climate.

Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.

Adaptive management for competing forest goods and services under climate change.

Developing adaptive forest management strategies is essential to maintain the provisioning of forest goods and services (FGS) under future climate change. We assessed how climate change and forest management affect forest development and FGS for a diverse case-study landscape in Central Europe. Using a process-based forest model (LandClim) we simulated forest dynamics and FGS under a range of climate change and management scenarios in the Black Forest, Germany, which is shaped by various management practices. We focused on the interdependencies between timber production and forest diversity, the most valued FGS in this region. We found that the conversion to more drought-adapted forest types is required to prevent climate change-induced forest dieback and that this conversion must be the target of any adaptive management, especially in areas where monocultures of drought-sensitive Norway spruce (Picea abies) were promoted in the past. Forest conversion takes up to 120 years, however, with past and future adaptive management being the key drivers of timber and forest diversity provision. The conversion of drought-sensitive conifer monocultures maintains timber production in the short-term and enhances a range of forest diversity indices. Using uneven-aged forest management that targets a drought-adapted, diverse, and resilient species mixture, high species diversity can be combined with timber production in the long term. Yet, the promotion of mature-stand attributes requires management restrictions. Selecting future adaptive management options thus implies the consideration of trade-offs between forest resource use and environmental objectives, but also the exploitation of synergies between FGS that occur during forest conversion. Lastly, the large impact of past management practices on the spatial heterogeneity of forest dynamics underpins the need to assess FGS provisioning at the landscape scale.

Genetic population structure of sympatric and allopatric populations of Baltic ciscoes (Coregonus albula complex, Teleostei, Coregonidae).

BACKGROUND: Teleost fishes of the Coregonidae are good model systems for studying postglacial evolution, adaptive radiation and ecological speciation. Of particular interest is whether the repeated occurrence of sympatric species pairs results from in-situ divergence from a single lineage or from multiple invasions of one or more different lineages. Here, we analysed the genetic structure of Baltic ciscoes (Coregonus albula complex), examining 271 individuals from 8 lakes in northern Germany using 1244 polymorphic AFLP loci. Six lakes had only one population of C. albula while the remaining two lakes had C. albula as well as a sympatric species (C. lucinensis or C. fontanae). RESULTS: AFLP demonstrated a significant population structure (Bayesian thetaB = 0.22). Lower differentiation between allopatric (thetaB = 0.028) than sympatric (0.063-0.083) populations contradicts the hypothesis of a sympatric origin of taxa, and there was little evidence for stocking or ongoing hybridization. Genome scans found only three loci that appeared to be under selection in both sympatric population pairs, suggesting a low probability of similar mechanisms of ecological segregation. However, removal of all non-neutral loci decreased the genetic distance between sympatric pairs, suggesting recent adaptive divergence at a few loci. Sympatric pairs in the two lakes were genetically distinct from the six other C. albula populations, suggesting introgression from another lineage may have influenced these two lakes. This was supported by an analysis of isolation-by-distance, where the drift-gene flow equilibrium observed among allopatric populations was disrupted when the sympatric pairs were included. CONCLUSIONS: While the population genetic data alone can not unambiguously uncover the mode of speciation, our data indicate that multiple lineages may be responsible for the complex patterns typically observed in Coregonus. Relative differences within and among lakes raises the possibility that multiple lineages may be present in northern Germany, thus understanding the postglacial evolution and speciation in the C. albula complex requires a large-scale phylogenetic analysis of several potential founder lineages.

Modeling abundance using N-mixture models: the importance of considering ecological mechanisms.

Predicting abundance across a species' distribution is useful for studies of ecology and biodiversity management. Modeling of survey data in relation to environmental variables can be a powerful method for extrapolating abundances across a species' distribution and, consequently, calculating total abundances and ultimately trends. Research in this area has demonstrated that models of abundance are often unstable and produce spurious estimates, and until recently our ability to remove detection error limited the development of accurate models. The N-mixture model accounts for detection and abundance simultaneously and has been a significant advance in abundance modeling. Case studies that have tested these new models have demonstrated success for some species, but doubt remains over the appropriateness of standard N-mixture models for many species. Here we develop the N-mixture model to accommodate zero-inflated data, a common occurrence in ecology, by employing zero-inflated count models. To our knowledge, this is the first application of this method to modeling count data. We use four variants of the N-mixture model (Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial) to model abundance, occupancy (zero-inflated models only) and detection probability of six birds in South Australia. We assess models by their statistical fit and the ecological realism of the parameter estimates. Specifically, we assess the statistical fit with AIC and assess the ecological realism by comparing the parameter estimates with expected values derived from literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the "best model" according to AIC, the negative binomial variants of the N-mixture often produce ecologically unrealistic parameter estimates. The zero-inflated Poisson variant is preferable to the negative binomial variants of the N-mixture, as it models an ecological mechanism rather than a statistical phenomenon and generates reasonable parameter estimates. Our results emphasize the need to include ecological reasoning when choosing appropriate models and highlight the dangers of modeling statistical properties of the data. We demonstrate that, to obtain ecologically realistic estimates of abundance, occupancy and detection probability, it is essential to understand the sources of variation in the data and then use this information to choose appropriate error distributions.

The role of landscape-dependent disturbance and dispersal in metapopulation persistence.

The fundamental processes that influence metapopulation dynamics (extinction and recolonization) will often depend on landscape structure. Disturbances that increase patch extinction rates will frequently be landscape dependent such that they are spatially aggregated and have an increased likelihood of occurring in some areas. Similarly, landscape structure can influence organism movement, producing asymmetric dispersal between patches. Using a stochastic, spatially explicit model, we examine how landscape-dependent correlations between dispersal and disturbance rates influence metapopulation dynamics. Habitat patches that are situated in areas where the likelihood of disturbance is low will experience lower extinction rates and will function as partial refuges. We discovered that the presence of partial refuges increases metapopulation viability and that the value of partial refuges was contingent on whether dispersal was also landscape dependent. Somewhat counterintuitively, metapopulation viability was reduced when individuals had a preponderance to disperse away from refuges and was highest when there was biased dispersal toward refuges. Our work demonstrates that landscape structure needs to be incorporated into metapopulation models when there is either empirical data or ecological rationale for extinction and/or dispersal rates being landscape dependent.

A 2 °C warmer world is not safe for ecosystem services in the European Alps.

Limiting the increase in global average temperature to 2 °C is the objective of international efforts aimed at avoiding dangerous climate impacts. However, the regional response of terrestrial ecosystems and the services that they provide under such a scenario are largely unknown. We focus on mountain forests in the European Alps and evaluate how a range of ecosystem services (ES) are projected to be impacted in a 2 °C warmer world, using four novel regional climate scenarios. We employ three complementary forest models to assess a wide range of ES in two climatically contrasting case study regions. Within each climate scenario we evaluate if and when ES will deviate beyond status quo boundaries that are based on current system variability. Our results suggest that the sensitivity of mountain forest ES to a 2 °C warmer world depends heavily on the current climatic conditions of a region, the strong elevation gradients within a region, and the specific ES in question. Our simulations project that large negative impacts will occur at low and intermediate elevations in initially warm-dry regions, where relatively small climatic shifts result in negative drought-related impacts on forest ES. In contrast, at higher elevations, and in regions that are initially cool-wet, forest ES will be comparatively resistant to a 2 °C warmer world. We also found considerable variation in the vulnerability of forest ES to climate change, with some services such as protection against rockfall and avalanches being sensitive to 2 °C global climate change, but other services such as carbon storage being reasonably resistant. Although our results indicate a heterogeneous response of mountain forest ES to climate change, the projected substantial reduction of some forest ES in dry regions suggests that a 2 °C increase in global mean temperature cannot be seen as a universally 'safe' boundary for the maintenance of mountain forest ES.

Catastrophic floods may pave the way for increased genetic diversity in endemic artesian spring snail populations.

The role of disturbance in the promotion of biological heterogeneity is widely recognised and occurs at a variety of ecological and evolutionary scales. However, within species, the impact of disturbances that decimate populations are neither predicted nor known to result in conditions that promote genetic diversity. Directly examining the population genetic consequences of catastrophic disturbances however, is rarely possible, as it requires both longitudinal genetic data sets and serendipitous timing. Our long-term study of the endemic aquatic invertebrates of the artesian spring ecosystem of arid central Australia has presented such an opportunity. Here we show a catastrophic flood event, which caused a near total population crash in an aquatic snail species (Fonscochlea accepta) endemic to this ecosystem, may have led to enhanced levels of within species genetic diversity. Analyses of individuals sampled and genotyped from the same springs sampled both pre (1988-1990) and post (1995, 2002-2006) a devastating flood event in 1992, revealed significantly higher allelic richness, reduced temporal population structuring and greater effective population sizes in nearly all post flood populations. Our results suggest that the response of individual species to disturbance and severe population bottlenecks is likely to be highly idiosyncratic and may depend on both their ecology (whether they are resilient or resistant to disturbance) and the stability of the environmental conditions (i.e. frequency and intensity of disturbances) in which they have evolved.