Lluís

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 to achieve systematically maximal cobenefits 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-makingrules 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 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.

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The Vulnerable (IUCN) whale shark spans warm and temperate waters around the globe. However, their present-day and possible future global distribution has never been predicted. Using 30 years (1980–2010) of whale shark observations recorded by tuna purse-seiners fishing in the Atlantic, Indian and Pacific Oceans, we applied generalized linear mixed-effects models to test the hypothesis that similar environmental covariates predict whale shark occurrence in all major ocean basins. We derived global predictors from satellite images for chlorophyll a and sea surface temperature, and bathymetric charts for depth, bottom slope and distance to shore. We randomly generated pseudo-absences within the area covered by the fisheries, and included fishing effort as an offset to account for potential sampling bias. We predicted sea surface temperatures for 2070 using an ensemble of five global circulation models under a no climate-policy reference scenario, and used these to predict changes in distribution. The full model (excluding standard deviation of sea surface temperature) had the highest relative statistical support (wAIC_c = 0.99) and explained ca. 60% of the deviance. Habitat suitability was mainly driven by spatial variation in bathymetry and sea surface temperature among oceans, although these effects differed slightly among oceans. Predicted changes in sea surface temperature resulted in a slight shift of suitable habitat towards the poles in both the Atlantic and Indian Oceans (ca. 5°N and 3–8°S, respectively) accompanied by an overall range contraction (2.5–7.4% and 1.1–6.3%, respectively). Predicted changes in the Pacific Ocean were small. Assuming that whale shark environmental requirements and human disturbances (i.e. no stabilization of greenhouse gas emissions) remain similar, we show that warming sea surface temperatures might promote a net retreat from current aggregation areas and an overall redistribution of the species.

Biological invasion is increasingly recognized as one of the greatest threats to biodiversity. Using ensemble forecasts from species distribution models to project future suitable areas of the 100 of the world's worst invasive species defined by the International Union for the Conservation of Nature, we show that both climate and land use changes will likely cause drastic species range shifts. Looking at potential spatial aggregation of invasive species, we identify three future hotspots of invasion in Europe, northeastern North America, and Oceania. We also emphasize that some regions could lose a significant number of invasive alien species, creating opportunities for ecosystem restoration. From the list of 100, scenarios of potential range distributions show a consistent shrinking for invasive amphibians and birds, while for aquatic and terrestrial invertebrates distributions are projected to substantially increase in most cases. Given the harmful impacts these invasive species currently have on ecosystems, these species will likely dramatically influence the future of biodiversity.

Dispersal is fundamental in determining biodiversity responses to rapid climate change, but recently acquired ecological and evolutionary knowledge is seldom accounted for in either predictive methods or conservation planning. We emphasise the accumulating evidence for direct and indirect impacts of climate change on dispersal. Additionally, evolutionary theory predicts increases in dispersal at expanding range margins, and this has been observed in a number of species. This multitude of ecological and evolutionary processes is likely to lead to complex responses of dispersal to climate change. As a result, improvement of models of species’ range changes will require greater realism in the representation of dispersal. Placing dispersal at the heart of our thinking will facilitate development of conservation strategies that are resilient to climate change, including landscape management and assisted colonisation.

Synthesis

This article seeks synthesis across the fields of dispersal ecology and evolution, species distribution modelling and conservation biology. Increasing effort focuses on understanding how dispersal influences species' responses to climate change. Importantly, though perhaps not broadly widely-recognised, species' dispersal characteristics are themselves likely to alter during rapid climate change. We compile evidence for direct and indirect influences that climate change may have on dispersal, some ecological and others evolutionary. We emphasise the need for predictive modelling to account for this dispersal realism and highlight the need for conservation to make better use of our existing knowledge related to dispersal.

European Wrynecks Jynx torquilla torquilla have generally been considered to be long-distance Palaearctic–African migrants that spend the non-breeding season in Sahelian Africa, where they have been reported regularly. Results from tracking individual birds showed that Wrynecks from two Central European populations migrated only relatively short distances to the Iberian Peninsula and northwestern Africa (c. 1500 km and 3000 km, respectively), compared with a minimum distance of about 4500 km to Sahelian Africa. Additionally, differences in wing lengths of populations from Central and Northern Europe support the idea of leap-frog migration, populations from Northern Europe being long-distance migrants with a non-breeding distribution in Sahelian Africa.

1. Though co-occurrence of invasive plant species is common, few studies have compared the community and ecosystem impacts of invaders when they occur alone and when they co-occur. Prioritization of invasive species management efforts requires sufficient knowledge of impacts – both among individual invasive species and among different sets of co-occurring invaders – to target resources towards management of sites expected to undergo the largest change.
2. Here, we observed differences in above- and below-ground impacts of two invasive woody shrubs, Lonicera maackii and Ligustrum sinense, among plots containing both shrubs (mixed), each species singly or lacking both species (control).
3. We found additive and non-additive effects of these co-occurring invasives on plant communities and soil processes. Mixed plots contained two times more subdominant invasive plant species than L. maackii or L. sinense plots. Compared to control plots, mixed plots had three times the potential activity of β-glucosidase, a carbon-degrading extracellular soil enzyme. L. maackii plots and mixed plots had less acidic soils, while L. sinense plots had higher soil moisture than control plot soils. Differences in soil properties among plots explained plant- and ground-dwelling arthropod community composition as well as the potential microbial function in soils.
4. Synthesis and applications. Our study highlights the importance of explicitly studying the impacts of co-occurring invasive plant species singly and together. Though Lonicera maackii and Ligustrum sinense have similar effects on ecosystem structure and function when growing alone, our data show that two functionally similar invaders can have non-additive impacts on ecosystems. These results suggest that sites with both species should be prioritized for invasive plant management over sites containing only one of these species. Furthermore, this study provides a valuable template for future studies exploring how and when invasion by co-occurring species alters above- and below-ground function in ecosystems with different traits.

1. Our understanding of a biological population can be greatly enhanced by modelling their distribution in space and as a function of environmental covariates. Such models can be used to investigate the relationships between distribution and environmental covariates as well as reliably estimate abundances and create maps of animal/plant distribution.
2. Density surface models consist of a spatial model of the abundance of a biological population which has been corrected for uncertain detection via distance sampling methods.
3. We review recent developments in the field and consider the likely directions of future research before focussing on a popular approach based on generalized additive models. In particular, we consider spatial modelling techniques that may be advantageous to applied ecologists such as quantification of uncertainty in a two-stage model and smoothing in areas with complex boundaries.
4. The methods discussed are available in an R package developed by the authors (dsm) and are largely implemented in the popular Windows software Distance.

1. The analysis of large heterogeneous data sets of avian point-count surveys compiled across studies is hindered by a lack of analytical approaches that can deal with detectability and variation in survey protocols.
2. We reformulated removal models of avian singing rates and distance sampling models of the effective detection radius (EDR) to control for the effects of survey protocol and temporal and environmental covariates on detection probabilities.
3. We estimated singing rates and EDR for 75 boreal forest songbird species and found that survey protocol, especially point-count radius, explained most of the variation in detectability. However, environmental and temporal covariates (date, time, vegetation) affected singing rates and EDR for 73% and 59% of species, respectively.
4. Unadjusted survey counts increased by an average of 201% from a 5-min, 50-m radius survey to a 10-min, 100-m radius survey (n = 75 species). This variability was decreased to 8·5% using detection probabilities estimated from a combination of removal and distance sampling models.
5. Our modelling approach reduced computation when fitting complex models to large data sets and can be used with a wide range of statistical techniques for inference and prediction of avian densities.

1. Fire and herbivory are the main disturbances shaping the structure of savannas. In these ecosystems, the key strategies by which woody plants escape fire are either early height growth (the lanky strategy) or early bark growth (the corky strategy). We hypothesize that the dominance of each strategy in different savannas depends on the prevailing disturbance regimes. Given the importance of herbivory in afrotropical savanna, we expect woody plants in these savannas to be taller and have thinner barks (the lanky strategy) than plants in neotropical savanna where fire tends to be more intense (the corky strategy).
2. We compiled data on bark thickness and stem height in relation to stem diameter for afrotropical and neotropical savanna woody species and tested for differences in the allometric relationship between these two savannas with a general linear mixed model (GLMM).
3. Fire intensities were higher in neotropical than in afrotropical savannas. Afrotropical savanna plants were taller and had thinner barks for a given diameter than neotropical savanna plants – supporting our hypothesis that because of the contrasting disturbance regimes, the lanky strategy is more adaptive in afrotropical savannas, whereas the corky strategy is more adaptive in neotropical savannas.
4. Synthesis. While the lanky strategy is more associated with heavily browsed and fuel-controlled savannas, the corky strategy is associated with lightly browsed savannas that experience more intense fires. Because the relative role of disturbances varies across the globe, we suggest that the height-bark-diameter scheme is a powerful framework for understanding the ecology of many savannas.

In savanna ecosystems there are two main strategies to scape fire. The lanky strategy (early alocation to height) is more associated with heavily-browsed and fuel-controlled savannas, while the corky strategy (early allocation to a thick bark) is associated with lightly-browsed savannas that experience more intense fires. Because the relative role of disturbances varies across the globe, we suggest that the height-bark-diameter scheme is a powerful framework for understanding the ecology of many savannas.

The Europe-wide decline in the populations and diversity of farmland birds has not been stopped despite dedicated conservation efforts such as agri-environment schemes (AES). The main reason for the lack of success of AES is considered to be their low ecological quality and insufficient area. Understanding the effects of different management strategies on the ecological quality of AES is therefore important. Here, we investigate the relationship between breeding bird density and species richness and the age of sown field margins, a widely used type of AES, in southwestern Switzerland. Territories of breeding birds were mapped on 67 field margins between 2004 and 2011. Territory densities (for eight species) and species richness were analysed in relation to age of the field margin. A general negative correlation between size of the field margin and territory density indicated that territory density was higher when the birds could forage in adjacent cultivated land. Territory densities and species richness increased up to an age of 4–6 years after sowing, depending on the species, and declined thereafter. The results suggest that the co-occurrence of newly sown margins and margins over 3 years old will have a positive effect on breeding bird densities and species diversity.

By altering its flight altitude, a bird can change the atmospheric conditions it experiences during migration. Although many factors may influence a bird's choice of altitude, wind is generally accepted as being the most influential. However, the influence of wind is not clearly understood, particularly outside the trade-wind zone, and other factors may play a role. We used operational weather radar to measure the flight altitudes of nocturnally migrating birds during spring and autumn in the Netherlands. We first assessed whether the nocturnal altitudinal distribution of proportional bird density could be explained by the vertical distribution of wind support using three different methods. We then used generalized additive models to assess which atmospheric variables, in addition to altitude, best explained variability in proportional bird density per altitudinal layer each night. Migrants generally remained at low altitudes, and flight altitude explained 52 and 73% of the observed variability in proportional bird density in spring and autumn, respectively. Overall, there were weak correlations between altitudinal distributions of wind support and proportional bird density. Improving tailwind support with height increased the probability of birds climbing to higher altitude, but when birds did fly higher than normal, they generally concentrated around the lowest altitude with acceptable wind conditions. The generalized additive model analysis also indicated an influence of temperature on flight altitudes, suggesting that birds avoided colder layers. These findings suggested that birds increased flight altitudes to seek out more supportive winds when wind conditions near the surface were prohibitive. Thus, birds did not select flight altitudes only to optimize wind support. Rather, they preferred to fly at low altitudes unless wind conditions there were unsupportive of migration. Overall, flight altitudes of birds in relation to environmental conditions appear to reflect a balance between different adaptive pressures.

1. Estimating abundance from mark–recapture data is challenging when capture probabilities vary among individuals.
2. Initial solutions to this problem were based on fitting conditional likelihoods and estimating abundance as a derived parameter. More recently, Bayesian methods using full likelihoods have been implemented via reversible jump Markov chain Monte Carlo sampling (RJMCMC) or data augmentation (DA). The latter approach is easily implemented in available software and has been applied to fit models that allow for heterogeneity in both open and closed populations. However, both RJMCMC and DA may be inefficient when modelling large populations.
3. We describe an alternative approach using Monte Carlo (MC) integration to approximate the posterior density within a Markov chain Monte Carlo (MCMC) sampling scheme. We show how this Monte Carlo within MCMC (MCWM) approach may be used to fit a simple, closed population model including a single individual covariate and present results from a simulation study comparing RJMCMC, DA and MCWM. We found that MCWM can provide accurate inference about population size and can be more efficient than both RJMCMC and DA. The efficiency of MCWM can also be improved by using advanced MC methods like antithetic sampling.
4. Finally, we apply MCWM to estimate the abundance of meadow voles (Microtus pennsylvanicus) at the Patuxent Wildlife Research Center in 1982 allowing for capture probabilities to vary as a function body mass.