Historical and contemporary habitat use of sperm whales around the Galápagos Archipelago: Implications for conservation

1. Sperm whales have occupied the waters off the Galápagos Islands, Ecuador, for at least the past 200 years. During the 19^th century, they were the target of intensive whaling that severely depleted the population. In recent times, after commercial whaling ended, sperm whales in the region remain vulnerable to multiple threats, especially potential entanglement in fishing gear, which may hinder their ability to recover from the whaling era.
2. As a highly mobile, long-lived species, long-term analysis of the habitat use of sperm whales is necessary to establish effective conservation and management strategies. Here, contemporary (1985–2014) and historical (1830–1850) sperm whale habitat use off the Galápagos Islands was analysed and contrasted to the extent of the Galápagos Marine Reserve (GMR). Contemporary habitat use and its variability over time were modelled as a function of geographic, oceanographic, and topographic variables using generalized additive models.
3. The fine-scale habitat (<50 km) used by sperm whales was associated with topographic (i.e. depth and slope) and oceanographic characteristics (i.e. relative sea surface temperature and standard deviation of sea surface temperature), but these preferences varied over time.
4. While historical and contemporary data indicate that sperm whale habitat primarily occurred within the boundaries of the GMR, in recent years, whales were found up to 30.1% of the time outside the GMR, potentially overlapping with commercial fisheries operating in the area.
5. The dynamic nature of the relationship of this nomadic species with its habitat highlights the need of large-scale conservation efforts across the Eastern Tropical Pacific region, including the wide-scale enforcement of regulations requiring the use of Automatic Identification System in fishing vessels, the promotion of on-board fisheries observer programmes, the development of adaptive management strategies, and international collaboration to identify and mitigate threats.

     

Drivers for spatial modelling of a critically endangered seabird on a dynamic ocean area: Balearic shearwaters are non-vegetarian

1. Spatial modelling is an important research tool to improve our knowledge about the distribution of wildlife in the ocean. Using different modelling techniques (MaxEnt and a generalized linear mixed model), a predictive habitat suitability model was developed for one of the most threatened seabirds in the world: the Balearic shearwater, Puffinus mauretanicus.
2. Models were developed using a 10-year dataset from the Gulf of Cádiz (on the south-western Iberian Peninsula), a key foraging area for Balearic shearwaters during migration and the non-breeding season.
3. Predictive habitat maps strongly matched the observed distribution patterns, pointing to bathymetric features as the main modelling drivers. The species was concentrated on shallow areas (up to approximately 100 m in depth) of the continental shelf, very close to the mouth of the Guadalquivir River. In contrast with previous studies, Balearic shearwater distribution in the highly dynamic Gulf of Cádiz was not correlated with areas of high chlorophyll a concentration.
4. This lack of spatial correlation probably arises from the delay between the phytoplankton bloom and the response of the zooplankton and small fish that are preyed upon by Balearic shearwaters, which may result in important displacements of this trophic chain across the Gulf of Cádiz.
5. The analysis presented contributes to a better understanding of the spatial distribution and ecology of the critically endangered top predator in the Gulf of Cádiz and offers important information to improve management plans.

     

Amazon floodplain hydrology and implications for aquatic conservation

1. The amplitude, duration, frequency, and predictability of runoff and inundation of aquatic habitats are key hydrological characteristics linked to aquatic ecosystem functioning and biodiversity, but they are seldom integrated into analyses of Amazon floodplain ecology. Remote sensing approaches, measurements and modelling of floodplain hydrology provide a basis for this integration.
2. Effective legislation to protect floodplains and other wetlands depends on operational definitions that require application of hydrological data.
3. Extent and changes of flooded areas are linked to fish diversity and to presence and growth of flooded forests and floating plants.
4. Dam construction reduces river system connectivity and modifies the flood pulse, with major negative implications for floodplain ecosystems adapted to and dependent on a natural flood regime.
5. Trends and variability in climate plus deforestation are altering the Amazon's hydrological cycle, causing changes in discharge and flooded area with concomitant ecological impacts.

     

Longer migration not necessarily the costliest strategy for migrating humpback whales

1. Long‐distance migration is a demanding physical activity, and how well animals manage the associated costs will have important implications for their fitness.
2. The Oceania humpback whale (Megaptera novaeangliae) population is recovering from past exploitation markedly slower than the neighbouring east Australian whales. The reasons for this are unknown, although higher energetic costs of longer migratory distances could be a possible explanation. Due to their fully aquatic lives, studying the energy expenditure of these large animals requires methods that do not rely on capturing the animal, such as bioenergetic models.
3. A state‐space model was fitted to satellite data to infer behavioural states for southern migrating whales. Travel speeds and behavioural states were used in a bioenergetic model to estimate the energetic cost of the migration phase. Relative differences in average duration, distance, and energetic costs were compared between migratory routes and distances.
4. Total energy used during migration was a trade‐off between cost of transport (determined by travel speed) and daily maintenance (determined by daily basal metabolic costs). Oceania whales migrating to the Amundsen and Bellingshausen Seas travelled fastest and furthest, 15 and 21% further than whales migrating to the d'Urville Sea (east Australian whales) and Ross Sea, respectively. Therefore, they had the highest cost of transport, 25 and 85% higher than for d'Urville Sea and Ross Sea whales, respectively. However, energy saved in terms of daily maintenance by using fewer days to complete a longer migration resulted in only a 6–7% increase in total energetic cost.
5. The results highlight that travelling further does not necessarily translate into an increase in total energy expenditure for migratory whales, since they can compensate for longer distance by travelling faster. Further research on the energetics of different whale populations could provide insight into the productivity of Southern Ocean feeding regions and help understand the environmental and anthropogenic effects on the whales' energy budgets.

     

Woody species diversity in temperate Andean forests: The need for new conservation strategies

Chile has more than half of the temperate forests in the southern hemisphere. These have been included among the most threatened eco-regions in the world, because of the high degree of endemism and presence of monotypic genera. In this study, we develop empirical models to investigate present and future spatial patterns of woody species richness in temperate forests in south-central Chile. Our aims are both to increase understanding of species richness patterns in such forests and to develop recommendations for forest conservation strategies. Our data were obtained at multiple spatial scales, including field sampling, climate, elevation and topography data, and land-cover and spectrally derived variables from satellite sensor imagery. Climatic and land-cover variables most effectively accounted for tree species richness variability, while only weak relationships were found between explanatory variables and shrub species richness. The best models were used to obtain prediction maps of tree species richness for 2050, using data from the Hadley Centre’s HadCM3 model. Current protected areas are located far from the areas of highest tree conservation value and our models suggest this trend will continue. We therefore suggest that current conservation strategies are insufficient, a trend likely to be repeated across many other areas. We propose the current network of protected areas should be increased, prioritizing sites of both current and future importance to increase the effectiveness of the national protected areas system. In this way, target sites for conservation can also be chosen to bring other benefits, such as improved water supply to populated areas.     

Overcoming the rare species modelling paradox: A novel hierarchical framework applied to an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the “rare species modelling paradox” and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models are not over-fitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.     

Dealing with the variability in biofumigation efficacy through an epidemiological framework

Biofumigation, as originally defined, is the use, in agriculture, of the toxicity of Brassica crop residues to control soilborne plant pathogens. This toxicity is specifically attributed to the release of toxic isothiocyanates, through the hydrolysis of glucosinolates present in the crop residues. This technique is considered a possible alternative to the use of pesticides, but field studies have generated conflicting data concerning the efficacy of biofumigation at field scale, limiting the use of this technique. Analytical studies based on a systematic approach involving evaluation of the potential effects of isothiocyanates can be used to address this problem in a rigorous manner. However, many recent studies have indicated that the mechanisms underlying biofumigation are much more complex than a simple toxic effect of residues. In this review, we dissect and discuss the problems encountered when trying to understand the variability in biofumigation efficacy and propose an integrative epidemiological approach to overcome these problems. This approach involves separating the effects of the different parameters of the system, such as the effects of different management phases of the biofumigant crop (i.e. the period of biofumigant crop growth and the phase during which crop residues are pulverised and incorporated into the soil) on the epidemiological mechanisms driving the development of an epidemic (density of primary inoculum and dynamics of disease progression). Finally, we propose new avenues of research into biofumigation in which the use of epidemiological tools and methods may improve our understanding of the factors underlying variation in the efficacy of biofumigant crops.     

Influence of tree crown characteristics on the local PM10 distribution inside an urban street canyon in Antwerp (Belgium): A model and experimental approach

Apart from influencing the amount of leaf-deposited particles, tree crown morphology will influence the local distribution of atmospheric particles. Nevertheless, tree crowns are often represented very rudimentary in three-dimensional air quality models. Therefore, the influence of tree crown representation on the local ambient PM₁₀ concentration and resulting leaf-deposited PM₁₀ mass was evaluated, using the three-dimensional computational fluid dynamics (CFD) model ENVI-met^® and ground-based LiDAR imaging. The modelled leaf-deposited PM₁₀ mass was compared to gravimetric results within three different particle size fractions (0.2–3, 3–10 and >10 μm), obtained at 20 locations within the tree crown. Modelling of the LiDAR-derived tree crown resulted in altered atmospheric PM₁₀ concentrations in the vicinity of the tree crown. Although this model study was limited to a single tree and model configuration, our results demonstrate that improving tree crown characteristics (shape, dimensions and LAD) affects the resulting local PM₁₀ distribution in ENVI-met. An accurate tree crown representation seems, therefore, of great importance when aiming at modelling the local PM distribution.     

Effects of mountaintop mining on fish distributions in central Appalachia

Mountaintop mining with valley fills (MTM/VF) is the main source of landscape change in central Appalachia. While our knowledge of the local‐scale effects of MTM/VF on stream chemistry and biotic assemblages has recently improved, the effects at the landscape scale are less well known. In this study, we explore the effects of MTM/VF on the distributions of six fish species with contrasting ecologies in the upper Kentucky River basin, an area heavily affected by MTM/VF. Using a museum‐based data set of 239 occurrence records, land use/land cover data and boosted regression tree modelling, we were able to create robust predictive models for the focal species (AUCs = 0.82–0.93). Models explained from 41.2 to 71.9% of the variation in species distributions. We detected a marked negative influence of MTM/VF in four of the six species distribution models – with relative influences ranging from 5.9–12.7%. Species typically inhabiting faster‐flowing riffle and run mesohabitats appeared to respond more strongly to MTM/VF. Interestingly, the mean patch size of MTM/VF was more influential than the overall proportion of the watershed affected by MTM/VF in our models. Thus, our data suggest the spatial pattern of mining disturbance is very important in determining the cumulative impact of MTM/VF. Considering the central Appalachian region is a continental hot spot for freshwater biodiversity, establishing a firm understanding of the effects of MTM/VF at the landscape scale is essential if we wish to protect these natural resources.     

Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km²), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m⁻² d⁻¹ and 2.7–6.1 g C m⁻² d⁻¹ for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data aggregation. However, the scale of climate data is more relevant for impacts on annual averages of NPP or if the period is strongly affected or dominated by drought stress. There should be an awareness of the greater uncertainty for the NPP values in these situations if data are not available at high resolution. On the other hand, the results suggest that there is no need to simulate at high resolution for long term regional NPP averages based on the simplified assumptions (soil and management constant in time and space) used in this study.