Wildfire refugia in forests: Severe fire weather and drought mute the influence of topography and fuel age

Wildfire refugia (unburnt patches within large wildfires) are important for the persistence of fire‐sensitive species across forested landscapes globally. A key challenge is to identify the factors that determine the distribution of fire refugia across space and time. In particular, determining the relative influence of climatic and landscape factors is important in order to understand likely changes in the distribution of wildfire refugia under future climates. Here, we examine the relative effect of weather (i.e. fire weather, drought severity) and landscape features (i.e. topography, fuel age, vegetation type) on the occurrence of fire refugia across 26 large wildfires in south‐eastern Australia. Fire weather and drought severity were the primary drivers of the occurrence of fire refugia, moderating the effect of landscape attributes. Unburnt patches rarely occurred under ‘severe’ fire weather, irrespective of drought severity, topography, fuels or vegetation community. The influence of drought severity and landscape factors played out most strongly under ‘moderate’ fire weather. In mesic forests, fire refugia were linked to variables that affect fuel moisture, whereby the occurrence of unburnt patches decreased with increasing drought conditions and were associated with more mesic topographic locations (i.e. gullies, pole‐facing aspects) and vegetation communities (i.e. closed‐forest). In dry forest, the occurrence of refugia was responsive to fuel age, being associated with recently burnt areas (<5 years since fire). Overall, these results show that increased severity of fire weather and increased drought conditions, both predicted under future climate scenarios, are likely to lead to a reduction of wildfire refugia across forests of southern Australia. Protection of topographic areas able to provide long‐term fire refugia will be an important step towards maintaining the ecological integrity of forests under future climate change.     

Modeling optimal responses and fitness consequences in a changing Arctic

Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade‐offs, but this method has not yet been used to study possible changes in optimal trade‐offs caused by climate change. We created a stochastic dynamic programming model capturing trade‐off decisions required by an individual adult female polar bear (Ursus maritimus) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best‐case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.     

Optimising Seagrass Conservation for Ecological Functions

Ecosystems - Animals are central to numerous ecological processes that shape the structure and function of ecosystems. It follows that species that are strongly linked to specific functions can...     

SAR inspired by aldehyde oxidase (AO) metabolism: Discovery of novel,CNS penetrant tricyclic M4 PAMs

This letter describes progress towards an M₄ PAM preclinical candidate inspired by an unexpected aldehyde oxidase (AO) metabolite of a novel, CNS penetrant thieno[2,3-c]pyridine core to an equipotent, non-CNS penetrant thieno[2,3-c]pyrdin-7(6H)-one core. Medicinal chemistry design efforts yielded two novel tricyclic cores that enhanced M₄ PAM potency, regained CNS penetration, displayed favorable DMPK properties and afforded robust in vivo efficacy in reversing amphetamine-induced hyperlocomotion in rats.     

Integrating life history traits into predictive phylogeography

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest and the Southwestern Arid Lands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine‐learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.     

IMPACT World+: a globally regionalized life cycle impact assessment method

The International Journal of Life Cycle Assessment - This paper addresses the need for a globally regionalized method for life cycle impact assessment (LCIA), integrating multiple state-of-the-art...     

PMR5, an acetylation protein at the intersection of pectin biosynthesis and defense against fungal pathogens

Powdery mildew (Golovinomyces cichoracearum), one of the most prolific obligate biotrophic fungal pathogens worldwide, infects its host by penetrating the plant cell wall without activating the plant's innate immune system. The Arabidopsis mutant powdery mildew resistant 5 (pmr5) carries a mutation in a putative pectin acetyltransferase gene that confers enhanced resistance to powdery mildew. Here, we show that heterologously expressed PMR5 protein transfers acetyl groups from [¹⁴C]‐acetyl‐CoA to oligogalacturonides. Through site‐directed mutagenesis, we show that three amino acids within a highly conserved esterase domain in putative PMR5 orthologs are necessary for PMR5 function. A suppressor screen of mutagenized pmr5 seed selecting for increased powdery mildew susceptibility identified two previously characterized genes affecting the acetylation of plant cell wall polysaccharides, RWA2 and TBR. The rwa2 and tbr mutants also suppress powdery mildew disease resistance in pmr6, a mutant defective in a putative pectate lyase gene. Cell wall analysis of pmr5 and pmr6, and their rwa2 and tbr suppressor mutants, demonstrates minor shifts in cellulose and pectin composition. In direct contrast to their increased powdery mildew resistance, both pmr5 and pmr6 plants are highly susceptibile to multiple strains of the generalist necrotroph Botrytis cinerea, and have decreased camalexin production upon infection with B. cinerea. These results illustrate that cell wall composition is intimately connected to fungal disease resistance and outline a potential route for engineering powdery mildew resistance into susceptible crop species.     

Monarch butterfly host plant (milkweed Asclepias spp.) abundance varies by habitat type across 98 prairies

The decline in migratory monarch butterflies (Danaus plexippus) over the past 20 years has been attributed to several drivers, including loss of their host plants (milkweeds Asclepias spp.). This has sparked widespread interest in milkweed ecology and restoration. We developed a model on environmental and habitat‐type variables to predict milkweed abundance by sampling 93 prairie plantings (47 conservation plantings and 46 roadsides) and 5 unplowed prairie remnants throughout the state of Iowa, United States. Milkweeds were censused in 10–25 random locations within each site, and data on plant diversity, age of planting, soil characteristics, and management were tested as predictors of abundance. Milkweed densities of all species combined were highest in remnant prairies (8,705 stems/ha), intermediate in roadside plantings (1,274 stems/ha), and lowest in conservation plantings (212 stems/ha). Most milkweeds were common milkweeds Asclepias syriaca, which were more abundant in roadside than conservation plantings. Remnants contained the most milkweed species. Total milkweed and common milkweed abundance were both predicted by higher soil pH, a more linear site shape, and lower soil bulk density across restorations. Our results indicate that common milkweed is maintained by disturbance, and establishes readily in rural roadside habitat. Remnants are important as reservoirs for multiple milkweed species and should be protected.