Noah's ark conservation will not preserve threatened ecological communities under climate change

Background: Effective conservation of threatened ecological communities requires knowledge of where climatically suitable habitat is likely to persist into the future. We use the critically endangered Lowland Grassland community of Tasmania, Australia a

A framework for incorporating fine-scale dispersal behaviour into biodiversity conservation planning

Fine-scale landscape features such as scattered trees are increasingly thought to be critical for dispersal, and need to be considered in connectivity modelling and planning. Yet existing modelling approaches struggle to adequately take fine-scale features and threshold dynamics of dispersal behaviour into account, in part because of computational limitations. We present a framework for modelling connectivity at fine spatial resolutions over large spatial extents. Our framework involves a novel approach to characterising fine-scale dispersal behaviour within the context of existing modelling methods, and uses key parameters of dispersal behaviour to link models and their interpretation at multiple scales. We address computational limitations by creating a gap-crossing threshold layer, which identifies areas where dispersal is possible because of the presence and spacing of fine-scale connectivity elements. This layer is combined with a dispersal-cost layer within a graph-network analysis to identify the optimal least-cost path between patches. Graph metrics are used to assess the importance of specific patches at the regional-scale and to describe connectivity for the whole landscape. A local-scale connectivity model using the Circuitscape software complements the regional analysis outputs by considering all possible pathways across a landscape simultaneously rather than a single least-cost path. The framework was designed specifically to be applied by land use planners who need to quantify the impacts of property development on fine-scale connectivity, yet need to assess implications at the regional scale. We demonstrate the framework by applying it in the Lower Hunter region, Australia

Climate projections for ecologists

Climate projections are essential for studying ecological responses to climate change, and their use is now common in ecology. However, the lack of integration between ecology and climate science has restricted understanding of the available climate dat

To Be Or Not to Be? Variable selection can change the projected fate of a threatened species under future climate

Species distribution models (SDMs) are commonly used to project future changes in the geographic ranges of species, to estimate extinction rates and to plan biodiversity conservation. However, these models can produce a range of results depending on how

Effects of soil- and climate data aggregation on simulated potato yield and irrigation water requirement

Input data aggregation affects crop model estimates at the regional level. Previous studies have focused on the impact of aggregating climate data used to compute crop yields. However, little is known about the combined data aggregation effect of climate (DAEc) and soil (DAEs) on irrigation water requirement (IWR) in cool-temperate and spatially heterogeneous environments. The aims of this study were to quantify DAEc\ua0and DAEs\ua0of model input data and their combined impacts for simulated irrigated and rainfed yield and IWR. The Agricultural Production Systems sIMulator Next Generation model was applied for the period 1998–2017 across areas suitable for potato (Solanum tuberosum\ua0L.) in Tasmania, Australia, using data at 5, 15, 25 and 40\ua0km resolution. Spatial variances of inputs and outputs were evaluated by the relative absolute difference (rAD¯) between the aggregated grids and the 5\ua0km grids. Climate data aggregation resulted in a\ua0rAD¯\ua0of 0.7–12.1%, with high values especially for areas with pronounced differences in elevation. The\ua0rAD¯\ua0of soil data was higher (5.6–26.3%) than\ua0rAD¯\ua0of climate data and was mainly affected by aggregation of organic carbon and maximum plant available water capacity (i.e.\ua0the difference between field capacity and wilting point in the effective root zone). For yield estimates, the difference among resolutions (5\ua0km\ua0vs.\ua040\ua0km) was more pronounced for rainfed (rAD¯\ua0=\ua014.5%) than irrigated conditions (rAD¯\ua0=\ua03.0%). The\ua0rAD¯\ua0of IWR was 15.7% when using input data at 40\ua0km resolution. Therefore, reliable simulations of rainfed yield require a higher spatial resolution than simulation of irrigated yields. This needs to be considered when conducting regional modelling studies across Tasmania. This study also highlights the need to separately quantify the impact of input data aggregation on model outputs to inform about data aggregation errors and identify those variables that explain these errors

From static connectivity modelling to scenario-based planning at local and regional scales

Despite the proliferation of connectivity modelling approaches, static models have limited usefulness for decision-making by policy-makers and land managers, particularly where significant changes in land uses might be expected into the future. This study presents a flexible, scenario-based approach for modelling fine-scaled connectivity using graph-theory with least-cost paths for modelling connectivity at the regional scale and circuit theory at the local scale. The method allows for the assessment of a range of scenarios based on varying land use practices. Using the Lower Hunter region, Australia as a case study we tested five scenarios that describe the impact of different development choices on connectivity, ranging from high rates of urbanisation to revegetation of a designated green corridor. The changes in connectivity from the current state were assessed by visualising component boundaries and link locations and calculating patch- and landscape-scale graph metrics. In the Lower Hunter we found the green corridor scenario increased connectivity both visually and quantitatively, as shown by a 105% increase in the integral index of connectivity (IIC) which measures habitat availability (reachability) at the landscape scale. In contrast the urbanisation scenario resulted in a decrease in connectivity, with a 39% decrease in the IIC. The approach outlined in this paper is flexible, enabling a range of interests to be included, depending on the datasets available and the issues that need to be addressed. Such methods can be readily and rapidly applied by consultants or government agencies, in this region and elsewhere, to incorporate connectivity modelling into development plans

HNRNPC haploinsufficiency affects alternative splicing of intellectual disability-associated genes and causes a neurodevelopmental disorder

Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an essential, ubiquitously abundant protein involved in mRNA processing. Genetic variants in other members of the HNRNP family have been associated with neurodevelopmental disorders. Here, we describe 13 individuals with global developmental delay, intellectual disability, behavioral abnormalities, and subtle facial dysmorphology with heterozygous HNRNPC germline variants. Five of them bear an identical in-frame deletion of nine amino acids in the extreme C terminus. To study the effect of this recurrent variant as well as HNRNPC haploinsufficiency, we used induced pluripotent stem cells (iPSCs) and fibroblasts obtained from affected individuals. While protein localization and oligomerization were unaffected by the recurrent C-terminal deletion variant, total HNRNPC levels were decreased. Previously, reduced HNRNPC levels have been associated with changes in alternative splicing. Therefore, we performed a meta-analysis on published RNA-seq datasets of three different cell lines to identify a ubiquitous HNRNPC-dependent signature of alternative spliced exons. The identified signature was not only confirmed in fibroblasts obtained from an affected individual but also showed a significant enrichment for genes associated with intellectual disability. Hence, we assessed the effect of decreased and increased levels of HNRNPC on neuronal arborization and neuronal migration and found that either condition affects neuronal function. Taken together, our data indicate that HNRNPC haploinsufficiency affects alternative splicing of multiple intellectual disability-associated genes and that the developing brain is sensitive to aberrant levels of HNRNPC. Hence, our data strongly support the inclusion of HNRNPC to the family of HNRNP-related neurodevelopmental disorders. [Display omitted] We identified genetic variants of HNRNPC in 13 individuals with intellectual disability and global developmental delay. Through a meta-analysis of multiple cell types, we found that loss of HNRNPC affects alternative splicing, in particular of intellectual disability-associated genes. In vivo assays confirmed that neurodevelopment was affected by aberrant HNRNPC levels

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of

Systematic study of flow vector decorrelation in sNN=5.02\mathbf{\sqrt{\textit{s}_{_{\bf NN}}}=5.02} TeV Pb--Pb collisions

Measurements of the $p_{\rm T}$-dependent flow vector fluctuations in Pb--Pb collisions at $\sqrt{s_{_{\rm NN}}} = 5.02~\mathrm{TeV}$ using azimuthal correlations with the ALICE experiment at the LHC are presented. A four-particle correlation approach [1] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the $p_{\rm T}$-dependent flow vector fluctuations at $\sqrt{s_{_{\rm NN}}} = 5.02~\mathrm{TeV}$ with two-particle correlations. Significant $p_{\rm T}$-dependent fluctuations of the $\vec{V}_{2}$ flow vector in Pb--Pb collisions are found across different centrality ranges, with the largest fluctuations of up to $\sim$15% being present in the 5% most central collisions. In parallel, no evidence of significant $p_{\rm T}$-dependent fluctuations of $\vec{V}_{3}$ or $\vec{V}_{4}$ is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than $5\sigma$ significance in central collisions. These observations in Pb--Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high $p_{\rm T}$, which might be biased by $p_{\rm T}$-dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be re-examined to improve our understanding of initial conditions, quark--gluon plasma (QGP) properties, and the dynamic evolution of the created system.Measurements of the pT-dependent flow vector fluctuations in Pb–Pb collisions at sNN=5.02TeV using azimuthal correlations with the ALICE experiment at the Large Hadron Collider are presented. A four-particle correlation approach [ALICE Collaboration, Phys. Rev. C 107, L051901 (2023)] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the pT-dependent flow vector fluctuations at sNN=5.02TeV with two-particle correlations. Significant pT-dependent fluctuations of the V⃗2 flow vector in Pb–Pb collisions are found across different centrality ranges, with the largest fluctuations of up to ∼15% being present in the 5% most central collisions. In parallel, no evidence of significant pT-dependent fluctuations of V⃗3 or V⃗4 is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than 5σ significance in central collisions. These observations in Pb–Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high pT, which might be biased by pT-dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be reexamined to improve our understanding of initial conditions, quark–gluon plasma properties, and the dynamic evolution of the created system.Measurements of the $p_{\rm T}$-dependent flow vector fluctuations in Pb-Pb collisions at $\sqrt{s_{_{\rm NN}}} = 5.02~\mathrm{TeV}$ using azimuthal correlations with the ALICE experiment at the LHC are presented. A four-particle correlation approach [1] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the $p_{\rm T}$-dependent flow vector fluctuations at $\sqrt{s_{_{\rm NN}}} = 5.02~\mathrm{TeV}$ with two-particle correlations. Significant $p_{\rm T}$-dependent fluctuations of the $\vec{V}_{2}$ flow vector in Pb-Pb collisions are found across different centrality ranges, with the largest fluctuations of up to $\sim$15% being present in the 5% most central collisions. In parallel, no evidence of significant $p_{\rm T}$-dependent fluctuations of $\vec{V}_{3}$ or $\vec{V}_{4}$ is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than $5\sigma$ significance in central collisions. These observations in Pb-Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high $p_{\rm T}$, which might be biased by $p_{\rm T}$-dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be re-examined to improve our understanding of initial conditions, quark--gluon plasma (QGP) properties, and the dynamic evolution of the created system