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1. A novel synthesis of two decades of microsatellite studies on European beech reveals decreasing genetic diversity from glacial refugia

   https://doi.org/10.1007/s11295-022-01577-4  

   Stefanini, Camilla ; Csilléry, Katalin ; Ulaszewski, Bartosz ; Burczyk, Jarosław ; Schaepman, Michael E. ; Schuman, Meredith C. ( February 2023 , Tree Genetics & Genomes)

   Abstract Genetic diversity influences the evolutionary potential of forest trees under changing environmental conditions, thus indirectly the ecosystem services that forests provide. European beech ( Fagus sylvatica L.) is a dominant European forest tree species that increasingly suffers from climate change-related die-back. Here, we conducted a systematic literature review of neutral genetic diversity in European beech and created a meta-data set of expected heterozygosity ( He ) from all past studies providing nuclear microsatellite data. We propose a novel approach, based on population genetic theory and a min–max scaling to make past studies comparable. Using a new microsatellite data set with unprecedented geographic coverage and various re-sampling schemes to mimic common sampling biases, we show the potential and limitations of the scaling approach. The scaled meta-dataset reveals the expected trend of decreasing genetic diversity from glacial refugia across the species range and also supports the hypothesis that different lineages met and admixed north of the European mountain ranges. As a result, we present a map of genetic diversity across the range of European beech which could help to identify seed source populations harboring greater diversity and guide sampling strategies for future genome-wide and functional investigations of genetic variation. Our approach illustrates how to combine information from several nuclear microsatellite data sets to describe patterns of genetic diversity extending beyond the geographic scale or mean number of loci used in each individual study, and thus is a proof-of-concept for synthesizing knowledge from existing studies also in other species. 

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2. Tropical cyclone frequency: turning paleoclimate into projections

   https://doi.org/10.1088/2752-5295/aca785  

   Wallace, E. J. ; Dee, S. G. ( December 2022 , Environmental Research: Climate)

   Future changes to tropical cyclone (TC) climate have the potential to dramatically impact the social and economic landscape of coastal communities. Paleoclimate modeling and paleohurricane proxy development offer exciting opportunities to understand how TC properties (like frequency) change in response to climate variability on long time scales. However, sampling biases in proxies make it difficult to ascertain whether signals in paleohurricane records are related to climate variability or just stochasticity. Short observations and simulation biases prevent TC models from capturing the full range of climate variability and TC characteristics. Integration of these two data types can help address these uncertainties. Robust data model comparison in paleotempestology will require (a) simulating TCs using new paleoclimate data assimilation products and climate model ensembles, (b) building a central repository of open access paleohurricane proxies, (c) compiling paleohurricane records, and (d) filling key gaps in the existing paleohurricane networks. Incorporating the combined information from both paleohurricane proxies and paleo TC simulations into risk assessments for coastal communities could help improve adaptation strategies.

    

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3. E nvironmental niche adaptation revealed through fine scale phenological niche modelling

   https://doi.org/10.1111/jbi.13663  

   Van Dam, Matthew H. ; Rominger, Andrew J. ; Brewer, Michael S. ( July 2019 , Journal of Biogeography)

   Phenology, the temporal response of a population to its climate, is a crucial behavioural trait shared across life on earth. How species adapt their phenologies to climate change is poorly understood but critical in understanding how species will respond to future change. We use a group of flies (Rhaphiomidas) endemic to the North American deserts to understand how species adapt to changing climatic conditions. Here, we explore a novel approach for taxa with constrained phenologies aimed to accurately model their environmental niche and relate this to phenological and morphological adaptations in a phylogenetic context.

   Insecta, Diptera, Mydidae,Rhaphiomidas.

   North America, Mojave, Sonoran and Chihuahuan Deserts.

   We gathered geographical and phenological occurrence data for the entire genusRhaphiomidas, and, estimated a time calibrated phylogeny. We compared Daymet derived temperature values for a species adult occurrence period (phenology) with those derived from WorldClim data that is partitioned by month or quarter to examine what effect using more precise data has on capturing a species’ environmental niche. We then examined to what extent phylogenetic signal in phenological traits, climate tolerance and morphology can inform us about how species adapt to different environmental regimes.

   We found that the Bioclim temperature data, which are averages across monthly intervals, poorly represent the climate windows to which adult flies are actually adapted. Using temporally relevant climate data, we show that many species use a combination of morphological and phenological changes to adapt to different climate regimes. There are also instances where species changed only phenology to track a climate type or only morphology to adapt to different environments.

   Without using a fine‐scale phenological data approach, identifying environmental adaptations could be misleading because the data do not represent the conditions the animals are actually experiencing. We find that fine‐scale phenological niche models are needed when assessing taxa that have a discrete phenological window that is key to their survival, accurately linking environment to morphology and phenology. Using this approach, we show thatRhaphiomidasuse a combination of niche tracking and adaptation to persist in new niches. Modelling the effect of phenology on such species’ niches will be critical for better predictions of how these species might respond to future climate change.

    

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4. Predicting climate change impacts on critical fisheries species in Fijian marine systems and its implications for protected area spatial planning

   https://doi.org/10.1111/ddi.13709  

   Lawson, Katherine N. ; Lang, Karina M. ; Rabaiotti, Daniella ; Drew, Joshua ( August 2023 , Diversity and Distributions)

   Spatially explicit protections of coastal habitats determined on the current distribution of species and ecosystems risk becoming obsolete in 100 years if the movement of species ranges outpaces management action. Hence, a critical step of conservation is predicting the efficacy of management actions in future. We aimed to determine how foundational, habitat‐building species will respond to climate change in Fiji.

   The Republic of Fiji.

   We develop species distribution models (SDMs) using MaxEnt, General Additive Models and Boosted Regression Trees and publicly available data from the Global Biodiversity Information Facility to predict changes in distribution of suitable habitat for mangrove forests, coral habitat, seagrass meadows and critical fisheries invertebrates under several IPCC climate change scenarios in 2070 or 2100. We then overlay predicted distribution models onto existing Fijian protected area network to assess whether today's conservation measures will afford protection to tomorrow's distributions.

   We found that mangrove suitability is projected to decrease along the Coral Coast and increase northward towards the Yasawa Islands due to precipitation changes. The response of seagrass meadows was predicted to be inconsistent and dependent on the climate scenario. Meanwhile, suitability for coral reefs was not predicted to decline significantly overall. The mangrove crabScylla serrata, an important resource for fisherwomen in Fiji, is projected to increase in habitat suitability while economically important sea cucumber species will have highly variable responses to climate change.

   Species distribution models are a critical tool for conservation managers, as linking spatial distribution data with future climate change scenarios can aid in the creation and resiliency of protected area programmes. New protected area designations should consider the future distribution of species to maximize benefits to those taxa.

    

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5. Redesigning the Trading Zone between Systematics and Conservation: Insights from Malagasy mouse lemur classifications, 1982 to present

   https://doi.org/10.3897/biss.4.59234  

   Franz, Nico ; Sterner, Beckett ; Upham, Nathan ; Cortés Hernández, Kevin ( October 2020 , Biodiversity Information Science and Standards)

   Translating information between the domains of systematics and conservation requires novel information management designs. Such designs should improve interactions across the trading zone between the domains, herein understood as the model according to which knowledge and uncertainty are productively translated in both directions (cf. Collins et al. 2019). Two commonly held attitudes stand in the way of designing a well-functioning systematics-to-conservation trading zone. On one side, there are calls to unify the knowledge signal produced by systematics, underpinned by the argument that such unification is a necessary precondition for conservation policy to be reliably expressed and enacted (e.g., Garnett et al. 2020). As a matter of legal scholarship, the argument for systematic unity by legislative necessity is principally false (Weiss 2003, MacNeil 2009, Chromá 2011), but perhaps effective enough as a strategy to win over audiences unsure about robust law-making practices in light of variable and uncertain knowledge. On the other side, there is an attitude that conservation cannot ever restrict the academic freedom of systematics as a scientific discipline (e.g., Raposo et al. 2017). This otherwise sound argument misses the mark in the context of designing a productive trading zone with conservation. The central interactional challenge is not whether the systematic knowledge can vary at a given time and/or evolve over time, but whether these signal dynamics are tractable in ways that actors can translate into robust maxims for conservation. Redesigning the trading zone should rest on the (historically validated) projection that systematics will continue to attract generations of inspired, productive researchers and broad-based societal support, frequently leading to protracted conflicts and dramatic shifts in how practioners in the field organize and identify organismal lineages subject to conservation. This confident outlook for systematics' future, in turn, should refocus the challenge of designing the trading zone as one of building better information services to model the concurrent conflicts and longer-term evolution of systematic knowledge. It would seem unreasonable to expect the International Union for Conservation of Nature (IUCN) Red List Index to develop better data science models for the dynamics of systematic knowledge (cf. Hoffmann et al. 2011) than are operational in the most reputable information systems designed and used by domain experts (Burgin et al. 2018). The reasonable challenge from conservation to systematics is not to stop being a science but to be a better data science. In this paper, we will review advances in biodiversity data science in relation to representing and reasoning over changes in systematic knowledge with computational logic, i.e., modeling systematic intelligence (Franz et al. 2016). We stress-test this approach with a use case where rapid systematic signal change and high stakes for conservation action intersect, i.e., the Malagasy mouse lemurs ( Microcebus É. Geoffroy, 1834 sec. Schüßler et al. 2020), where the number of recognized species-level concepts has risen from 2 to 25 in the span of 38 years (1982–2020). As much as scientifically defensible, we extend our modeling approach to the level of individual published occurrence records, where the inability to do so sometimes reflects substandard practice but more importantly reveals systemic inadequacies in biodiversity data science or informational modeling. In the absence of shared, sound theoretical foundations to assess taxonomic congruence or incongruence across treatments, and in the absence of biodiversity data platforms capable of propagating logic-enabled, scalable occurrence-to-concept identification events to produce alternative and succeeding distribution maps, there is no robust way to provide a knowledge signal from systematics to conservation that is both consistent in its syntax and acccurate in its semantics, in the sense of accurately reflecting the variation and uncertainty that exists across multiple systematic perspectives. Translating this diagnosis into new designs for the trading zone is only one "half" of the solution, i.e., a technical advancement that then would need to be socially endorsed and incentivized by systematic and conservation communities motivated to elevate their collaborative interactions and trade robustly in inherently variable and uncertain information. 

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