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Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H₁₀₀.

Combler le fossé entre les prévisions des modèles climatiques à échelle grossière et la réalité climatique à échelle fine des espèces est un enjeu clé de la recherche en biologie du changement climatique. Bien qu'il soit maintenant bien connu que la plupart des organismes ne connaissent pas les conditions climatiques enregistrées dans les stations météorologiques, il existe peu d'informations sur les écarts entre les microclimats et les températures interpolées mondiales utilisées dans les modèles de répartition des espèces, et leurs conséquences sur les performances des organismes. Pour résoudre ce problème, nous avons examiné l'hétérogénéité spatio-temporelle à échelle fine des températures de l'air, du couvert végétal et du sol des paysages agricoles des Andes équatoriennes et les avons comparés aux prévisions des grilles climatiques interpolées mondiales. Des séries temporelles de températures ont été mesurées dans l'air, la canopée et le sol pour 108 localités à trois altitudes et analysées à l'aide de la transformée de Fourier. Les écarts entre les températures locales et les grilles interpolées mondiales et leurs implications pour la performance des ravageurs ont ensuite été cartographiés et analysés à l'aide de la boîte à outils statistique SIG. Nos résultats ont montré que les prévisions globales interpolées surestiment de 77,5±10 % et sous-estiment de 82,1±12 % les températures locales minimales et maximales de l'air enregistrées dans la grille étudiée. Des modifications supplémentaires de la température de l'air local étaient dues au tamponnage thermique du couvert végétal (de − 2,7°K pendant la journée à 1,3°K pendant la nuit) et des sols (de −4,9°K pendant la journée à 6,7°K pendant la nuit) avec un effet significatif de la phénologie des cultures sur l'effet tampon. Ces écarts entre les températures interpolées et locales ont fortement affecté les prévisions de la performance d'un ravageur ectothermique des cultures, car les températures interpolées prédisaient des taux de croissance des ravageurs 2,3 à 4,3 fois inférieurs à ceux prédits par les températures locales. Cette étude fournit des informations quantitatives sur la limitation des données climatiques à échelle grossière pour capturer la réalité de l'environnement climatique vécu par les organismes vivants. Dans les régions très hétérogènes telles que les montagnes tropicales, il convient donc de faire preuve de prudence lors de l'utilisation de modèles mondiaux pour déduire des processus biologiques à l'échelle locale. Cerrar la brecha entre las predicciones de los modelos climáticos a escala gruesa y la realidad climática a escala fina de las especies es un tema clave de la investigación en biología del cambio climático. Si bien ahora es bien sabido que la mayoría de los organismos no experimentan las condiciones climáticas registradas en las estaciones meteorológicas, hay poca información sobre las discrepancias entre los microclimas y las temperaturas globales interpoladas utilizadas en los modelos de distribución de especies, y sus consecuencias para el rendimiento de los organismos. Para abordar este problema, examinamos la heterogeneidad espaciotemporal a escala fina en las temperaturas del aire, el dosel de los cultivos y el suelo de los paisajes agrícolas en los Andes ecuatorianos y los comparamos con las predicciones de las redes climáticas interpoladas globales. Las series temporales de temperatura se midieron en aire, dosel y suelo para 108 localidades a tres altitudes y se analizaron mediante la transformada de Fourier. Las discrepancias entre las temperaturas locales frente a las redes interpoladas globales y sus implicaciones para el rendimiento de las plagas se mapearon y analizaron utilizando una caja de herramientas estadísticas SIG. Nuestros resultados mostraron que las predicciones interpoladas globales sobreestiman en un 77.5±10% y subestiman en un 82.1±12% las temperaturas mínimas y máximas locales del aire registradas en la cuadrícula estudiada. Las modificaciones adicionales de las temperaturas locales del aire se debieron al amortiguamiento térmico de las copas de las plantas (de -2,7 ° K durante el día a 1,3 ° K durante la noche) y los suelos (de -4,9 ° K durante el día a 6,7 ° K durante la noche) con un efecto significativo de la fenología de los cultivos en el efecto amortiguador. Estas discrepancias entre las temperaturas interpoladas y locales afectaron fuertemente las predicciones del rendimiento de una plaga de cultivo ectotérmico, ya que las temperaturas interpoladas predijeron tasas de crecimiento de plagas 2.3–4.3 veces más bajas que las predichas por las temperaturas locales. Este estudio proporciona información cuantitativa sobre la limitación de los datos climáticos a escala aproximada para capturar la realidad del entorno climático experimentado por los organismos vivos. Por lo tanto, en regiones altamente heterogéneas como las montañas tropicales, se debe tener precaución al utilizar modelos globales para inferir procesos biológicos a escala local. Bridging the gap between the predictions of coarse-scale climate models and the fine-scale climatic reality of species is a key issue of climate change biology research. While it is now well known that most organisms do not experience the climatic conditions recorded at weather stations, there is little information on the discrepancies between microclimates and global interpolated temperatures used in species distribution models, and their consequences for organisms' performance. To address this issue, we examined the fine-scale spatiotemporal heterogeneity in air, crop canopy and soil temperatures of agricultural landscapes in the Ecuadorian Andes and compared them to predictions of global interpolated climatic grids. Temperature time-series were measured in air, canopy and soil for 108 localities at three altitudes and analysed using Fourier transform. Discrepancies between local temperatures vs. global interpolated grids and their implications for pest performance were then mapped and analysed using GIS statistical toolbox. Our results showed that global interpolated predictions over-estimate by 77.5±10% and under-estimate by 82.1±12% local minimum and maximum air temperatures recorded in the studied grid. Additional modifications of local air temperatures were due to the thermal buffering of plant canopies (from −2.7°K during daytime to 1.3°K during night-time) and soils (from −4.9°K during daytime to 6.7°K during night-time) with a significant effect of crop phenology on the buffer effect. This discrepancies between interpolated and local temperatures strongly affected predictions of the performance of an ectothermic crop pest as interpolated temperatures predicted pest growth rates 2.3–4.3 times lower than those predicted by local temperatures. This study provides quantitative information on the limitation of coarse-scale climate data to capture the reality of the climatic environment experienced by living organisms. In highly heterogeneous region such as tropical mountains, caution should therefore be taken when using global models to infer local-scale biological processes. يعد سد الفجوة بين تنبؤات النماذج المناخية ذات النطاق الخشن والواقع المناخي الدقيق للأنواع قضية رئيسية في أبحاث البيولوجيا المتعلقة بتغير المناخ. في حين أنه من المعروف الآن أن معظم الكائنات الحية لا تعاني من الظروف المناخية المسجلة في محطات الطقس، إلا أن هناك القليل من المعلومات حول التناقضات بين المناخات الدقيقة ودرجات الحرارة العالمية المستكملة المستخدمة في نماذج توزيع الأنواع، وعواقبها على أداء الكائنات الحية. لمعالجة هذه المشكلة، قمنا بفحص عدم التجانس الزماني المكاني الدقيق في الهواء ومظلة المحاصيل ودرجات حرارة التربة للمناظر الطبيعية الزراعية في جبال الأنديز الإكوادورية وقارناها بتنبؤات الشبكات المناخية العالمية المستكملة. تم قياس السلاسل الزمنية لدرجة الحرارة في الهواء والمظلة والتربة لـ 108 موقعًا على ثلاثة ارتفاعات وتم تحليلها باستخدام تحويل فورييه. ثم تم رسم خرائط التناقضات بين درجات الحرارة المحلية مقابل الشبكات العالمية المستكملة وآثارها على أداء الآفات وتحليلها باستخدام مجموعة الأدوات الإحصائية لنظم المعلومات الجغرافية. أظهرت نتائجنا أن التنبؤات العالمية المستكملة تزيد عن التقديرات بنسبة 77.5±10 ٪ وتقل عن التقديرات بنسبة 82.1±12 ٪ من الحد الأدنى المحلي والحد الأقصى لدرجات حرارة الهواء المسجلة في الشبكة المدروسة. كانت التعديلات الإضافية في درجات حرارة الهواء المحلية بسبب التخزين المؤقت الحراري لمظلات النباتات (من - 2.7 درجة كلفن خلال النهار إلى 1.3 درجة كلفن خلال الليل) والتربة (من - 4.9 درجة كلفن خلال النهار إلى 6.7 درجة كلفن خلال الليل) مع تأثير كبير لظاهرة المحاصيل على تأثير العازل. أثرت هذه التناقضات بين درجات الحرارة المستكملة والمحلية بشدة على التنبؤات بأداء آفة المحاصيل خارجة الحرارة حيث تنبأت درجات الحرارة المستكملة بمعدلات نمو الآفات 2.3–4.3 مرة أقل من تلك التي تنبأت بها درجات الحرارة المحلية. توفر هذه الدراسة معلومات كمية عن محدودية البيانات المناخية ذات النطاق الخشن لالتقاط واقع البيئة المناخية التي تعاني منها الكائنات الحية. في المناطق غير المتجانسة للغاية مثل الجبال الاستوائية، يجب توخي الحذر عند استخدام النماذج العالمية لاستنتاج العمليات البيولوجية على المستوى المحلي.

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21(st) century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning.

Water use efficiency (WUE) is a quantitative measurement which improvement is a major issue in the context of global warming and restrictions in water availability for agriculture. In this study, we aimed at studying the variation and genetic control of WUE and the respective role of its components (plant biomass and transpiration) in a perennial fruit crop. We explored an INRA apple core collection grown in a phenotyping platform to screen one-year-old scions for their accumulated biomass, transpiration and WUE under optimal growing conditions. Plant biomass was decompose into morphological components related to either growth or organ expansion. For each trait, nine mixed models were evaluated to account for the genetic effect and spatial heterogeneity inside the platform. The Best Linear Unbiased Predictors of genetic values were estimated after model selection. Mean broad-sense heritabilities were calculated from variance estimates. Heritability values indicated that biomass (0.76) and WUE (0.73) were under genetic control. This genetic control was lower in plant transpiration with an heritability of 0.54. Across the collection, biomass accounted for 70% of the WUE variability. A Hierarchical Ascendant Classification of the core collection indicated the existence of six groups of genotypes with contrasting morphology and WUE. Differences between morphotypes were interpreted as resulting from differences in the main processes responsible for plant growth: cell division leading to the generation of new organs and cell elongation leading to organ dimension. Although further studies will be necessary on mature trees with more complex architecture and multiple sinks such as fruits, this study is a first step for improving apple plant material for the use of water.

Recent shifts in the geographic distribution of marine species have been linked to shifts in preferred thermal habitats. These shifts in distribution have already posed challenges for living marine resource management, and there is a strong need for projections of how species might be impacted by future changes in ocean temperatures during the 21st century. We modeled thermal habitat for 686 marine species in the Atlantic and Pacific oceans using long-term ecological survey data from the North American continental shelves. These habitat models were coupled to output from sixteen general circulation models that were run under high (RCP 8.5) and low (RCP 2.6) future greenhouse gas emission scenarios over the 21st century to produce 32 possible future outcomes for each species. The models generally agreed on the magnitude and direction of future shifts for some species (448 or 429 under RCP 8.5 and RCP 2.6, respectively), but strongly disagreed for other species (116 or 120 respectively). This allowed us to identify species with more or less robust predictions. Future shifts in species distributions were generally poleward and followed the coastline, but also varied among regions and species. Species from the U.S. and Canadian west coast including the Gulf of Alaska had the highest projected magnitude shifts in distribution, and many species shifted more than 1000 km under the high greenhouse gas emissions scenario. Following a strong mitigation scenario consistent with the Paris Agreement would likely produce substantially smaller shifts and less disruption to marine management efforts. Our projections offer an important tool for identifying species, fisheries, and management efforts that are particularly vulnerable to climate change impacts.