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Seagrass systems of the Western Pacific region are biodiverse habitats, providing vital services to ecosystems and humans over a vast geographic range. SeagrassNet is a worldwide monitoring program that collects data on seagrass habitats, including the ten locations across the Western Pacific reported here where change at various scales was rapidly detected. Three sites remote from human influence were stable. Seagrasses declined largely due to increased nutrient loading (4 sites) and increased sedimentation (3 sites), the two most common stressors of seagrass worldwide. Two sites experienced near-total loss from of excess sedimentation, followed by partial recovery once sedimentation was reduced. Species shifts were observed at every site with recovering sites colonized by pioneer species. Regulation of watersheds is essential if marine protected areas are to preserve seagrass meadows. Seagrasses in the Western Pacific experience stress due to human impacts despite the vastness of the ocean area and low development pressures.

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the “high hazardous” category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures.

Alpine and arctic lemming populations appear to be highly sensitive to climate change, and when faced with warmer and shorter winters, their well-known high-amplitude population cycles may collapse. Being keystone species in tundra ecosystems, changed lemming dynamics may convey significant knock-on effects on trophically linked species. Here, we analyse long-term (1988–2010), community-wide monitoring data from two sites in high-arctic Greenland and document how a collapse in collared lemming cyclicity affects the population dynamics of the predator guild. Dramatic changes were observed in two highly specialized lemming predators: snowy owl and stoat. Following the lemming cycle collapse, snowy owl fledgling production declined by 98 per cent, and there was indication of a severe population decline of stoats at one site. The less specialized long-tailed skua and the generalist arctic fox were more loosely coupled to the lemming dynamics. Still, the lemming collapse had noticeable effects on their reproductive performance. Predator responses differed somewhat between sites in all species and could arise from site-specific differences in lemming dynamics, intra-guild interactions or subsidies from other resources. Nevertheless, population extinctions and community restructuring of this arctic endemic predator guild are likely if the lemming dynamics are maintained at the current non-cyclic, low-density state.

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.

This study examined the potential use of macroalgae epiphytic on mangrove aerial roots as indicators of estuarine contamination. The distribution and abundance of macroalgae was investigated in four estuaries in the vicinity of Sydney, Australia, and compared to water and sediment metal concentrations, nutrient concentrations and physicochemical parameters over four seasonal surveys. Macroalgal diversity and distribution appeared to be highly influenced by the ambient contaminant concentrations, while biomass appeared to be linked with nutrient concentrations. The distribution of the Rhodophyta species, Catenella nipae Zanardini significantly decreased as metal concentrations increased among the estuaries during all seasonal surveys. This species showed strong potential for use as a bioindicator of estuarine contamination.

Featured paper: See Editorial p553

AbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.