新疆吉木萨尔县蝴蝶群落多样性

蝴蝶作为指示生物, 被广泛地应用于生物多样性监测及环境质量评估。探究新疆吉木萨尔县蝴蝶群落多样性, 可为当地蝴蝶多样性的保护及环境监测提供基础数据。本研究采用样线法在新疆吉木萨尔县选取山前荒漠、农田、山地草原、山地森林、亚高山草甸5种不同的生境类型, 对蝴蝶种类和群落多样性进行调查。共记录蝴蝶4,401号, 隶属于7科26属38种。其中蛱蝶科有9属12种, 为优势科; 粉蝶科的个体数最多, 占比55.01%; 绢蝶科、凤蝶科和弄蝶科的种类数和个体数最少, 均为单科种, 是该地区的稀有类群。对不同生境蝴蝶群落多样性和相似度分析比较的结果显示: 5种生境中多样性指数从高到低依次为亚高山草甸、山地森林、山地草原、农田及山前荒漠, 其中山地森林和亚高山草甸的相似性系数较高, 达到0.77, 山前荒漠和山地草原的相似性系数最低, 为0.37。蝴蝶物种数及多样性指数随海拔的增加呈上升趋势。蝴蝶群落随月份发生变化, 蝴蝶种类和数量在5月发生、7月达到峰值。蝶类个体数在3年内呈下降趋势。研究结果表明, 蝴蝶物种的组成和多样性与生境类型具有密切联系, 保护生态环境, 维持该地区植物群落的多样性、降低人为干扰程度是保护蝶类多样性的关键。     

What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.     

鄂西南木林子常绿落叶阔叶混交林2014~2019年主要物种动态变化

为了明确鄂西南木林子亚热带山地常绿落叶阔叶混交林的短期群落动态,为该区森林生态的保护、恢复与可持续经营提供科学依据。该研究基于木林子自然保护区2.2 hm²动态监测样地,以2014和2019年样地内所有胸径(DBH)≥1 cm的木本植物为研究对象,从物种组成与多样性、重要值、死亡率、补员率及胸径等方面分析了其动态变化。结果表明：(1)5年间2.2 hm²样地内木本植物个体从17 308株减少到16 533株,降幅为4.48%,胸高断面积31.42 m²·hm^-2增长到35.53 m²·hm^-2,物种增加了1科6属18种,消失1属7种。 乔木、亚乔木、灌木及藤本4类生长型物种的Margalef丰富度指数均上升,而Pielou均匀度指数均下降;除乔木外其他3种生长型的Shannon Wiener多样性指数和Simpson指数均上升。(2)补员个体1 269株,平均胸径2.44 cm,胸高断面积为0.32 m²·hm^-2,平均新增115.36 株·hm^-2·a^-1,隶属39科59属99种;死亡个体2 044株,平均胸径3.32 cm,胸高段面积为1.31 m²·hm^-2,平均死亡185.82 株·hm^-2·a^-1,隶属51科90属146种;不同径级补员与死亡个体数差异明显,总体上随着径级的增大而减少。(3)46个主要物种中有15种重要值增大,有31种降低,增加与降低的变化幅度为乔木层>灌木层>亚乔木层;平均胸径从4.70 cm上升为5.12 cm,除锥栗(Castanea henryi)平均胸径有所下降外其他物种均上升。(4)主要树种中有44个为增长型种群,另外2个物种种群增长率不变,主要物种年补员率大于年死亡率,不同生长型物种及其不同径级的死亡率与补员率不同,不同径级补员率总体大于死亡率;随着径级的增大,补员率与死亡率的差值逐渐降低趋于平缓。研究认为,该群落物种组成与多样性及主要物种的重要值、平均胸径变化幅度较小,未发生明显波动,主要物种不同径级的更新动态有所差别,但不剧烈,因此整个群落外貌基本保持不变,发展较为稳定。     

Long‐term persistence of wildlife populations in a pastoral area

Facilitating coexistence between people and wildlife is a major conservation challenge in East Africa. Some conservation models aim to balance the needs of people and wildlife, but the effectiveness of these models is rarely assessed. Using a case‐study approach, we assessed the ecological performance of a pastoral area in northern Tanzania (Manyara Ranch) and established a long‐term wildlife population monitoring program (carried out intermittently from 2003 to 2008 and regularly from 2011 to 2019) embedded in a distance sampling framework. By comparing density estimates of the road transect‐based long‐term monitoring to estimates derived from systematically distributed transects, we found that the bias associated with nonrandom placement of transects was nonsignificant. Overall, cattle and sheep and goat reached the greatest densities and several wildlife species occurred at densities similar (zebra, wildebeest, waterbuck, Kirk's dik‐dik) or possibly even greater (giraffe, eland, lesser kudu, Grant's gazelle, Thomson's gazelle) than in adjacent national parks in the same ecosystem. Generalized linear mixed models suggested that most wildlife species (8 out of 14) reached greatest densities during the dry season, that wildlife population densities either remained constant or increased over the 17‐year period, and that herbivorous livestock species remained constant, while domestic dog population decreased over time. Cross‐species correlations did not provide evidence for interference competition between grazing or mixed livestock species and wildlife species but indicate possible negative relationships between domestic dog and warthog populations. Overall, wildlife and livestock populations in Manyara Ranch appear to coexist over the 17‐year span. Most likely, this is facilitated by existing connectivity to adjacent protected areas, effective anti‐poaching efforts, spatio‐temporal grazing restrictions, favorable environmental conditions of the ranch, and spatial heterogeneity of surface water and habitats. This long‐term case study illustrates the potential of rangelands to simultaneously support wildlife conservation and human livelihood goals if livestock grazing is restricted in space, time, and numbers.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

Metapopulation dynamics and foraging plasticity in a highly vagile seabird,the southern rockhopper penguin

Population connectivity is driven by individual dispersal potential and modulated by natal philopatry. In seabirds, high vagility facilitates dispersal yet philopatry is also common, with foraging area overlap often correlated with population connectivity. We assess the interplay between these processes by studying past and current connectivity and foraging niche overlap among southern rockhopper penguin colonies of the coast of southern South America using genomic and stable isotope analyses. We found two distinct genetic clusters and detected low admixture between northern and southern colonies. Stable isotope analysis indicated niche variability between colonies, with Malvinas/Falklands colonies encompassing the species entire isotopic foraging niche, while the remaining colonies had smaller, nonoverlapping niches. A recently founded colony in continental Patagonia differed in isotopic niche width and position with Malvinas/Falklands colonies, its genetically identified founder population, suggesting the exploitation of novel foraging areas and/or prey items. Additionally, dispersing individuals found dead across the Patagonian shore in an unusual mortality event were also assigned to the northern cluster, suggesting northern individuals reach southern localities, but do not breed in these colonies. Facilitated by variability in foraging strategies, and especially during unfavorable conditions, the number of dispersing individuals may increase and enhance the probability of founding new colonies. Metapopulation demographic dynamics in seabirds should account for interannual variability in dispersal behavior and pay special attention to extreme climatic events, classically related to negative effects on population trends.     

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.     

Exploring context dependency in eco‐evolutionary patterns with the stick insect Timema cristinae

Rapid evolution can influence the ecology of populations, communities, and ecosystems, but the importance of evolution for ecological dynamics remains unclear, largely because the contexts in which evolution is powerful are poorly resolved. Here, we carry out a large observational study to test hypotheses about context dependency of eco‐evolutionary patterns previously identified on the stick insect Timema cristinae. Experiments and observations conducted in 2011 and 2012 documented predator‐mediated negative effects of camouflage maladaptation (i.e., evolutionary dynamics) on: (a) T. cristinae abundance and, (b) species richness and abundance of other arthropods. Here we show that camouflage maladaptation does not correlate with T. cristinae abundance and, instead, is associated with increased abundance and species richness of cohabitating arthropods. We furthermore find that plants with high levels of Timema maladaptation tend to have higher foliar nitrogen, that is, higher nutritional value, and more positive mass‐abundance slopes in the coexisting arthropod communities. We propose explanations for the observed contrasting results, such as negative density‐ and frequency‐dependent selection, feedbacks between herbivore abundance and plant nutritional quality, and common effects of predation pressure on selection and prey abundance. Our results demonstrate the utility of observational studies to assess the context dependency of eco‐evolutionary dynamics patterns and provide testable hypotheses for future work.     

Travel with your kin ship! Insights from genetic sibship among settlers of a coral damselfish

Coral reef fish larvae are tiny, exceedingly numerous, and hard to track. They are also highly capable, equipped with swimming and sensory abilities that may influence their dispersal trajectories. Despite the importance of larval input to the dynamics of a population, we remain reliant on indirect insights to the processes influencing larval behavior and transport. Here, we used genetic data (300 independent single nucleotide polymorphisms) derived from a light trap sample of a single recruitment event of Dascyllus abudafur in the Red Sea (N = 168 settlers). We analyzed the genetic composition of the larvae and assessed whether kinship among these was significantly different from random as evidence for cohesive dispersal during the larval phase. We used Monte Carlo simulations of similar‐sized recruitment cohorts to compare the expected kinship composition relative to our empirical data. The high number of siblings within the empirical cohort strongly suggests cohesive dispersal among larvae. This work highlights the utility of kinship analysis as a means of inferring dynamics during the pelagic larval phase.     

Drought conditions alter litter decomposition and nutrient release of litter types in an agroforestry system of China

Evaluating how decomposition rates and litter nutrient release of different litter types respond to changes in water conditions is crucial for understanding global carbon and nutrient cycling. However, it is unclear how decreasing water affects litter mixture interactions for the maize–poplar system in arid regions. Here, the responses of the litter decomposition process and litter mixture interactions in the agroforestry system to changes in water conditions (control, light drought, and moderate drought) were tested. Moderate drought significantly decreased the decomposition rate for poplar leaf and mixed litters, and decomposition rate was significantly reduced for maize straw litter in light and moderate drought stress. The mass loss rates of maize straw and mixed litters were significantly higher than that of the poplar leaf litter under drought conditions, but there was no significant difference among the three litter types in the control. There was no interaction between mass loss of the mixed litter in the control and light drought conditions, and the litter mixture interaction showed nonadditive synergistic interactions under moderate drought. In terms of nutrient release, there was also no interaction between litter mixture with nitrogen and carbon, but there was antagonistic interaction with potassium release under the light drought condition. Our results demonstrate that drought conditions can lead to decreasing decomposition rate and strong changes in the litter mixture interactions from additive effects to nonadditive synergistic effects in moderate drought. Moreover, light drought changed the mixture interaction from an additive effect to an antagonistic interaction for potassium release.