José Alfredo Caro

Without appropriate and ongoing management interventions, weeds will continue to economically and environmentally disadvantage agricultural and natural ecosystems. For these management strategies to have long‐term sustained success, they need to carefully consider the biological aspects of the targeted weed. These strategies will also need to consider potential adaptations evolved by the targeted weed in response to a range of selection pressures imposed by anthropogenetic factors, climate change, changing environmental conditions, and inappropriate or unsuccessful management regimes. One group of weeds that has been observed to readily adapt to a wide range of conditions and has shown considerable challenges in their management is invasive grasses. Adding to these challenges is that several invasive grasses have also developed resistance to a range of herbicide modes of action, which, to date, has been one of the most commonly used methods of control. To address these challenges, this review explores the biology and ecology of the globally invasive annuals Echinochloa crus‐galli (Barnyard grass) and Panicum capillare (Witchgrass), and the perennial Sorghum halepense (Johnson grass) to identify (i) the most suitable management options for their control and (ii) potential research gaps that may assist in the future management direction of these species. Based on the findings of this review, it is clear that an integrated management approach that targets different aspects of the plant's biology, in combination with early detection and treatment and ongoing surveillance, is necessary for the long‐term control of these species. Although a combination of methods appears promising, further investigation still is required to evaluate their efficiency and long‐term success in a changing environment, all of which are further discussed within this review.

Lonicera japonica, an importante rsource plant, possesses significant medicinal, economic, and ecological value. To understand its response to climate change and to optimize its conservation and utilization, this study employed the Biomod2 ensemble model to predict its potential distribution under future climate scenarios and identified key environmental factors influencing its distribution. The results showed that under current climatic conditions, the potential distribution of honeysuckle is primarily concentrated in low-altitude regions of central and eastern China and the Sichuan Basin. In future scenarios, the overall distribution pattern changes less, and the area of highly suitable habitats slightly decreases by 0.80%. Distribution analysis indicated a trend of northward migration towards higher latitudes. Temperature-related factors, including temperature seasonality, the minimum temperature of the coldest month, the mean temperature of the coldest quarter, and the annual mean temperature, were identified as dominant factors affecting its distribution. The Biomod2 ensemble model significantly improved the precision and accuracy of suitability predictions compared to single models, providing a scientific basis for predicting the future geographic distribution of honeysuckle and for establishing and utilizing its cultivation regions in China.

Invasive sandburs (Cenchrus spp.), tropical and subtropical plants, are preferred in grasslands and agricultural ecosystems worldwide, causing significant crop production losses and reducing native biodiversity. Integrating phylogenetic relatedness and potentially suitable habitats (PSHs) to identify areas at risk of invasion is critical for prioritizing management efforts and supporting decisions on early warning and surveillance for sandbur invasions. However, despite risk assessments for individual Cenchrus species, the combined analysis of suitable habitats and phylogenetic relationships remains unclear. Therefore, this study aims to assess the invasion risk regions—including PSHs, species richness (SR), and phylogenetic structure—of eight invasive and potentially invasive sandburs in China, to quantify their niche overlap and identify driving factors. Our results showed that the phylogenetic distance of potentially invasive sandburs was closely related to invasive sandburs. Especially, three potentially invasive sandburs, C. ciliaris, C. setigerus, and C. myosuroides, possessed invasion potential resulting from close phylogenetic relatedness and high climatic suitability compared with invasive sandburs. The PSHs for invasive sandburs were distributed in wider regions except northwest China and had higher suitability to different environmental conditions. Potentially invasive sandburs were primarily located in southwestern and southern China driven by precipitation, especially, being inspected in Guangdong, Hainan, and Yunnan on numerous occasions, or potentially introduced in Guangxi, Taiwan, and Fujian for sandburs invasion hotspots. The phylogenetic clustering for eight sandburs occurred in the eastern, center, and southern coastal China, where higher SR in distribution was correlated with invasion hotspots. The SR and phylogenetic relatedness metrics were related to temperature and topographic variables. Totally, the expansion and invasion risk could be increased toward higher latitudes under future global warming. These findings offer novel insights for the prevention and management of sandburs invasions.

Abstract The Neotropics have been host to a myriad of geological and climatic events that have shaped the biodiversity present in the region. Bromeliaceae forms one of the most prominent components of the Neotropical flora, being considered the largest group nearly exclusive to the Americas, with almost 4000 species divided into eight subfamilies. Here, we utilize a new time-calibrated molecular phylogeny including 1268 bromeliad taxa and integrate habitat and morphological data to answer the following questions: (i) Are bromeliad subfamilies monophyletic, and did Neogene and Quaternary events in South America coincide with their divergence? (ii) Did naked seeds of berry-fruited species, epiphytic growth, and climatic factors increase bromeliad diversification? Our analysis reconstructed a new topology concerning some recently diverged lineages, with the genus Bromelia emerging as the sister group of a clade including all remaining Bromelioideae lineages + Puyoideae. Miocene events possibly triggered the diversification of bromeliads after a long period of stasis during the Palaeogene. We hypothesize that the morphological shift between Bromelia and Bromelioideae (except Bromelia) is related to the colonization of a new high-elevation environment by Puyoideae in the Andes. Additionally, our results show that naked seeds and the epiphytic growth form positively influence diversification rate, while precipitation, temperature, and elevation have a negative influence. We emphasize the importance of considering a variety of morphological and ecological features to enhance our understanding of bromeliad evolution.

In this study, we explored the distributions of grass genera in the Southern Cone (SC) of South America, applying several phylogenetic diversity (PD) metrics and randomization tests. Grasses appear to have been present in South America since their early evolution as tropical understory species more than 60 Ma. During the course of evolution, grasses have adapted to all terrestrial biomes and become one of the most successful plant families on earth. At present, the SC contains nearly all terrestrial biomes and a wide range of humid to arid ecoregions. Analyzing 126.514 point occurrences and four plastid markers for 148 genera (91% of the native grass genera), we found that tropical humid regions hold the highest PD, with no observed bias in branch lengths. These results indicate that niche conservatism dominates the diversity pattern of grasses in the SC. We found significantly low PD in the Dry Chaco and in the Patagonian Steppe, which suggest ecological filtering in both warm and cold arid regions. The Patagonian Steppe also holds significantly longer branches than expected by chance, as the native grass flora is mainly composed of distantly related Pooideae genera with a northern hemisphere origin. Short branches are found in the Uruguayan Savanna, suggesting that these grasslands could be a cradle for grass diversity within the SC. The dated phylogeny supported the current view of a relatively recent evolution of the family within the SC, with most diversification taking place from the middle Miocene and onwards.

Climate change could significantly affect the geographic distribution of plant species. Hedeoma multiflora is a vulnerable medicinal and aromatic herb that distributes in the Pampa, Espinal and Chaco biogeographic provinces in austral South America. This integrated approach combines ecological models and cytogenetic evidence to assess the effects of climate change on this species. Species distribution modelling using the Maxent model was implemented under current climatic conditions and three future climate change scenarios, integrating data from three Global Climate Models. The most suitable areas span 68,557 km2, encompassing the Sierras Pampeanas in San Luis and Córdoba provinces, and the Tandilia and Ventania systems in Buenos Aires, Argentina. The primary variables influencing the models include elevation (500 to 2000 m.a.s.l.), annual mean temperature (10 to 17 °C), annual precipitation (500 to 900 mm) and precipitation seasonality (50 to 75%). While the results project an expansion in the potential distribution of the species, heterogeneous patterns of range shifts are predicted across the three mountain systems: expansion in Sierras Pampeanas, march in Ventania and retraction in the Tandilia system. Variations in chromosome numbers within four distinct localities were reported, indicating the presence of polyploidy. This could potentially provide adaptive advantages in response to changing climates. This plant lives in habitats that face human-induced alterations and insufficient area protected coverage, then we propose strategies for both in situ and ex situ conservation of this medicinal species in each area.

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Drylands cover ca. 40% of the land global surface and deliver significant ecosystem services. These regions are the most sensitive, prone to suffer the effects of climate and distribution changes, so estimates on projected range shifts are crucial to complement traditional approaches to biodiversity conservation and sustainability. Shrubs of the Monte Desert dominate the largest temperate dryland in South America. Our goal is to assess the spatial distribution and niche overlap of three native shrubs (Larrea cuneifolia (LC), L. divaricata (LD), and L. nitida (LN)), under present climate conditions, to retrodict their potential past distribution, and anticipate their predicted range under future climate scenarios. We used ecological niche modeling that were projected to the past (LGM and Mid Holocene) and future (2050 and 2070) under two scenarios of greenhouse gas emissions and two model of global circulation. All species have high niche overlap (67–89%), but showed species-specific responses, highlighting the need to develop mitigation measures particularly for LD and LN in the face of climate change and land use pressures. Global South deserts are being highly degraded and information on future potential ranges of endemic species can support the development of sustainable conservation and management plans.

Camelina [Camelina sativa (L.) Crantz] is a Brassicaceae oilseed that is gaining interest worldwide as low‐maintenance crop for diverse biobased applications. One of the most important factors determining its productivity is climate. We conducted a bioclimate analysis in order to analyze the relationship between climatic factors and the productivity of spring‐type camelina seeded in the spring, and to identify regions of the world with potential for camelina in this scenario. Using the modelling tool CLIMEX, a bioclimatic model was developed for spring‐seeded spring‐type camelina to match distribution, reported seed yields and phenology records in North America. Distribution, yield, and phenology data from outside of North America were used as independent datasets for model validation and demonstrated that model projections agreed with published distribution records, reported spring‐seeded camelina yields, and closely predicted crop phenology in Europe, South America, and Asia. Sensitivity analysis, used to quantify the response of camelina to changes in precipitation and temperature, indicated that crop performance was more sensitive to moisture than temperature index parameters, suggesting that the yield potential of spring‐seeded camelina may be more strongly impacted by water‐limited conditions than by high temperatures. Incremental climate scenarios also revealed that spring‐seeded camelina production will exhibit yield shifts at the continental scale as temperature and precipitation deviate from current conditions. Yield data were compared with indices of climatic suitability to provide estimates of potential worldwide camelina productivity. This information was used to identify new areas where spring‐seeded camelina could be grown and areas that may permit expanded production, including eastern Europe, China, eastern Russia, Australia and New Zealand. Our model is the first to have taken a systematic approach to determine suitable regions for potential worldwide production of spring‐seeded camelina.

The popularization of citizen-science platforms has increased the amount of data available in a fine spatial and temporal resolution, which can be used to fill distribution knowledge gaps through probabilistic maps. In this study, we gathered expert-based information and used species distribution models to produce two independent maps of the greater rhea ( Rhea americana , Rheiformes, Rheidae) distribution in the state of Rio Grande do Sul, Brazil. We integrated municipality level detection/non-detection data from five citizen-science datasets into a Bayesian site occupancy model, accounting for false negatives, sampling effort, habitat covariates, and spatial autocorrelation. We addressed whether habitat (grassland and crop field cover, number of rural properties) and spatial autocorrelation explains the realized occurrence of the species and compared model-based and expert-based occurrence maps. The mean estimated percentage of occupied municipalities was 48% (239 out of 497 municipalities), whereas experts declared 21% of the municipalities (103) as occupied by the species. While both mapping approaches showed greater rhea presence in most municipalities of the Pampa biome, they disagreed in the majority of the municipalities in the Atlantic Forest, where more fieldwork must be undertaken. The greater rhea distribution was exclusively explained by the spatial autocorrelation component, suggesting that the species expanded its distribution towards the north of the state, reaching the Atlantic Forest, following deforestation and agriculture expansion.