Invasion of freshwater ecosystems is promoted by network connectivity to hotspots of human activity

Aim: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. Location: England, UK. Time period: 1990–2018. Major taxa studied: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. Methods: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. Results: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. Main conclusions: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing alternative connectivity types for different human activities, our approach could enable robust inference of specific pathways and spread mechanisms associated with particular taxa. This would provide evidence to support better prioritization of surveillance and management for invasive non‐native species

Thresholds of fire response to moisture and fuel load differ between tropical savannas and grasslands across continents

Aim An emerging framework for tropical ecosystems states that fire activity is either “fuel build‐up limited” or “fuel moisture limited”, that is, as you move up along rainfall gradients, the major control on fire occurrence switches from being the amount of fuel, to the moisture content of the fuel. Here we used remotely sensed datasets to assess whether interannual variability of burned area is better explained by annual rainfall totals driving fuel build‐up, or by dry season rainfall driving fuel moisture. Location Pantropical savannas and grasslands. Time period 2002–2016. Methods We explored the response of annual burned area to interannual variability in rainfall. We compared several linear models to understand how fuel moisture and fuel build‐up effect (accumulated rainfall during 6 and 24 months prior to the end of the burning season, respectively) determine the interannual variability of burned area and explore if tree cover, dry season duration and human activity modified these relationships. Results Fuel and moisture controls on fire occurrence in tropical savannas varied across continents. Only 24% of South American savannas were fuel build‐up limited against 61% of Australian savannas and 47% of African savannas. On average, South America switched from fuel limited to moisture limited at 500 mm/year, Africa at 800 mm/year and Australia at 1,000 mm/year of mean annual rainfall. Main conclusions In 42% of tropical savannas (accounting for 41% of current area burned) increased drought and higher temperatures will not increase fire, but there are savannas, particularly in South America, that are likely to become more flammable with increasing temperatures. These findings highlight that we cannot transfer knowledge of fire responses to global change across ecosystems/regions—local solutions to local fire management issues are required, and different tropical savanna regions may show contrasting responses to the same drivers of global change

Global patterns of interannual climate–fire relationships

Climate shapes geographic and seasonal patterns in global fire activity by mediating vegetation composition, productivity, and desiccation in conjunction with land-use and anthropogenic factors. Yet, the degree to which climate variability affects interannual variability in burned area across Earth is less understood. Two decades of satellite-derived burned area records across forested and nonforested areas were used to examine global interannual climate-fire relationships at ecoregion scales. Measures of fuel aridity exhibited strong positive correlations with forested burned area, with weaker relationships in climatologically drier regions. By contrast, cumulative precipitation antecedent to the fire season exhibited positive correlations to nonforested burned area, with stronger relationships in climatologically drier regions. Climate variability explained roughly one-third of the interannual variability in burned area across global ecoregions. These results highlight the importance of climate variability in enabling fire activity globally, but also identify regions where anthropogenic and other influences may facilitate weaker relationships. Empirical fire modeling efforts can complement process-based global fire models to elucidate how fire activity is likely to change amidst complex interactions among climatic, vegetation, and human factors

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC‐NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC‐ NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction

Can local landscape attributes explain species richness patterns at macroecological scales?

Although the influence on species richness of landscape attributes representing landscape composition and spatial configuration has been well documented at landscape scales, its effects remain little understood at macroecological scales. We aim to assess the role of landscape attributes, and their relative importance compared with climate, habitat heterogeneity and human influence (CHH) in particular, in shaping broad-scale richness patterns