Seasonal dynamics of plant pollinator networks in agricultural landscapes: how important is connector species identity in the network?

Scavengers in the human-dominated landscape: an experimental study

Rapid urbanization is a major cause of habitat and biodiversity loss and human-animal conflict. While urbanization is inevitable, we need to develop a good understanding of the urban ecosystem and the urban-adapted species, in order to ensure sustainable cities for our future. Scavengers play a major role in urban ecosystems, and often, urban adaptation involves a shift towards scavenging behaviour in wild animals. We experimented at different sites in the state of West Bengal, India, to identify the scavenging guild within urban habitats, in response to human-provided food. Our study found a total of 17 different vertebrate species across 15 sites, over 498 sessions of observations. We carried out network analysis to understand the dynamics of the system and found that the free-ranging dog and common myna were key species within the scavenging networks. This study revealed the complexity of scavenging networks within human-dominated habitats. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Exploring spatiotemporal dynamics of flower visitor association pattern on two Avicennia mangroves: a network approach

Plant-flower visitor interaction is one of the most important relationships regarding the co-existence of the floral and faunal communities. The implication of network approaches is an efficient way to understand the impact of community structure on ecosystem functionality. To understand the association pattern of flower visitors, we performed this study on Avicennia officinalis and Avicennia marina mangroves from the islands of Indian Sundarban over three consecutive years. We found that visiting time and sites (islands) influenced the abundance of visitors. The bipartite networks showed a significant generalized structure for both site-visitor and visiting time-visitor networks where the strength and specialization of visitor species showed a highly and moderately significant positive correlation between both networks respectively. All the site-wise visiting time-visitor networks and year-wise site-visitor networks were significantly modular in structure. For both the plants, most of the visitors showed a generalized association pattern among islands and also among visiting times. Additionally, the study of the foraging behavior of dominant visitors showed Apis dorsata and Apis mellifera as the potential visitors for these plants. Our results showed that flower visitor networks are spatiotemporally dynamic. The interactions of visitors with flowers at different times influence their contribution to the network for becoming a generalist or peripheral species in the context of their visiting time, which may subsequently change over islands. This approach will help to devise more precise plant species-specific conservation strategies by understanding the contribution of visitors through the spatiotemporal context.

Remote Sensing of Floral Resources for Pollinators – New Horizons From Satellites to Drones

Insect pollinators are affected by the spatio-temporal distribution of floral resources, which are dynamic across time and space, and also influenced heavily by anthropogenic activities. There is a need for spatial data describing the time-varying spatial distribution of flowers, which can be used within behavioral and ecological studies. However, this information is challenging to obtain. Traditional field techniques for mapping flowers are often laborious and limited to relatively small areas, making it difficult to assess how floral resources are perceived by pollinators to guide their behaviors. Conversely, remote sensing of plant traits is a relatively mature technique now, and such technologies have delivered valuable data for identifying and measuring non-floral dynamics in plant systems, particularly leaves, stems and woody biomass in a wide range of ecosystems from local to global scales. However, monitoring the spatial and temporal dynamics of plant floral resources has been notably scarce in remote sensing studies. Recently, lightweight drone technology has been adopted by the ecological community, offering a capability for flexible deployment in the field, and delivery of centimetric resolution data, providing a clear opportunity for capturing fine-grained information on floral resources at key times of the flowering season. In this review, we answer three key questions of relevance to pollination science – can remote sensing deliver information on (a) how isolated are floral resources? (b) What resources are available within a flower patch? And (c) how do floral patches change over time? We explain how such information has potential to deepen ecological understanding of the distribution of floral resources that feed pollinators and the parameters that determine their navigational and foraging choices based on the sensory information they extract at different spatial scales. We provide examples of how such data can be used to generate new insights into pollinator behaviors in distinct landscape types and their resilience to environmental change.

Settling moths are the vital component of pollination in Himalayan ecosystem of North-East India, pollen transfer network approach revealed

Majority of the pollination related studies are based on the diurnal pollinators, and the nocturnal pollinators received less scientific attention. We reveal the significance of settling moths in pollination of angiosperm families in Himalayan ecosystem of North-East India. The refined and novel method of pollen extraction from the proboscides provides a more robust assessment of the pollen carrying capacity. The study is based on one of the largest data sets (140 pollen transporter moth species (PTMS)), with interpretation based on seasonal as well as altitudinal data. In the present study about 65% moths (91 species) carried sufficient quantities of pollen grains to be considered as potential pollinators (PPMS). Teliphasa sp. (Crambidae) and Cuculia sp. (Noctuidae) are found to carry the highest quantity of pollen. We found pollen grains of 21 plant families and the abundant pollen are from Betulaceae, Fabaceae, Rosaceae and Ericaceae. Species composition of PTMS and PPMS in pre-monsoon, monsoon, and post-monsoon revealed the dominance of Geometridae. Maximum diversity of PTMS and PPMS is found from 2000 to 2500 m altitude. The nocturnal pollen transfer network matrices exhibited high degree of selectivity (H₂' = 0.86).

Selection of Non-Crop Plant Mixes Informed by Arthropod-Plant Network Analyses for Multiple Ecosystem Services Delivery Towards Ecological Intensification of Agriculture

Ecological intensification (EI) of agriculture through the improvement of ecosystem service delivery has recently emerged as the alternative to the conventional intensification of agriculture that is widely considered unsustainable and has negative impacts on the environment. Although tropical agricultural landscapes are still heterogeneous, they are rapidly losing diversity due to agricultural intensification. Restoration of natural or semi-natural habitats, habitat diversity, and provision of multiple benefits have been identified as important targets for the transition to EI. Choosing the right plant mixes for the restoration of habitats that can offer multiple ecosystem service benefits is therefore crucial. The selection of candidate species for plant mixes is generally informed by studies focusing on a specific ecosystem service (e.g., pollination) and not based on the whole arthropod—non-crop plant interactions matrix. In this study, we try to identify non-crop plant mixes that would provide habitat for pollinators, act as refugia for natural pest predators, and also as a trap crop for potential crop pests by studying non-crop plants—arthropod interaction network. We have identified the non-crop plant species mixes by first identifying the connector species based on their centrality in the network and then by studying how their sequential exclusions affect the stability of the network.