Mapping functional traits: comparing abundance and presence-absence estimates at large spatial scales

Efforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition – overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question – and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R2: 5.6×10−7 to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R2: 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities

Mapping functional traits: comparing bundance and presence-absence estimates at large spatial scales

journal articleEfforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition - overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question - and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R2: 5.661027 to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R2: 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities

Widespread winners and narrow-ranged losers: land use homogenizes biodiversity in local assemblages worldwide

Human use of the land (for agriculture and settlements) has a substantial negative effect on biodiversity globally. However, not all species are adversely affected by land use, and indeed, some benefit from the creation of novel habitat. Geographically rare species may be more negatively affected by land use than widespread species, but data limitations have so far prevented global multi-clade assessments of land-use effects on narrow-ranged and widespread species. We analyse a large, global database to show consistent differences in assemblage composition. Compared with natural habitat, assemblages in disturbed habitats have more widespread species on average, especially in urban areas and the tropics. All else being equal, this result means that human land use is homogenizing assemblage composition across space. Disturbed habitats show both reduced abundances of narrow-ranged species and increased abundances of widespread species. Our results are very important for biodiversity conservation because narrow-ranged species are typically at higher risk of extinction than widespread species. Furthermore, the shift to more widespread species may also affect ecosystem functioning by reducing both the contribution of rare species and the diversity of species’ responses to environmental changes among local assemblages

Geography and availability of natural habitat determine whether cropland intensification or expansion is more detrimental to biodiversity

To mitigate biodiversity loss from agriculture, intensification is often promoted as an alternative to farmland expansion. However, its local impacts remain debated. We assess globally the responses of three biodiversity metrics—species richness, total abundance and relative community abundance-weighted average range size (RCAR), a proxy for biotic homogenization—to land conversion and yield increases. Our models predict a median species loss of 11% in primary vegetation in modified landscapes, and of 25% and 40% in cropland within natural and modified landscapes, respectively. Land conversion also reduces abundance and increases biotic homogenization, with impacts varying by geographic region and history of human modification. However, increasing yields changes biodiversity as well, including in adjacent primary vegetation, with effects dependent on crop, region, biodiversity metric and natural habitat cover. Ultimately, neither expansion nor intensification consistently benefits biodiversity. Intensification has better species richness outcomes in 29%, 83%, 64% and 57% of maize, soybean, wheat and rice landscapes, respectively, whereas expansion performs better in the remaining areas. In terms of abundance and RCAR, both expansion and intensification can outperform the other depending on landscape. Therefore, minimizing local biodiversity loss requires a context-dependent balance between expansion and intensification, while avoiding expansion in unmodified landscapes

Agriculture and climate change reshape insect biodiversity worldwide

Several previous studies have investigated changes in insect biodiversity, with some highlighting declines and others showing turnover in species composition without net declines1,2,3,4,5. Although research has shown that biodiversity changes are driven primarily by land-use change and increasingly by climate change6,7, the potential for interaction between these drivers and insect biodiversity on the global scale remains unclear. Here we show that the interaction between indices of historical climate warming and intensive agricultural land use is associated with reductions of almost 50% in the abundance and 27% in the number of species within insect assemblages relative to those in less-disturbed habitats with lower rates of historical climate warming. These patterns are particularly evident in the tropical realm, whereas some positive responses of biodiversity to climate change occur in non-tropical regions in natural habitats. A high availability of nearby natural habitat often mitigates reductions in insect abundance and richness associated with agricultural land use and substantial climate warming but only in low-intensity agricultural systems. In such systems, in which high levels (75% cover) of natural habitat are available, abundance and richness were reduced by 7% and 5%, respectively, compared with reductions of 63% and 61% in places where less natural habitat is present (25% cover). Our results show that insect biodiversity will probably benefit from mitigating climate change, preserving natural habitat within landscapes and reducing the intensity of agriculture

Species life‐history strategies affect population responses to temperature and land‐cover changes

Human-induced environmental changes have a direct impact on species populations, with some species experiencing declines while others display population growth. Understanding why and how species populations respond differently to environmental changes is fundamental to mitigate and predict future biodiversity changes. Theoretically, species life-history strategies are key determinants shaping the response of populations to environmental impacts. Despite this, the association between species life histories and the response of populations to environmental changes has not been tested. In this study, we analysed the effects of recent land-cover and temperature changes on rates of population change of 1,072 populations recorded in the Living Planet Database. We selected populations with at least 5 yearly consecutive records (after imputation of missing population estimates) between 1992 and 2016, and for which we achieved high population imputation accuracy (in the cases where missing values had to be imputed). These populations were distributed across 553 different locations and included 461 terrestrial amniote vertebrate species (273 birds, 137 mammals, and 51 reptiles) with different life-history strategies. We showed that populations of fast-lived species inhabiting areas that have experienced recent expansion of cropland or bare soil present positive populations trends on average, whereas slow-lived species display negative population trends. Although these findings support previous hypotheses that fast-lived species are better adapted to recover their populations after an environmental perturbation, the sensitivity analysis revealed that model outcomes are strongly influenced by the addition or exclusion of populations with extreme rates of change. Therefore, the results should be interpreted with caution. With climate and land-use changes likely to increase in the future, establishing clear links between species characteristics and responses to these threats is fundamental for designing and conducting conservation actions. The results of this study can aid in evaluating population sensitivity, assessing the likely conservation status of species with poor data coverage, and predicting future scenarios of biodiversity change

The value of species distribution models as a tool for conservation and ecology in Egypt and Britain

Knowledge about the distribution of species is limited, with extensive gaps in our knowledge, particularly in tropical areas and in arid environments. Species distribution models offer a potentially very powerful tool for filling these gaps in our knowledge. They relate a set of recorded occurrences of a species to environmental variables thought to be important in determining the distributions of species, in order to predict where species will be found throughout an area of interest. In this thesis, I explore the development, potential applications and possible limitations of distribution models using species from various taxonomic groups in two regions of the world: butterflies, mammals, reptiles and amphibians in Egypt, and butterflies, hoverflies and birds in Great Britain. Specifically I test: 1) which modelling methods produce the best models; 2) which variables correlate best with the distributions of species, and in particular whether interactions among species can explain observed distributions; 3) whether the distributions of some species correlate better with environmental variables than others and whether this variation can be explained by ecological characteristics of the species; 4) whether the same environmental variables that explain species’ occurrence can also explain species richness, and whether distribution models can be combined to produce an accurate model of species richness; 5) whether the apparent accuracy of distribution models is supported by ground-truthing; and 6) whether the models can predict the impact of climate change on the distribution of species. Overall the use of distribution models is supported; my models for species in both Egypt and Britain explained observed occurrence very well. My results shed some light on factors that may be important in determining the distributions of species, particularly on the importance of interactions among species. As they currently stand, distribution models appear unable to predict accurately the impacts of climate change

Large language models help facilitate the automated synthesis of information on potential pest controllers

The body of ecological literature, which informs much of our knowledge of the global loss of biodiversity, has been experiencing rapid growth in recent decades. The increasing difficulty of synthesising this literature manually has simultaneously resulted in a growing demand for automated text mining methods. Within the domain of deep learning, large language models (LLMs) have been the subject of considerable attention in recent years due to great leaps in progress and a wide range of potential applications; however, quantitative investigation into their potential in ecology has so far been lacking. In this work, we analyse the ability of GPT‐4 to extract information about invertebrate pests and pest controllers from abstracts of articles on biological pest control, using a bespoke, zero‐shot prompt. Our results show that the performance of GPT‐4 is highly competitive with other state‐of‐the‐art tools used for taxonomic named entity recognition and geographic location extraction tasks. On a held‐out test set, we show that species and geographic locations are extracted with F1‐scores of 99.8% and 95.3%, respectively, and highlight that the model can effectively distinguish between ecological roles of interest such as predators, parasitoids and pests. Moreover, we demonstrate the model's ability to effectively extract and predict taxonomic information across various taxonomic ranks. However, we do report a small number of cases of fabricated information (confabulations). Due to a lack of specialised, pre‐trained ecological language models, general‐purpose LLMs may provide a promising way forward in ecology. Combined with tailored prompt engineering, such models can be employed for a wide range of text mining tasks in ecology, with the potential to greatly reduce time spent on manual screening and labelling of the literature

Prioritizing conservation in sub-Saharan African lakes based on freshwater biodiversity and algal bloom metrics

As agricultural land-use and climate change continue to pose increasing threats to biodiversity in sub-Saharan Africa, efforts are being made to identify areas where trade-offs between future agricultural development and terrestrial biodiversity conservation are expected to be greatest. However, little research so far has focused on freshwater biodiversity conservation in the context of agricultural development in sub-Saharan Africa. Here, we aim to prioritize areas where freshwater biodiversity is most likely to be affected by the effects of eutrophication and Harmful Algal Blooms (i.e., when algae multiple to the extent that they cause toxic effects on people and freshwater fauna), some of the most important emerging threats to freshwater ecosystems worldwide with the onset of climate change. Using novel remote-sensing techniques, we identify lakes with overlap between high biodiversity and algal blooms, which are likely to signal negative impacts on freshwater systems. By calculating the richness of freshwater species and the Normalized Difference Chlorophyll Index (NDCI), we identify 169 'priority lakes' in Ghana, Ethiopia, Zambia and bordering countries with which they share watersheds. Our results give the first assessment of where freshwater biodiversity may be most threatened by algal blooms in these three sub-Saharan countries, highlighting Zambian lakes as those at greatest risk. Our findings emphasize that threats to freshwater biodiversity occur at the watershed scale, often extending beyond a country's political boundaries. We highlight the importance of water resource management and freshwater biodiversity conservation at the watershed scale, emphasizing the importance of collaborative conservation action across country borders. We also demonstrate the potential of remote-sensing tools for prioritizing freshwater systems for conservation according to algal-bloom risk, vital in remote, under-sampled regions of the world, especially given the increasing threat posed to freshwater biodiversity by rapidly expanding agriculture and climate change. Article Impact Statement: Spatial analysis reveals areas of overlap between freshwater biodiversity and potentially harmful algal blooms in Ghana, Ethiopia, and Zambia