The Return of Large Dams to the Development Agenda: A Post-Development Critique

Large dams are making a comeback. Large dams reflect an outdated development paradigm narrowly focused on economic growth through modernization. This article employs a post-development lens to highlight three biases of the narrow development perspective that underlies large dams. First, it views rivers, and nature more generally, as an unrealized source of economic growth and an input to production. Second, it is blind to distributional impacts and is resultantly inequitable: the benefits of large dams are concentrated in the hands of the wealthy, while conditions for the poor do not improve and often worsen. Third, it disempowers those supposedly being developed by de-politicizing the development decisions to pursue large dam projects. Each of these biases is illustrated by reference to the Mekong River Basin’s experience with large dam development. It is concerning, therefore, that large dams seem to be making a resurgence in Asia, Africa and South America, and are once again receiving World Bank support. This article serves as a reminder of why large dams do not deliver equitable development and faded from the development agenda at the turn of the century

Comparison of manual, machine learning, and hybrid methods for video annotation to extract parental care data

Measuring parental care behaviour in the wild is central to the study of animal ecology and evolution, but it is often labour- and time-intensive. Efficient open-source tools have recently emerged that allow animal behaviour to be quantified from videos using machine learning and computer vision techniques, but there is limited appraisal of how these tools perform compared to traditional methods. To gain insight into how different methods perform in extracting data from videos taken in the field, we compared estimates of the parental provisioning rate of wild house sparrows Passer domesticus from video recordings. We compared four methods: manual annotation by experts, crowd-sourcing, automatic detection based on the open-source software DeepMeerkat, and a hybrid annotation method. We found that the data collected by the automatic method correlated with expert annotation (r = 0.62) and further show that these data are biologically meaningful as they predict brood survival. However, the automatic method produced largely biased estimates due to the detection of non-visitation events, while the crowd-sourcing and hybrid annotation produced estimates that are equivalent to expert annotation. The hybrid annotation method takes approximately 20% of annotation time compared to manual annotation, making it a more cost-effective way to collect data from videos. We provide a successful case study of how different approaches can be adopted and evaluated with a pre-existing dataset, to make informed decisions on the best way to process video datasets. If pre-existing frameworks produce biased estimates, we encourage researchers to adopt a hybrid approach of first using machine learning frameworks to preprocess videos, and then to do manual annotation to save annotation time. As open-source machine learning tools are becoming more accessible, we encourage biologists to make use of these tools to cut annotation time but still get equally accurate results without the need to develop novel algorithms from scratch

The EDGE2 protocol: Advancing the prioritisation of Evolutionarily Distinct and Globally Endangered species for practical conservation action

The conservation of evolutionary history has been linked to increased benefits for humanity and can be captured by phylogenetic diversity (PD). The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to prioritise threatened species for practical conservation that embody large amounts of evolutionary history. While there have been important research advances since 2007, they have not been adopted in practice because of a lack of consensus in the conservation community. Here, building from an interdisciplinary workshop to update the existing EDGE approach, we present an “EDGE2” protocol that draws on a decade of research and innovation to develop an improved, consistent methodology for prioritising species conservation efforts. Key advances include methods for dealing with uncertainty and accounting for the extinction risk of closely related species. We describe EDGE2 in terms of distinct components to facilitate future revisions to its constituent parts without needing to reconsider the whole. We illustrate EDGE2 by applying it to the world’s mammals. As we approach a crossroads for global biodiversity policy, this Consensus View shows how collaboration between academic and applied conservation biologists can guide effective and practical priority-setting to conserve biodiversity

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

pez: Phylogenetics for the Environmental Sciences

Summary: pez is an R package that permits measurement, modelling and simulation of phylogenetic structure in ecological data. pez contains the first implementation of many methods in R, and aggregates existing data structures and methods into a single, coherent package

Building up biogeography: Pattern to process

Linking pattern to process across spatial and temporal scales has been a key goal of the field of biogeography. In January 2017, the 8th biennial conference of the International Biogeography Society sponsored a symposium on Building up biogeography—process to pattern that aimed to review progress towards this goal. Here we present a summary of the symposium, in which we identified promising areas of current research and suggested future research directions. We focus on (1) emerging types of data such as behavioural observations and ancient DNA, (2) how to better incorporate historical data (such as fossils) to move beyond what we term “footprint measures” of past dynamics and (3) the role that novel modelling approaches (e.g. maximum entropy theory of ecology and approximate Bayesian computation) and conceptual frameworks can play in the unification of disciplines. We suggest that the gaps separating pattern and process are shrinking, and that we can better bridge these aspects by considering the dimensions of space and time simultaneously