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		<title>From pattern to process: estimating species interactions and driver-species relationships from count data</title>
		<link>https://methodsblog.com/2026/07/13/from-pattern-to-process-estimating-species-interactions-and-driver-species-relationships-from-count-data/</link>
					<comments>https://methodsblog.com/2026/07/13/from-pattern-to-process-estimating-species-interactions-and-driver-species-relationships-from-count-data/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Mon, 13 Jul 2026 15:23:45 +0000</pubDate>
				<category><![CDATA[Methods papers]]></category>
		<category><![CDATA[Biotic Interactions]]></category>
		<category><![CDATA[Environmental drivers]]></category>
		<category><![CDATA[modelling]]></category>
		<category><![CDATA[Paleoecology]]></category>
		<category><![CDATA[State-Space]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16548</guid>

					<description><![CDATA[Post provided by Quinn Asena Uncovering signals from the past Understanding interactions among organisms, and between organisms and their environment, has been a cornerstone of ecology as long as we have been busying ourselves with the lives of other species. How do plants and animals facilitate or compete with each other? How do they respond to the continuous challenge of changing climates or new neighbors? &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16548</post-id>
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		<title>Welcoming new Associate Editors to Methods in Ecology and Evolution</title>
		<link>https://methodsblog.com/2026/07/08/welcoming-new-associate-editors-to-methods-in-ecology-and-evolution/</link>
					<comments>https://methodsblog.com/2026/07/08/welcoming-new-associate-editors-to-methods-in-ecology-and-evolution/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Wed, 08 Jul 2026 16:30:53 +0000</pubDate>
				<category><![CDATA[Editor Profiles]]></category>
		<category><![CDATA[Journal updates]]></category>
		<category><![CDATA[Associate Editors]]></category>
		<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Editors]]></category>
		<category><![CDATA[evolution]]></category>
		<category><![CDATA[Journal]]></category>
		<category><![CDATA[Methods in Ecology and Evolution]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16554</guid>

					<description><![CDATA[Following an open call for applicants at the beginning of 2026, we are pleased to welcome 44 new Associate Editors to Methods in Ecology and Evolution. The researchers joining us span 18 different countries. We are really delighted to have further expanded the expertise on our board so that we can continue to promote the development of new methods in ecology and evolution. Welcome aboard! &#8230;]]></description>
		
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		<item>
		<title>Hybrid Forest Models: integrating mechanistic knowledge and data</title>
		<link>https://methodsblog.com/2026/07/07/hybrid-forest-models-integrating-mechanistic-knowledge-and-data/</link>
					<comments>https://methodsblog.com/2026/07/07/hybrid-forest-models-integrating-mechanistic-knowledge-and-data/#respond</comments>
		
		<dc:creator><![CDATA[plydtanthera]]></dc:creator>
		<pubDate>Tue, 07 Jul 2026 16:28:51 +0000</pubDate>
				<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Statistical methods]]></category>
		<category><![CDATA[Theoretical methods]]></category>
		<category><![CDATA[modelling]]></category>
		<category><![CDATA[community ecology]]></category>
		<category><![CDATA[Population Ecology]]></category>
		<category><![CDATA[Forest]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16539</guid>

					<description><![CDATA[Post provided by Yannek Käber and Maximilian Pichler We met at YOMOS, a workshop for early-career researchers and young modelers in ecology supported by the German Society for Ecology, and we came at modeling from opposite ends. Yannek builds dynamic forest models, which are mechanistic models that integrate decades of ecological reasoning about how trees grow, compete, and die. Max builds machine learning models for &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16539</post-id>
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	</item>
		<item>
		<title>Developing the Mothbox automated light trap</title>
		<link>https://methodsblog.com/2026/06/30/developing-the-mothbox-automated-light-trap/</link>
					<comments>https://methodsblog.com/2026/06/30/developing-the-mothbox-automated-light-trap/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Tue, 30 Jun 2026 14:06:08 +0000</pubDate>
				<category><![CDATA[Practical Tools]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[biodiversity]]></category>
		<category><![CDATA[Computer Vision]]></category>
		<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Insects]]></category>
		<category><![CDATA[Methods in Ecology and Evolution]]></category>
		<category><![CDATA[monitoring]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16477</guid>

					<description><![CDATA[Blog post provided by Hubert A. Szczygieł Origins Back in 2022, I was in Panama working on landscape-scale biodiversity monitoring. The system I was testing included a lot of standard approaches – for example trail cameras for mammals, point counts and passive acoustic monitoring for birds, and Gentry transects for trees. However, I realized that none of the standard insect monitoring methodologies work for large-scale &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16477</post-id>
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	</item>
		<item>
		<title>Forking anatomy: borrowing software’s best idea to build 3D atlases together</title>
		<link>https://methodsblog.com/2026/06/25/forking-anatomy-borrowing-softwares-best-idea-to-build-3d-atlases-together/</link>
					<comments>https://methodsblog.com/2026/06/25/forking-anatomy-borrowing-softwares-best-idea-to-build-3d-atlases-together/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Thu, 25 Jun 2026 11:13:07 +0000</pubDate>
				<category><![CDATA[Methods papers]]></category>
		<category><![CDATA[3D]]></category>
		<category><![CDATA[Anatomy]]></category>
		<category><![CDATA[collaboration]]></category>
		<category><![CDATA[Data Sharing]]></category>
		<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Methods in Ecology and Evolution]]></category>
		<category><![CDATA[Morphology]]></category>
		<category><![CDATA[software]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16525</guid>

					<description><![CDATA[Post provided by A. Murat Maga Picture a graduate student who has just spent eighty hours tracing the individual bones of a fish skull, slice by slice, through a high-resolution microCT scan. The result is a beautiful, richly labelled 3D dataset. And then? Too often it lands on a hard drive, or gets flattened into a static 3D model that no one else can edit, &#8230;]]></description>
		
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		<title>Goby gummies: the fish ‘lolly’ that provides a window to study predation underwater</title>
		<link>https://methodsblog.com/2026/06/22/goby-gummies-the-fish-lolly-that-provides-a-window-to-study-predation-underwater/</link>
					<comments>https://methodsblog.com/2026/06/22/goby-gummies-the-fish-lolly-that-provides-a-window-to-study-predation-underwater/#respond</comments>
		
		<dc:creator><![CDATA[plydtanthera]]></dc:creator>
		<pubDate>Mon, 22 Jun 2026 16:30:43 +0000</pubDate>
				<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Field Methods]]></category>
		<category><![CDATA[Practical Tools]]></category>
		<category><![CDATA[Methods in Ecology and Evolution]]></category>
		<category><![CDATA[predation]]></category>
		<category><![CDATA[Predator-Prey Interactions]]></category>
		<category><![CDATA[Trophic ecology]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16510</guid>

					<description><![CDATA[Post provided by Christopher Hemingson Close your eyes and picture a predation event. Personally, I default to the Planet Earth series’ “Mountains” episode, in which a snow leopard acrobatically chases a mountain goat across near-vertical cliffs in an adrenaline-inducing pursuit. While iconic, predation sequences like this one generally represent the minority. More often than not, predation events occur on the order of split seconds – &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16510</post-id>
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		<item>
		<title>RAPID re-identification of patterned animals</title>
		<link>https://methodsblog.com/2026/06/22/rapid-re-identification-of-patterned-animals/</link>
					<comments>https://methodsblog.com/2026/06/22/rapid-re-identification-of-patterned-animals/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Mon, 22 Jun 2026 04:00:00 +0000</pubDate>
				<category><![CDATA[Ecology]]></category>
		<category><![CDATA[Animal identification]]></category>
		<category><![CDATA[Drone]]></category>
		<category><![CDATA[RAPID]]></category>
		<category><![CDATA[Zebra]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16489</guid>

					<description><![CDATA[Post provided by András Zábó Just imagine&#8230; You&#8217;re all sitting excitedly around the monitor, watching the video captured by the drone. This is the first time you&#8217;ve tested the complete monitoring system in the national park&#8230; Your drones had already been capable of autonomously finding, detecting, and tracking zebras, but you had never flown drones that were also capable of identifying individual zebras&#8230; And both &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16489</post-id>
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		<item>
		<title>Why we built a new approach to field sampling for soil eDNA</title>
		<link>https://methodsblog.com/2026/06/08/why-we-built-a-new-approach-to-field-sampling-for-soil-edna/</link>
					<comments>https://methodsblog.com/2026/06/08/why-we-built-a-new-approach-to-field-sampling-for-soil-edna/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Mon, 08 Jun 2026 09:00:00 +0000</pubDate>
				<category><![CDATA[Practical Tools]]></category>
		<category><![CDATA[Ecological Communities]]></category>
		<category><![CDATA[eDNA]]></category>
		<category><![CDATA[Land management]]></category>
		<category><![CDATA[Method]]></category>
		<category><![CDATA[Sampling]]></category>
		<category><![CDATA[Soil sampling]]></category>
		<category><![CDATA[Sustainable agriculture]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16453</guid>

					<description><![CDATA[Post provided by Karen Dyson and Kayla Aburida When we first started using soil environmental DNA (eDNA) to understand how sustainable farming practices affect biodiversity, we thought the hard parts would be in the lab or the analysis. We were wrong. Instead, one of the biggest challenges came much earlier: in the field when collecting data. Soil eDNA is patchy, shaped by microhabitats, plant cover, &#8230;]]></description>
		
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	</item>
		<item>
		<title>From video to behaviour: new tool for automated nest monitoring</title>
		<link>https://methodsblog.com/2026/06/04/from-video-to-behaviour-new-tool-for-automated-nest-monitoring/</link>
					<comments>https://methodsblog.com/2026/06/04/from-video-to-behaviour-new-tool-for-automated-nest-monitoring/#respond</comments>
		
		<dc:creator><![CDATA[Harriet Rhodes]]></dc:creator>
		<pubDate>Thu, 04 Jun 2026 14:30:49 +0000</pubDate>
				<category><![CDATA[Practical Tools]]></category>
		<category><![CDATA[Animal Behaviour]]></category>
		<category><![CDATA[Behavioural Ecology]]></category>
		<category><![CDATA[Bird]]></category>
		<category><![CDATA[Deep-learning]]></category>
		<category><![CDATA[Nest]]></category>
		<category><![CDATA[YOLO]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16465</guid>

					<description><![CDATA[Post provided by Liliana Silva Why we developed this automation framework Observing animal behaviour is one of the most widely used methods in ecology. But anyone who has spent hours viewing video footage knows how quickly behavioural analysis becomes overwhelming. A single nest camera can generate hundreds of hours of recordings, and turning those videos into behavioural data often means endless manual annotation. As a &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16465</post-id>
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		<title>Processing visual survey data with sampley</title>
		<link>https://methodsblog.com/2026/05/29/processing-visual-survey-data-with-sampley/</link>
					<comments>https://methodsblog.com/2026/05/29/processing-visual-survey-data-with-sampley/#respond</comments>
		
		<dc:creator><![CDATA[plydtanthera]]></dc:creator>
		<pubDate>Fri, 29 May 2026 11:12:11 +0000</pubDate>
				<category><![CDATA[Code and Applications]]></category>
		<category><![CDATA[Ecology]]></category>
		<category><![CDATA[data processing]]></category>
		<category><![CDATA[ecological models]]></category>
		<category><![CDATA[grids]]></category>
		<category><![CDATA[Python package]]></category>
		<category><![CDATA[samples]]></category>
		<category><![CDATA[Visual survey data]]></category>
		<guid isPermaLink="false">http://methodsblog.com/?p=16429</guid>

					<description><![CDATA[Post provided by Jonathan Syme Picture this idyllic scene: You’re on a research vessel that is steadily making its way through the vast blue sea, surveying back and forth along a set of transect lines, its track recorded by a GPS. Through your binoculars, you see a column of spray, an arching back, a fluke that rises high above the water, then disappears. You call &#8230;]]></description>
		
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		<post-id xmlns="com-wordpress:feed-additions:1">16429</post-id>
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